Stochastic interest rates in the analysis of energy investments: Implications on economic performance and sustainability

International Nuclear Information System (INIS)

Tolis, Athanasios; Tatsiopoulos, Ilias; Doukelis, Aggelos

2010-01-01

A systematic impact assessment of stochastic interest and inflation rates on the analysis of energy investments is presented. A real-options algorithm has been created for this task. Constant interest rates incorporating high risk premium have been extensively used for economic calculations, within the framework of traditional direct cash flow methods, thus favouring immediate, irreversible investments in the expense of, sometimes, insubstantially low anticipated yields. In this article, not only incomes and expenses but also interest and inflation rates are considered stochastically evolving according to specific probabilistic models. The numerical experiments indicated that the stochastic interest rate forecasts fluctuate in such low levels that may signal delayed investment entry in favour of higher expected yields. The implementation of stochastically evolving interest rates in energy investment analysis may have a controversial effect on sustainability. Displacements of inefficient plants may be significantly delayed, thus prolonging high CO 2 emission rates. Under the current CO 2 allowance prices or their medium-term forecasts, this situation may not be improved and flexible policy interventions may be necessitated. (author)

Stochastic Economic Dispatch with Wind using Versatile Probability Distribution and L-BFGS-B Based Dual Decomposition

DEFF Research Database (Denmark)

Huang, Shaojun; Sun, Yuanzhang; Wu, Qiuwei

2018-01-01

This paper focuses on economic dispatch (ED) in power systems with intermittent wind power, which is a very critical issue in future power systems. A stochastic ED problem is formed based on the recently proposed versatile probability distribution (VPD) of wind power. The problem is then analyzed...

Robustness of Populations in Stochastic Environments

DEFF Research Database (Denmark)

Gießen, Christian; Kötzing, Timo

2016-01-01

We consider stochastic versions of OneMax and LeadingOnes and analyze the performance of evolutionary algorithms with and without populations on these problems. It is known that the (1+1) EA on OneMax performs well in the presence of very small noise, but poorly for higher noise levels. We extend...... the abilities of the (1+1) EA. Larger population sizes are even more beneficial; we consider both parent and offspring populations. In this sense, populations are robust in these stochastic settings....

Economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

Science.gov (United States)

Smith, R L; Al-Mamun, M A; Gröhn, Y T

2017-03-01

The cost of paratuberculosis to dairy herds, through decreased milk production, early culling, and poor reproductive performance, has been well-studied. The benefit of control programs, however, has been debated. A recent stochastic compartmental model for paratuberculosis transmission in US dairy herds was modified to predict herd net present value (NPV) over 25 years in herds of 100 and 1000 dairy cattle with endemic paratuberculosis at initial prevalence of 10% and 20%. Control programs were designed by combining 5 tests (none, fecal culture, ELISA, PCR, or calf testing), 3 test-related culling strategies (all test-positive, high-positive, or repeated positive), 2 test frequencies (annual and biannual), 3 hygiene levels (standard, moderate, or improved), and 2 cessation decisions (testing ceased after 5 negative whole-herd tests or testing continued). Stochastic dominance was determined for each herd scenario; no control program was fully dominant for maximizing herd NPV in any scenario. Use of the ELISA test was generally preferred in all scenarios, but no paratuberculosis control was highly preferred for the small herd with 10% initial prevalence and was frequently preferred in other herd scenarios. Based on their effect on paratuberculosis alone, hygiene improvements were not found to be as cost-effective as test-and-cull strategies in most circumstances. Global sensitivity analysis found that economic parameters, such as the price of milk, had more influence on NPV than control program-related parameters. We conclude that paratuberculosis control can be cost effective, and multiple control programs can be applied for equivalent economic results. Copyright © 2017 Elsevier B.V. All rights reserved.

e-Dairy: a dynamic and stochastic whole-farm model that predicts biophysical and economic performance of grazing dairy systems.

Science.gov (United States)

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N

2013-05-01

A whole-farm, stochastic and dynamic simulation model was developed to predict biophysical and economic performance of grazing dairy systems. Several whole-farm models simulate grazing dairy systems, but most of them work at a herd level. This model, named e-Dairy, differs from the few models that work at an animal level, because it allows stochastic behaviour of the genetic merit of individual cows for several traits, namely, yields of milk, fat and protein, live weight (LW) and body condition score (BCS) within a whole-farm model. This model accounts for genetic differences between cows, is sensitive to genotype × environment interactions at an animal level and allows pasture growth, milk and supplements price to behave stochastically. The model includes an energy-based animal module that predicts intake at grazing, mammary gland functioning and body lipid change. This whole-farm model simulates a 365-day period for individual cows within a herd, with cow parameters randomly generated on the basis of the mean parameter values, defined as input and variance and co-variances from experimental data sets. The main inputs of e-Dairy are farm area, use of land, type of pasture, type of crops, monthly pasture growth rate, supplements offered, nutritional quality of feeds, herd description including herd size, age structure, calving pattern, BCS and LW at calving, probabilities of pregnancy, average genetic merit and economic values for items of income and costs. The model allows to set management policies to define: dry-off cows (ceasing of lactation), target pre- and post-grazing herbage mass and feed supplementation. The main outputs are herbage dry matter intake, annual pasture utilisation, milk yield, changes in BCS and LW, economic farm profit and return on assets. The model showed satisfactory accuracy of prediction when validated against two data sets from farmlet system experiments. Relative prediction errors were <10% for all variables, and concordance

INTERRELATIONSHIP S BETWEEN HEALTH, ENVIRONMENT QUALITY AND ECONOMIC ACTIVITY: WHAT CONSEQUENCES FOR ECONOMIC CONVERGENCE?

Directory of Open Access Journals (Sweden)

Alassane Drabo

2010-03-01

Full Text Available This paper examines the link between health indicators, environmental variables and economic development, and th e consequences of this relationship on economic convergence for a large sample of rich and poor countries. While in economic literature income and environment are seen to have an inverted-U shaped relationship (Environment Kuznets Curve hypothesis, it is also well established that an improvement in environmental quality is positively related to health. Our study focuses on the implications of this relationship for economic convergence. In the early stage of economic development, the gain from income growth could be cancelled or mitigated by environmental degradation through populations' health (and other channels and create a vicious circle in economic activity unlike in developed countries. This in turn could slow down economic convergence. To empirically assess these issues, we proceeded to an econometric analysis through three equations: a growth equation, a health equation and an environment equation. We found that health is a channel through which environment impacts economic growth. When we take into account the effect of environment quality on economic growth, the speed of convergence tends to increase slightly. This shows that environmental quality could be considered as a constraint for economic convergence.

ENVIRONMENT: a computational platform to stochastically simulate reacting and self-reproducing lipid compartments

Science.gov (United States)

Mavelli, Fabio; Ruiz-Mirazo, Kepa

2010-09-01

'ENVIRONMENT' is a computational platform that has been developed in the last few years with the aim to simulate stochastically the dynamics and stability of chemically reacting protocellular systems. Here we present and describe some of its main features, showing how the stochastic kinetics approach can be applied to study the time evolution of reaction networks in heterogeneous conditions, particularly when supramolecular lipid structures (micelles, vesicles, etc) coexist with aqueous domains. These conditions are of special relevance to understand the origins of cellular, self-reproducing compartments, in the context of prebiotic chemistry and evolution. We contrast our simulation results with real lab experiments, with the aim to bring together theoretical and experimental research on protocell and minimal artificial cell systems.

Stochastic pump effect and geometric phases in dissipative and stochastic systems

Energy Technology Data Exchange (ETDEWEB)

Sinitsyn, Nikolai [Los Alamos National Laboratory

2008-01-01

The success of Berry phases in quantum mechanics stimulated the study of similar phenomena in other areas of physics, including the theory of living cell locomotion and motion of patterns in nonlinear media. More recently, geometric phases have been applied to systems operating in a strongly stochastic environment, such as molecular motors. We discuss such geometric effects in purely classical dissipative stochastic systems and their role in the theory of the stochastic pump effect (SPE).

Persistence and extinction of a stochastic single-species population model in a polluted environment with impulsive toxicant input

Directory of Open Access Journals (Sweden)

Meng Liu

2013-10-01

Full Text Available A stochastic single-species population system in a polluted environment with impulsive toxicant input is proposed and studied. Sufficient conditions for extinction, non-persistence in the mean, strong persistence in the mean and stochastic permanence of the population are established. The threshold between strong persistence in the mean and extinction is obtained. Some simulation figures are introduced to illustrate the main results.

Consumption and environment - ecological economic perspectives

DEFF Research Database (Denmark)

Røpke, Inge

2006-01-01

motivation for dealing with consumption in ecological economics is presented. Basically, ecological economists agree that there are limits to the material growth of the economy, and that these limits have already been reached or exceeded. As there is an ethical challenge to increase environmental space......Consumption and environment – ecological economic perspectives Summary Research on issues related to consumption and environment has grown rapidly since the middle of the 1990s, and several disciplines as well as transdisciplinary fields have contributed to this development. The present papers...... constitute a small part of this wave of interest, and they are mostly framed as belonging to ecological economics. The collection starts with an introduction to the field of consumption research within ecological economics and then follows a series of papers on more specific issues. The introductionary...

Research on nonlinear stochastic dynamical price model

International Nuclear Information System (INIS)

Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

2008-01-01

In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

Characterizing economic trends by Bayesian stochastic model specifi cation search

OpenAIRE

Grassi, Stefano; Proietti, Tommaso

2010-01-01

We apply a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. We illustrate that the methodology can be quite successfully applied to discriminate between stochastic and deterministic trends. In particular, we formulate autoregressive models with stochastic trends components and decide on whether a specific feature of the series, i.e. the underlying level and/or the rate...

R&D Project Valuation Considering Changes of Economic Environment: A Case of a Pharmaceutical R&D Project

Directory of Open Access Journals (Sweden)

Jung Ho Park

2018-03-01

Full Text Available R&D project valuation is important for effective R&D portfolio management through decision making, related to the firm’s R&D productivity, sustainable management. In particular, scholars have emphasized the necessities of capturing option value in R&D and developed methods of real option valuation. However, despite suggesting various real option models, there are few studies on simultaneously employing mean-reverting stochastic process and Markov regime switching to describe the evolution of cash flow and to reflect time-varying parameters resulting from changes of economic environment. Therefore, we suggest a mean-reverting binomial lattice model under Markov regime switching and apply it to evaluate clinical development with project cases of the pharmaceutical industry. This study finds that decision making can be different according to the regime condition, thus the suggested model can capture risks caused by the uncertainty of the economic environment, represented by regime switching. Further, this study simulates the model according to rate parameter from 0.00 to 1.00 and risk-free interest rates for regimes 1 and 2 from ( r 1 = 4%, r 2 = 2% to ( r 1 = 7%, r 2 = 5%, and confirms the rigidity of the model. Therefore, in practice, the mean-reverting binomial lattice model under Markov regime switching proposed in this study for R&D project valuation contributes to assisting company R&D project managers make effective decision making considering current economic environment and future changes.

Computational Investigation of Environment-Noise Interaction in Single-Cell Organisms: The Merit of Expression Stochasticity Depends on the Quality of Environmental Fluctuations.

Science.gov (United States)

Lück, Anja; Klimmasch, Lukas; Großmann, Peter; Germerodt, Sebastian; Kaleta, Christoph

2018-01-10

Organisms need to adapt to changing environments and they do so by using a broad spectrum of strategies. These strategies include finding the right balance between expressing genes before or when they are needed, and adjusting the degree of noise inherent in gene expression. We investigated the interplay between different nutritional environments and the inhabiting organisms' metabolic and genetic adaptations by applying an evolutionary algorithm to an agent-based model of a concise bacterial metabolism. Our results show that constant environments and rapidly fluctuating environments produce similar adaptations in the organisms, making the predictability of the environment a major factor in determining optimal adaptation. We show that exploitation of expression noise occurs only in some types of fluctuating environment and is strongly dependent on the quality and availability of nutrients: stochasticity is generally detrimental in fluctuating environments and beneficial only at equal periods of nutrient availability and above a threshold environmental richness. Moreover, depending on the availability and nutritional value of nutrients, nutrient-dependent and stochastic expression are both strategies used to deal with environmental changes. Overall, we comprehensively characterize the interplay between the quality and periodicity of an environment and the resulting optimal deterministic and stochastic regulation strategies of nutrient-catabolizing pathways.

Recursive utility in a Markov environment with stochastic growth.

Science.gov (United States)

Hansen, Lars Peter; Scheinkman, José A

2012-07-24

Recursive utility models that feature investor concerns about the intertemporal composition of risk are used extensively in applied research in macroeconomics and asset pricing. These models represent preferences as the solution to a nonlinear forward-looking difference equation with a terminal condition. In this paper we study infinite-horizon specifications of this difference equation in the context of a Markov environment. We establish a connection between the solution to this equation and to an arguably simpler Perron-Frobenius eigenvalue equation of the type that occurs in the study of large deviations for Markov processes. By exploiting this connection, we establish existence and uniqueness results. Moreover, we explore a substantive link between large deviation bounds for tail events for stochastic consumption growth and preferences induced by recursive utility.

A Q-Learning Approach to Flocking With UAVs in a Stochastic Environment.

Science.gov (United States)

Hung, Shao-Ming; Givigi, Sidney N

2017-01-01

In the past two decades, unmanned aerial vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, where tasks can be dull, dirty, dangerous, or simply too costly with conventional methods. Many of the applications contain tasks that can be executed in parallel, hence the natural progression is to deploy multiple UAVs working together as a force multiplier. However, to do so requires autonomous coordination among the UAVs, similar to swarming behaviors seen in animals and insects. This paper looks at flocking with small fixed-wing UAVs in the context of a model-free reinforcement learning problem. In particular, Peng's Q(λ) with a variable learning rate is employed by the followers to learn a control policy that facilitates flocking in a leader-follower topology. The problem is structured as a Markov decision process, where the agents are modeled as small fixed-wing UAVs that experience stochasticity due to disturbances such as winds and control noises, as well as weight and balance issues. Learned policies are compared to ones solved using stochastic optimal control (i.e., dynamic programming) by evaluating the average cost incurred during flight according to a cost function. Simulation results demonstrate the feasibility of the proposed learning approach at enabling agents to learn how to flock in a leader-follower topology, while operating in a nonstationary stochastic environment.

Stochastic Pi-calculus Revisited

DEFF Research Database (Denmark)

Cardelli, Luca; Mardare, Radu Iulian

2013-01-01

We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...

Evaluating Economic Alternatives for Wood Energy Supply Based on Stochastic Simulation

Directory of Open Access Journals (Sweden)

Ulises Flores Hernández

2018-04-01

Full Text Available Productive forests, as a major source of biomass, represent an important pre-requisite for the development of a bio-economy. In this respect, assessments of biomass availability, efficiency of forest management, forest operations, and economic feasibility are essential. This is certainly the case for Mexico, a country with an increasing energy demand and a considerable potential for sustainable forest utilization. Hence, this paper focuses on analyzing economic alternatives for the Mexican bioenergy supply based on the costs and revenues of utilizing woody biomass residues. With a regional spatial approach, harvesting and transportation costs of utilizing selected biomass residues were stochastically calculated using Monte Carlo simulations. A sensitivity analysis of percentage variation of the most probable estimate in relation to the parameters price and cost for one alternative using net future analysis was conducted. Based on the results for the northern region, a 10% reduction of the transportation cost would reduce overall supply cost, resulting in a total revenue of 13.69 USD/m3 and 0.75 USD/m3 for harvesting residues and non-extracted stand residues, respectively. For the central south region, it is estimated that a contribution of 16.53 USD/m3 from 2013 and a total revenue of 33.00 USD/m3 in 2030 from sawmill residues will improve the value chain. The given approach and outputs provide the basis for the decision-making process regarding forest utilization towards energy generation based on economic indicators.

Fuzzy Stochastic Optimization Theory, Models and Applications

CERN Document Server

Wang, Shuming

2012-01-01

Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies.   The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...

Stochastic processes in cell biology

CERN Document Server

Bressloff, Paul C

2014-01-01

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

Investment in different sized SMRs: Economic evaluation of stochastic scenarios by INCAS code

International Nuclear Information System (INIS)

Barenghi, S.; Boarin, S.; Ricotti, M. E.

2012-01-01

Small Modular LWR concepts are being developed and proposed to investors worldwide. They capitalize on operating track record of GEN II LWR, while introducing innovative design enhancements allowed by smaller size and additional benefits from the higher degree of modularization and from deployment of multiple units on the same site. (i.e. 'Economy of Multiple' paradigm) Nevertheless Small Modular Reactors pay for a dis-economy of scale that represents a relevant penalty on a capital intensive investment. Investors in the nuclear power generation industry face a very high financial risk, due to high capital commitment and exceptionally long pay-back time. Investment risk arise from uncertainty that affects scenario conditions over such a long time horizon. Risk aversion is increased by current adverse conditions of financial markets and general economic downturn, as is the case nowadays. This work investigates both the investment profitability and risk of alternative investments in a single Large Reactor or in multiple SMR of different sizes drawing information from project's Internal Rate of Return stochastic distribution. multiple SMR deployment on a single site with total power installed, equivalent to a single LR. Uncertain scenario conditions and stochastic input assumptions are included in the analysis, representing investment uncertainty and risk. Results show that, despite the combination of much larger number of stochastic variables in SMR fleets, uncertainty of project profitability is not increased, as compared to LR: SMR have features able to smooth IRR variance and control investment risk. Despite dis-economy of scale, SMR represent a limited capital commitment and a scalable investment option that meet investors' interest, even in developed and mature markets, that are traditional marketplace for LR. (authors)

NATURE OF BUSINESS ENVIRONMENT IN INTERNATIONAL ECONOMIC RELATIONS

Directory of Open Access Journals (Sweden)

Zlatka Kushelieva

2017-06-01

Full Text Available The role and importance of the factors influencing the business environment in the economic relations of enterprises in national and international aspect are discussed. Global interdependencies have been explored and results have been drawn on the impact of international political and economic changes on the business environment of national and supranational companies.

Spatial stochastic regression modelling of urban land use

International Nuclear Information System (INIS)

Arshad, S H M; Jaafar, J; Abiden, M Z Z; Latif, Z A; Rasam, A R A

2014-01-01

Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. This results in innumerable benefits of the quantity and quality of the urban environment and lifestyle but on the other hand contributes to unbounded development, urban sprawl, overcrowding and decreasing standard of living. Regulation and observation of urban development activities is crucial. The understanding of urban systems that promotes urban growth are also essential for the purpose of policy making, formulating development strategies as well as development plan preparation. This study aims to compare two different stochastic regression modeling techniques for spatial structure models of urban growth in the same specific study area. Both techniques will utilize the same datasets and their results will be analyzed. The work starts by producing an urban growth model by using stochastic regression modeling techniques namely the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR). The two techniques are compared to and it is found that, GWR seems to be a more significant stochastic regression model compared to OLS, it gives a smaller AICc (Akaike's Information Corrected Criterion) value and its output is more spatially explainable

Oriented stochastic data envelopment models: ranking comparison to stochastic frontier approach

Czech Academy of Sciences Publication Activity Database

Brázdik, František

-, č. 271 (2005), s. 1-46 ISSN 1211-3298 Institutional research plan: CEZ:AV0Z70850503 Keywords : stochastic data envelopment analysis * linear programming * rice farm Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp271.pdf

A stochastic model for the derivation of economic values and their standard deviations for production and functional traits in dairy cattle

DEFF Research Database (Denmark)

Nielsen, Hanne-Marie; Groen, A F; Østergaard, Søren

2006-01-01

The objective of this paper was to present a model of a dairy cattle production system for the derivation of economic values and their standard deviations for both production and functional traits under Danish production circumstances. The stochastic model used is dynamic, and simulates production...... was -0.94 €/day per cow-year. Standard deviations of economic values expressing variation in realised profit of a farm before and after a genetic change were computed using a linear Taylor series expansion. Expressed as coefficient of variation, standard deviations of economic values based on 1000...

A stochastic model for the derivation of economic values and their standard deviations for production and functional traits in dairy cattle

NARCIS (Netherlands)

Nielsen, H.M.; Groen, A.F.; Ostergaard, S.; Berg, P.

2006-01-01

The objective of this paper was to present a model of a dairy cattle production system for the derivation of economic values and their standard deviations for both production and functional traits under Danish production circumstances. The stochastic model used is dynamic, and simulates production

Investment in different sized SMRs: Economic evaluation of stochastic scenarios by INCAS code

Energy Technology Data Exchange (ETDEWEB)

Barenghi, S.; Boarin, S.; Ricotti, M. E. [Politecnico di Milano, Dept. of Energy, CeSNEF-Nuclear Engineering Div., via La Masa 34, 20156 Milano (Italy)

2012-07-01

Small Modular LWR concepts are being developed and proposed to investors worldwide. They capitalize on operating track record of GEN II LWR, while introducing innovative design enhancements allowed by smaller size and additional benefits from the higher degree of modularization and from deployment of multiple units on the same site. (i.e. 'Economy of Multiple' paradigm) Nevertheless Small Modular Reactors pay for a dis-economy of scale that represents a relevant penalty on a capital intensive investment. Investors in the nuclear power generation industry face a very high financial risk, due to high capital commitment and exceptionally long pay-back time. Investment risk arise from uncertainty that affects scenario conditions over such a long time horizon. Risk aversion is increased by current adverse conditions of financial markets and general economic downturn, as is the case nowadays. This work investigates both the investment profitability and risk of alternative investments in a single Large Reactor or in multiple SMR of different sizes drawing information from project's Internal Rate of Return stochastic distribution. multiple SMR deployment on a single site with total power installed, equivalent to a single LR. Uncertain scenario conditions and stochastic input assumptions are included in the analysis, representing investment uncertainty and risk. Results show that, despite the combination of much larger number of stochastic variables in SMR fleets, uncertainty of project profitability is not increased, as compared to LR: SMR have features able to smooth IRR variance and control investment risk. Despite dis-economy of scale, SMR represent a limited capital commitment and a scalable investment option that meet investors' interest, even in developed and mature markets, that are traditional marketplace for LR. (authors)

Economics for the Environment: Research Capacity Building in ...

International Development Research Centre (IDRC) Digital Library (Canada)

Economics for the Environment: Research Capacity Building in South Asia. This project will enhance environmental economics research capacity in South Asia through a program of research grants, training, and networking. It provides funds to the South Asian Network for Development and Environmental Economics ...

Stochastic Dominance under the Nonlinear Expected Utilities

Directory of Open Access Journals (Sweden)

Xinling Xiao

2014-01-01

Full Text Available In 1947, von Neumann and Morgenstern introduced the well-known expected utility and the related axiomatic system (see von Neumann and Morgenstern (1953. It is widely used in economics, for example, financial economics. But the well-known Allais paradox (see Allais (1979 shows that the linear expected utility has some limitations sometimes. Because of this, Peng proposed a concept of nonlinear expected utility (see Peng (2005. In this paper we propose a concept of stochastic dominance under the nonlinear expected utilities. We give sufficient conditions on which a random choice X stochastically dominates a random choice Y under the nonlinear expected utilities. We also provide sufficient conditions on which a random choice X strictly stochastically dominates a random choice Y under the sublinear expected utilities.

Economic Growth and the Environment. An empirical analysis

Energy Technology Data Exchange (ETDEWEB)

De Bruyn, S.M.

1999-12-21

A number of economists have claimed that economic growth benefits environmental quality as it raises political support and financial means for environmental policy measures. Since the early 1990s this view has increasingly been supported by empirical evidence that has challenged the traditional belief held by environmentalists that economic growth degrades the environment. This study investigates the relationship between economic growth and environmental quality and elaborates the question whether economic growth can be combined with a reduced demand for natural resources. Various hypotheses on this relationship are described and empirically tested for a number of indicators of environmental pressure. The outcome of the tests advocates the use of alternative models for estimation that alter conclusions about the relationship between economic growth and the environment and give insight into the driving forces of emission reduction in developed economies. refs.

Brownian motion and stochastic calculus

CERN Document Server

Karatzas, Ioannis

1998-01-01

This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...

Obesity and economic environments.

Science.gov (United States)

Sturm, Roland; An, Ruopeng

2014-01-01

This review summarizes current understanding of economic factors during the obesity epidemic and dispels some widely held, but incorrect, beliefs. Rising obesity rates coincided with increases in leisure time (rather than increased work hours), increased fruit and vegetable availability (rather than a decline in healthier foods), and increased exercise uptake. As a share of disposable income, Americans now have the cheapest food available in history, which fueled the obesity epidemic. Weight gain was surprisingly similar across sociodemographic groups or geographic areas, rather than specific to some groups (at every point in time; however, there are clear disparities). It suggests that if one wants to understand the role of the environment in the obesity epidemic, one needs to understand changes over time affecting all groups, not differences between subgroups at a given time. Although economic and technological changes in the environment drove the obesity epidemic, the evidence for effective economic policies to prevent obesity remains limited. Taxes on foods with low nutritional value could nudge behavior toward healthier diets, as could subsidies/discounts for healthier foods. However, even a large price change for healthy foods could close only part of the gap between dietary guidelines and actual food consumption. Political support has been lacking for even moderate price interventions in the United States and this may continue until the role of environmental factors is accepted more widely. As opinion leaders, clinicians play an important role in shaping the understanding of the causes of obesity. © 2014 American Cancer Society.

New travelling wave solutions for nonlinear stochastic evolution

Indian Academy of Sciences (India)

The nonlinear stochastic evolution equations have a wide range of applications in physics, chemistry, biology, economics and finance from various points of view. In this paper, the (′/)-expansion method is implemented for obtaining new travelling wave solutions of the nonlinear (2 + 1)-dimensional stochastic ...

Environmental and Economic Optimization Model for Electric System Planning in Ningxia, China: Inexact Stochastic Risk-Aversion Programming Approach

Directory of Open Access Journals (Sweden)

L. Ji

2015-01-01

Full Text Available The main goal of this paper is to provide a novel risk aversion model for long-term electric power system planning from the manager’s perspective with the consideration of various uncertainties. In the proposed method, interval parameter programming and two-stage stochastic programming are integrated to deal with the technical, economics, and policy uncertainties. Moreover, downside risk theory is introduced to balance the trade-off between the profit and risk according to the decision-maker’s risk aversion attitude. To verify the effectiveness and practical application of this approach, an inexact stochastic risk aversion model is developed for regional electric system planning and management in Ningxia Hui Autonomous Region, China. The series of solutions provide the decision-maker with the optimal investment strategy and operation management under different future emission reduction scenarios and risk-aversion levels. The results indicated that pollution control devices are still the main measures to achieve the current mitigation goal and the adjustment of generation structure would play an important role in the future cleaner electricity system with the stricter environmental policy. In addition, the model can be used for generating decision alternatives and helping decision-makers identify desired energy structure adjustment and pollutants/carbon mitigation abatement policies under various economic and system-reliability constraints.

A Stochastic Water Balance Framework for Lowland Watersheds

Science.gov (United States)

Thompson, Sally; MacVean, Lissa; Sivapalan, Murugesu

2017-11-01

The water balance dynamics in lowland watersheds are influenced not only by local hydroclimatic controls on energy and water availability, but also by imports of water from the upstream watershed. These imports result in a stochastic extent of inundation in lowland watersheds that is determined by the local flood regime, watershed topography, and the rate of loss processes such as drainage and evaporation. Thus, lowland watershed water balances depend on two stochastic processes—rainfall and local inundation dynamics. Lowlands are high productivity environments that are disproportionately associated with urbanization, high productivity agriculture, biodiversity, and flood risk. Consequently, they are being rapidly altered by human development—generally with clear economic and social motivation—but also with significant trade-offs in ecosystem services provision, directly related to changes in the components and variability of the lowland water balance. We present a stochastic framework to assess the lowland water balance and its sensitivity to two common human interventions—replacement of native vegetation with alternative land uses, and construction of local flood protection levees. By providing analytical solutions for the mean and PDF of the water balance components, the proposed framework provides a mechanism to connect human interventions to hydrologic outcomes, and, in conjunction with ecosystem service production estimates, to evaluate trade-offs associated with lowland watershed development.

International symposium on energy, environment and economics: Transactions

International Nuclear Information System (INIS)

Colville, E.J.

1995-01-01

The conference deals with a comprehensive range of topics on energy sources and technologies, the economic impacts of energy use and production, and environmental issues. The papers are grouped into chapters covering environmental policy, environment education, environment economics, new and renewable energy sources, utilities, electricity and planning software, domestic energy, commercial energy, heat pumps and cogeneration, and transport. A number of un-presented papers and abstracts of contributions are included. Relevant papers are individually indexed/abstracted. Tabs. figs., refs

A fuzzy stochastic framework for managing hydro-environmental and socio-economic interactions under uncertainty

Science.gov (United States)

Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens

2014-05-01

An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater

Stochastic Signal Processing for Sound Environment System with Decibel Evaluation and Energy Observation

Directory of Open Access Journals (Sweden)

Akira Ikuta

2014-01-01

Full Text Available In real sound environment system, a specific signal shows various types of probability distribution, and the observation data are usually contaminated by external noise (e.g., background noise of non-Gaussian distribution type. Furthermore, there potentially exist various nonlinear correlations in addition to the linear correlation between input and output time series. Consequently, often the system input and output relationship in the real phenomenon cannot be represented by a simple model using only the linear correlation and lower order statistics. In this study, complex sound environment systems difficult to analyze by using usual structural method are considered. By introducing an estimation method of the system parameters reflecting correlation information for conditional probability distribution under existence of the external noise, a prediction method of output response probability for sound environment systems is theoretically proposed in a suitable form for the additive property of energy variable and the evaluation in decibel scale. The effectiveness of the proposed stochastic signal processing method is experimentally confirmed by applying it to the observed data in sound environment systems.

Economic Efficiency of Artisanal Fishing Households under Oil Pollution Environment in the Niger Delta Region of Nigeria

Directory of Open Access Journals (Sweden)

Gbigbi, TM.

2014-01-01

Full Text Available Fish supplies more than 87% of the animal protein in Nigeria, and more than 90% of coastal communities depend solely on fishing and fisheries related activities for their survival. Available information however, shows that Nigeria's inland water bodies are producing less than 13% of their estimated fishery potential. And domestic demand for fish has never been met by dependence on output from available aquatic sources. Nigeria therefore imports over US$ 200 million worth of frozen fish per annum. The capacity of artisanal fisheries to play its role of bridging this food gap, providing employment and generating income, particularly for the coastal communities in Nigeria, will largely depend on the adoption of appropriate management strategies that will ensure efficiency and sustainability given their debilitating oil pollution environment. This study employed a Cobb- Douglas stochastic frontier cost function to measure the level of economic efficiency and its determinants among these households. A multi-stage random sampling technique was used to select 160 respondents from whom input-output data, prices and socioeconomic characteristics were obtained. The results of the analysis showed that individual levels of economic efficiency ranged from 0.10 - 0.96 with a mean of 0.68. While age, household size and number of fishing trips made in a week decreased, access to credit, membership of co-operative society, and oil spill increased, significantly, the respondents' level of economic inefficiency. These observations particularly suggest that the farmers were yet to harness the potentials of farm credit and membership of cooperative societies in their farm business, perhaps as a result of poverty. We recommend training workshops and seminars to remedy this. There is also the need for policies that could compel oil companies to minimize oil spill within the farmers' fishing environment. The adverse effects of oil spill on the environment and the

Stochastic Modeling and Optimization in a Microgrid: A Survey

Directory of Open Access Journals (Sweden)

Hao Liang

2014-03-01

Full Text Available The future smart grid is expected to be an interconnected network of small-scale and self-contained microgrids, in addition to a large-scale electric power backbone. By utilizing microsources, such as renewable energy sources and combined heat and power plants, microgrids can supply electrical and heat loads in local areas in an economic and environment friendly way. To better adopt the intermittent and weather-dependent renewable power generation, energy storage devices, such as batteries, heat buffers and plug-in electric vehicles (PEVs with vehicle-to-grid systems can be integrated in microgrids. However, significant technical challenges arise in the planning, operation and control of microgrids, due to the randomness in renewable power generation, the buffering effect of energy storage devices and the high mobility of PEVs. The two-way communication functionalities of the future smart grid provide an opportunity to address these challenges, by offering the communication links for microgrid status information collection. However, how to utilize stochastic modeling and optimization tools for efficient, reliable and economic planning, operation and control of microgrids remains an open issue. In this paper, we investigate the key features of microgrids and provide a comprehensive literature survey on the stochastic modeling and optimization tools for a microgrid. Future research directions are also identified.

Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

International Nuclear Information System (INIS)

Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen

2017-01-01

Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

New Directions in the Economic Theory of the Environment

Science.gov (United States)

Carraro, Carlo; Siniscalco, Domenico

1998-01-01

This volume provides a broad survey of the recent developments in the new economics of the environment and reports the state of the art on a new set of environmental problems, analytical tools and economic policies. Throughout the volume environmental problems are analyzed in an open, generally noncompetitive economy with transnational or global externalities. The first part deals with the relationship between the environment, economic growth and technological innovation. The second part analyzes the optimal design of environmental taxation, while the third part considers the international dimension of environmental policy.

The impact of the economic environment on financial reports

Directory of Open Access Journals (Sweden)

Valentin Burcă

2011-06-01

Full Text Available Financial reporting represents a current issue of economic environment, given globalization and the recent economic crisis. Accounting -as profession - along with the investors and state institutions have started a comprehensive project of accounting convergence designed to improve the comparability of accounting information released by financial statements synthesis. The success of the project can only be provided by taking into account several constraints imposed by the economic environment, and not only. Therefore, attention must be paid to the voice of capital markets and large multinational corporations regarding the future development of financial reporting.

Fuzzy Stochastic Optimal Guaranteed Cost Control of Bio-Economic Singular Markovian Jump Systems.

Science.gov (United States)

Li, Li; Zhang, Qingling; Zhu, Baoyan

2015-11-01

This paper establishes a bio-economic singular Markovian jump model by considering the price of the commodity as a Markov chain. The controller is designed for this system such that its biomass achieves the specified range with the least cost in a finite-time. Firstly, this system is described by Takagi-Sugeno fuzzy model. Secondly, a new design method of fuzzy state-feedback controllers is presented to ensure not only the regularity, nonimpulse, and stochastic singular finite-time boundedness of this kind of systems, but also an upper bound achieved for the cost function in the form of strict linear matrix inequalities. Finally, two examples including a practical example of eel seedling breeding are given to illustrate the merit and usability of the approach proposed in this paper.

A stochastic model for simulation of the economic consequences of bovine virus diarrhoea virus infection in a dairy herd

DEFF Research Database (Denmark)

Sørensen, J.T.; Enevoldsen, Carsten; Houe, H.

1995-01-01

A dynamic, stochastic model simulating the technical and economic consequences of bovine virus diarrhoea virus (BVDV) infections for a dairy cattle herd for use on a personal computer was developed. The production and state changes of the herd were simulated by state changes of the individual cows...... and heifers. All discrete events at the cow level were triggered stochastically. Each cow and heifer was characterized by state variables such as stage of lactation, parity, oestrous status, decision for culling, milk production potential, and immune status for BVDV. The model was controlled by 170 decision...... variables describing biologic and management variables including 21 decision variables describing the effect of BVDV infection on the production of the individual animal. Two markedly different scenarios were simulated to demonstrate the behaviour of the developed model and the potentials of the applied...

Stochastic Growth Models with No Discounting

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

2007-01-01

Roč. 15, č. 4 (2007), s. 88-98 ISSN 0572-3043 R&D Projects: GA ČR(CZ) GA402/06/0990; GA ČR GA402/05/0115 Institutional research plan: CEZ:AV0Z10750506 Keywords : economic dynamics * stochastic version of the Ramsey growth model * Markov decision processes Subject RIV: AH - Economics

CORPORATE BUSINESS ENVIRONMENT AS A SET OF ECONOMIC CONDITIONS FOR BUSINESS DEVELOPMENT

Directory of Open Access Journals (Sweden)

Svetlana A. Gusar

2015-01-01

Full Text Available Intellectual resources are widely used in the formation of corporate business environment. This environment is a new phenomenon in the system of socio-economic relations. The corporate business environment is a set of economic conditions for the development of entrepreneurship, business life. In this environment, exercise more incentives to work, increasing the level of economic freedom, including the freedom of movement of the resource, including intellectual, production components. It is therefore important and necessary to give its definition from the perspective of both economic and organizational-administrative relations, which is a key objective of this research. In addition, the article carried out a comprehensive assessment of how the corporate environment for the development of regional business and knowledge of the mechanisms of the effect of factors internal and external environment for the development of corporate business environment.

A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty

Science.gov (United States)

Llopis-Albert, Carlos; Palacios-Marqués, Daniel; Merigó, José M.

2014-04-01

In this paper a methodology for the stochastic management of groundwater quality problems is presented, which can be used to provide agricultural advisory services. A stochastic algorithm to solve the coupled flow and mass transport inverse problem is combined with a stochastic management approach to develop methods for integrating uncertainty; thus obtaining more reliable policies on groundwater nitrate pollution control from agriculture. The stochastic inverse model allows identifying non-Gaussian parameters and reducing uncertainty in heterogeneous aquifers by constraining stochastic simulations to data. The management model determines the spatial and temporal distribution of fertilizer application rates that maximizes net benefits in agriculture constrained by quality requirements in groundwater at various control sites. The quality constraints can be taken, for instance, by those given by water laws such as the EU Water Framework Directive (WFD). Furthermore, the methodology allows providing the trade-off between higher economic returns and reliability in meeting the environmental standards. Therefore, this new technology can help stakeholders in the decision-making process under an uncertainty environment. The methodology has been successfully applied to a 2D synthetic aquifer, where an uncertainty assessment has been carried out by means of Monte Carlo simulation techniques.

Stochastic modeling of economic injury levels with respect to yearly trends in price commodity.

Science.gov (United States)

Damos, Petros

2014-05-01

The economic injury level (EIL) concept integrates economics and biology and uses chemical applications in crop protection only when economic loss by pests is anticipated. The EIL is defined by five primary variables: the cost of management tactic per production unit, the price of commodity, the injury units per pest, the damage per unit injury, and the proportionate reduction of injury averted by the application of a tactic. The above variables are related according to the formula EIL = C/VIDK. The observable dynamic alteration of the EIL due to its different parameters is a major characteristic of its concept. In this study, the yearly effect of the economic variables is assessed, and in particular the influence of the parameter commodity value on the shape of the EIL function. In addition, to predict the effects of the economic variables on the EIL level, yearly commodity values were incorporated in the EIL formula and the generated outcomes were further modelled with stochastic linear autoregressive models having different orders. According to the AR(1) model, forecasts for the five-year period of 2010-2015 ranged from 2.33 to 2.41 specimens per sampling unit. These values represent a threshold that is in reasonable limits to justify future control actions. Management actions as related to productivity and price commodity significantly affect costs of crop production and thus define the adoption of IPM and sustainable crop production systems at local and international levels. This is an open access paper. We use the Creative Commons Attribution 3.0 license that permits unrestricted use, provided that the paper is properly attributed.

Library macro-environment: New technological and economic rules

Directory of Open Access Journals (Sweden)

Karmen Štular-Sotošek

2003-01-01

Full Text Available Fast and flexible adaptation to changes in the macro-environment is also crucial for libraries, which have to review them, respond to them and become a part of them. Consequently, the application of marketing science and tools helps libraries to find out how to survive in the competitive world and how to become better and stronger. The article, which draws from marketing, economic and information disciplines, introduces the main principles in the technological and economic environment of libraries and finds the knowledge about these disciplines to be most crucial for successful management of modern libraries, especially on the pretentious publishing market and on the market of information suppliers. Within the technological and economic environment, the cooperation is the only logical solution, which benefits the producers of information services and products as well as libraries. The following text finds that libraries will achieve long-term success and will be proactive in developing partnerships only by using relationship marketing. This relatively new approach offers libraries new ways for successful and long-term management of alliances between partners.

Distance Determination Method for Normally Distributed Obstacle Avoidance of Mobile Robots in Stochastic Environments

Directory of Open Access Journals (Sweden)

Jinhong Noh

2016-04-01

Full Text Available Obstacle avoidance methods require knowledge of the distance between a mobile robot and obstacles in the environment. However, in stochastic environments, distance determination is difficult because objects have position uncertainty. The purpose of this paper is to determine the distance between a robot and obstacles represented by probability distributions. Distance determination for obstacle avoidance should consider position uncertainty, computational cost and collision probability. The proposed method considers all of these conditions, unlike conventional methods. It determines the obstacle region using the collision probability density threshold. Furthermore, it defines a minimum distance function to the boundary of the obstacle region with a Lagrange multiplier method. Finally, it computes the distance numerically. Simulations were executed in order to compare the performance of the distance determination methods. Our method demonstrated a faster and more accurate performance than conventional methods. It may help overcome position uncertainty issues pertaining to obstacle avoidance, such as low accuracy sensors, environments with poor visibility or unpredictable obstacle motion.

Assessing associations between socio-economic environment and self-reported health in Amsterdam using bespoke environments.

Directory of Open Access Journals (Sweden)

Eleonore M Veldhuizen

Full Text Available The study of the relationship between residential environment and health at micro area level has a long time been hampered by a lack of micro-scale data. Nowadays data is registered at a much more detailed scale. In combination with Geographic Information System (GIS-techniques this creates opportunities to look at the relationship at different scales, including very local ones. The study illustrates the use of a 'bespoke environment' approach to assess the relationship between health and socio-economic environment.We created these environments by buffer-operations and used micro-scale data on 6-digit postcode level to describe these individually tailored areas around survey respondents in an accurate way. To capture the full extent of area effects we maximized variation in socio-economic characteristics between areas. The area effect was assessed using logistic regression analysis.Although the contribution of the socio-economic environment in the explanation of health was not strong it tended to be stronger at a very local level. A positive association was observed only when these factors were measured in buffers smaller than 200 meters. Stronger associations were observed when restricting the analysis to socioeconomically homogeneous buffers. Scale effects proved to be highly important but potential boundary effects seemed not to play an important role. Administrative areas and buffers of comparable sizes came up with comparable area effects.This study shows that socio-economic area effects reveal only on a very micro-scale. It underlines the importance of the availability of micro-scale data. Through scaling, bespoke environments add a new dimension to study environment and health.

Economic analysis of energy system considering the uncertainties of crude oil, natural gas and nuclear utilization employing stochastic dynamic programming

International Nuclear Information System (INIS)

Hasegawa, Keita; Komiyama, Ryoichi; Fujii, Yasumasa

2016-01-01

The paper presents an economic rationality analysis of power generation mix by stochastic dynamic programming considering fuel price uncertainties and supply disruption risks such as import disruption and nuclear power plant shutdown risk. The situation revolving around Japan's energy security adopted the past statistics, it cannot be applied to a quantitative analysis of future uncertainties. Further objective and quantitative evaluation methods are required in order to analyze Japan's energy system and make it more resilient in sight of long time scale. In this paper, the authors firstly develop the cost minimization model considering oil and natural gas price respectively by stochastic dynamic programming. Then, the authors show several premises of model and an example of result with related to crude oil stockpile, liquefied natural gas stockpile and nuclear power plant capacity. (author)

The use of economic forecasts in Danish economic policy, with special emphasis on energy and the environment

International Nuclear Information System (INIS)

Nielsen, Lise

1998-01-01

This article discusses the use of economic forecasts in Danish economic policy, with special emphasis on energy and the environment. Two different approaches have been used to forecast energy consumption and its effects on environment in Denmark and other countries. These are the macro economic and the technical approaches. The technical approach is based on technical expertise related to energy production and energy consumption, and the article asks whether the forecasts produced by this approach are superior to macro economic forecasts of energy consumption. This question is interesting because the implications for policy resulting from the two approaches seem to be different. The analysis may have relevance to other areas outside the main economic field. (au) 22 refs

Extinction of mammalian populations in conservation units of the Brazilian Cerrado by inbreeding depression in stochastic environments

OpenAIRE

Silva, Marcel Müller Fernandes Pereira da; Diniz-Filho, José Alexandre Felizola

2008-01-01

Despite methodological and theoretical advances in conservation genetics, data on genetic variation on broad regional spatial scales are still scarce, leading conservation planners to use general heuristic or simulation models for an integrated analysis of genetic, demographic and landscape parameters. Here, we extended previous results by evaluating spatial patterns of extinction by inbreeding depression under stochastic variation of environments for mammalian populations in 31 conservation ...

Characterizing economic trends by Bayesian stochastic model specification search

DEFF Research Database (Denmark)

Grassi, Stefano; Proietti, Tommaso

We extend a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. In particular, we focus on autoregressive models with possibly time-varying intercept and slope and decide on ...

A hybrid stochastic approach for self-location of wireless sensors in indoor environments.

Science.gov (United States)

Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro

2009-01-01

Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

New insights into the stochastic ray production frontier

Czech Academy of Sciences Publication Activity Database

Henningsen, A.; Bělín, Matěj; Henningsen, G.

2017-01-01

Roč. 156, July (2017), s. 18-21 ISSN 0165-1765 R&D Projects: GA MŠk(CZ) SVV260475 Institutional support: Progres-Q24 Keywords : stochastic ray production frontier * distance function * multiple outputs Subject RIV: AH - Economics OBOR OECD: Economic Theory Impact factor: 0.558, year: 2016

Robustness of Populations in Stochastic Environments

DEFF Research Database (Denmark)

Gießen, Christian; Kötzing, Timo

2014-01-01

these results to LeadingOnes and to many different noise models, showing how the application of drift theory can significantly simplify and generalize previous analyses. Most surprisingly, even small populations (of size _(log n)) can make evolutionary algorithms perform well for high noise levels, well outside......We consider stochastic versions of OneMax and Leading-Ones and analyze the performance of evolutionary algorithms with and without populations on these problems. It is known that the (1+1) EA on OneMax performs well in the presence of very small noise, but poorly for higher noise levels. We extend...

Alternative Approaches to Technical Efficiency Estimation in the Stochastic Frontier Model

OpenAIRE

Acquah, H. de-Graft; Onumah, E. E.

2014-01-01

Estimating the stochastic frontier model and calculating technical efficiency of decision making units are of great importance in applied production economic works. This paper estimates technical efficiency from the stochastic frontier model using Jondrow, and Battese and Coelli approaches. In order to compare alternative methods, simulated data with sample sizes of 60 and 200 are generated from stochastic frontier model commonly applied to agricultural firms. Simulated data is employed to co...

Adaptive behavior in economic and social environments

NARCIS (Netherlands)

Droste, E.J.R.

1999-01-01

Various economic and social environments feature repeated interaction of decision-makers. Firms compete for market shares continually, politicians enter into debates almost every day, and friends communicate regularly. When decision-makers accumulate experience and collect new information each time

Techno-economic simulation data based deterministic and stochastic for product engineering research and development BATAN

International Nuclear Information System (INIS)

Petrus Zacharias; Abdul Jami

2010-01-01

Researches conducted by Batan's researchers have resulted in a number competences that can be used to produce goods and services, which will be applied to industrial sector. However, there are difficulties how to convey and utilize the R and D products into industrial sector. Evaluation results show that each research result should be completed with techno-economy analysis to obtain the feasibility of a product for industry. Further analysis on multy-product concept, in which one business can produce many main products, will be done. For this purpose, a software package simulating techno-economy I economic feasibility which uses deterministic and stochastic data (Monte Carlo method) was been carried out for multi-product including side product. The programming language used in Visual Basic Studio Net 2003 and SQL as data base processing software. This software applied sensitivity test to identify which investment criteria is sensitive for the prospective businesses. Performance test (trial test) has been conducted and the results are in line with the design requirement, such as investment feasibility and sensitivity displayed deterministically and stochastically. These result can be interpreted very well to support business decision. Validation has been performed using Microsoft Excel (for single product). The result of the trial test and validation show that this package is suitable for demands and is ready for use. (author)

Managing flowback and produced water from hydraulic fracturing under stochastic environment

Science.gov (United States)

Zhang, X.; Sun, A. Y.; Duncan, I. J.; Vesselinov, V. V.

2017-12-01

A large volume of wastewater is being generated from hydraulic fracturing in shale gas plays, including flowback and produced water. The produced wastewater in terms of its quantity and quality has become one of the main environmental problems facing shale gas industries worldwide. Cost-effective planning and management of flowback and produced water is highly desirable. Careful choice of treatment, disposal, and reuse options can lower costs and reduce potential environmental impacts. To handle the recourse issue in decision-making, a two-stage stochastic management model is developed to provide optimal alternatives for fracturing wastewater management. The proposed model is capable of prompting corrective actions to allow decision makers to adjust the pre-defined management strategies. By using this two-stage model, potential penalties arising from decision infeasibility can be minimized. The applicability of the proposed model is demonstrated using a representative synthetic example, in which tradeoffs between economic and environmental goals are quantified. This approach can generate informed defensible decisions for shale gas wastewater management. In addition, probabilistic and non-probabilistic uncertainties are effectively addressed.

Using ecosystem services to represent the environment in hydro-economic models

Science.gov (United States)

Momblanch, Andrea; Connor, Jeffery D.; Crossman, Neville D.; Paredes-Arquiola, Javier; Andreu, Joaquín

2016-07-01

Demand for water is expected to grow in line with global human population growth, but opportunities to augment supply are limited in many places due to resource limits and expected impacts of climate change. Hydro-economic models are often used to evaluate water resources management options, commonly with a goal of understanding how to maximise water use value and reduce conflicts among competing uses. The environment is now an important factor in decision making, which has resulted in its inclusion in hydro-economic models. We reviewed 95 studies applying hydro-economic models, and documented how the environment is represented in them and the methods they use to value environmental costs and benefits. We also sought out key gaps and inconsistencies in the treatment of the environment in hydro-economic models. We found that representation of environmental values of water is patchy in most applications, and there should be systematic consideration of the scope of environmental values to include and how they should be valued. We argue that the ecosystem services framework offers a systematic approach to identify the full range of environmental costs and benefits. The main challenges to more holistic representation of the environment in hydro-economic models are the current limits to understanding of ecological functions which relate physical, ecological and economic values and critical environmental thresholds; and the treatment of uncertainty.

Some Remarks on Stochastic Versions of the Ramsey Growth Model

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

2012-01-01

Roč. 19, č. 29 (2012), s. 139-152 ISSN 1212-074X R&D Projects: GA ČR GAP402/10/1610; GA ČR GAP402/10/0956; GA ČR GAP402/11/0150 Institutional support: RVO:67985556 Keywords : Economic dynamics * Ramsey growth model with disturbance * stochastic dynamic programming * multistage stochastic programs Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/E/sladky-some remarks on stochastic versions of the ramsey growth model.pdf

Stochastic modelling of the economic viability of on-farm co-digestion of pig manure and food waste in Ireland

International Nuclear Information System (INIS)

Dennehy, C.; Lawlor, P.G.; Gardiner, G.E.; Jiang, Y.; Shalloo, L.; Zhan, X.

2017-01-01

Highlights: •Assessed economic viability of on-farm manure mono- and co-digestion. •Assessed three farm sizes: 521 sows; 2607 sows; and 5214 sows. •Mono-digestion of manure alone not economically viable. •Co-digestion viable on small farms as food waste likely to be sourced. •Viability on larger farms dependent on securing sufficient food waste. -- Abstract: The majority of studies analysing the economic potential of biogas systems utilise deterministic models to assess the viability of a system using fixed inputs. However, changes in market conditions can significantly affect the viability of biogas plants, and need to be accounted for. This study assessed the economic potential of undertaking on-farm anaerobic co-digestion of food waste (FW) and pig manure (PM) using both deterministic and stochastic modelling approaches. The financial viability of three co-digestion plants sized to treat PM generated from 521, 2607 and 5214 sow integrated units was assessed. Under current market conditions the largest co-digestion scenario modelled was found to be unviable. Stochastic modelling of four key input variables (FW availability, renewable electricity tariff, gate fees and digestate disposal costs) was undertaken to assess the sensitivity of project viability to changes in market conditions. Due to the high likelihood of accessing sufficient FW, the smallest co-digestion scenario was found to be the least sensitive to any future changes in market conditions. Due to its potential to treat greater amounts of FW than the smallest scenario, a co-digestion plant designed for a 2607 sow farm had the highest revenue generating potential under optimal market conditions; however, it was more sensitive to changes in FW availability than the smaller scenario. This study illustrates the need for farm-based biogas plant projects to secure long-term, stable supplies of co-substrates and to size plants’ capacity based on the availability of the co-substrates which drive

Simulation of the energy - environment economic system power generation costs in power-stations

International Nuclear Information System (INIS)

Weible, H.

1978-09-01

The costs of power generation are an important point in the electricity industry. The present report tries to supply a model representation for these problems. The costs of power generation for base load, average and peak load power stations are examined on the basis of fossil energy sources, nuclear power and water power. The methods of calculation where dynamic investment calculation processes are used, are given in the shape of formulae. From the point of view of long term prediction, power generation cost sensitivity studies are added to the technical, economic and energy-political uncertainties. The sensitivity of models for calculations is examined by deterministic and stochastic processes. In the base load and average region, power generation based on nuclear power and water power is economically more favourable than that from fossilfired power stations. Even including subsidies, this cost advantage is not in doubt. In the peak load region, pumped storage power stations are more economic than fossilfired power stations. (orig.) [de

A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

Directory of Open Access Journals (Sweden)

Alejandro Canovas

2009-05-01

Full Text Available Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

A Backward-Lagrangian-Stochastic Footprint Model for the Urban Environment

Science.gov (United States)

Wang, Chenghao; Wang, Zhi-Hua; Yang, Jiachuan; Li, Qi

2018-02-01

Built terrains, with their complexity in morphology, high heterogeneity, and anthropogenic impact, impose substantial challenges in Earth-system modelling. In particular, estimation of the source areas and footprints of atmospheric measurements in cities requires realistic representation of the landscape characteristics and flow physics in urban areas, but has hitherto been heavily reliant on large-eddy simulations. In this study, we developed physical parametrization schemes for estimating urban footprints based on the backward-Lagrangian-stochastic algorithm, with the built environment represented by street canyons. The vertical profile of mean streamwise velocity is parametrized for the urban canopy and boundary layer. Flux footprints estimated by the proposed model show reasonable agreement with analytical predictions over flat surfaces without roughness elements, and with experimental observations over sparse plant canopies. Furthermore, comparisons of canyon flow and turbulence profiles and the subsequent footprints were made between the proposed model and large-eddy simulation data. The results suggest that the parametrized canyon wind and turbulence statistics, based on the simple similarity theory used, need to be further improved to yield more realistic urban footprint modelling.

How is an analysis of the enterprise economic environment done?

Directory of Open Access Journals (Sweden)

Carlos Parodi Trece

2015-09-01

Full Text Available The proper interpretation of the evolution of the economy is a useful tool to improve corporate decision-making. The aim of this paper is to explain, with examples applied to the current economic reality, how an analysis of the economic environment is made and how it serves for the corporate strategic planning. To do this, after the explanation of the overall conceptual framework; gross domestic product, inflation and external deficit as indicators, key in the "language" used by analysts are defined. These are economic indicators, related, that depend on domestic policy and exogenous shocks, defined as events that are out of the hands of economic policy designers, but that influence the three variables, such as the international financial crisis. Following it, the formalization through macroeconomic identities is made, in order to finally explain "how is the economy" through them; and the relationship between the internal to the external economic environment. Bringing the economy to business should be a priority in an increasingly integrated context, characterized by the fact that the positive and the negative of what happens in the world economy is transmitted through various channels, to companies located in different countries. Hence, companies should broaden their vision, as the economic environment does not only include what happens within the country, but the future of the world economy.

New economic initiatives are designed to protect the environment

International Nuclear Information System (INIS)

Fleet, B.; Fleet, N.S.

1992-01-01

The use of economic initiatives or economic instruments as an alternative to or as support for existing environmental legislation is reviewed. The most controversial area of economic incentives is the concept of creating a market in pollution rights. While emissions trading can enable economic growth in areas of high pollution, this approach is only marginally different than the traditional regulatory approach. Environmental economics is complex, with mixtures of private and public costs. Social costs include subsidies, waste treatment, landfill disposal costs, etc. More intangible social costs include public health costs and damage to the natural environment. Conventional economic approaches ignore most such social costs. Several European countries have started to develop a green gross national product (GNP) which sets out an alternative approach to the traditional measure of economic activity by subtracting a figure for harm to the environment from economic activity. This ambitious approach attempts to measure the costs of all toxic discharges along with the disappearance of plant and animal life and other environmental changes. A powerful new tool for the environmental manager is full cost accounting, which uses a long (10-20 y) window for projects, anticipates the impact of stricter discharge standards, and attempts to quantify a range of less tangible social costs elements, such as liability, improved environmental image, etc. Various strategies can be ranked on the basis of their future risk cost. The application of full cost accounting models, small business, computer models and expert systems, developing country debt-for-nature swaps, and environmental risk assessment are discussed. 12 refs

Informal sector, business environment and economic growth: A ...

International Development Research Centre (IDRC) Digital Library (Canada)

2012-12-01

Informal sector, business environment and economic growth: A comparative analysis of West and Central Africa ... taxes, which undermines fair competition and puts formal enterprises at a disadvantage. ... Start Date. December 1, 2012 ...

International Conference Modern Stochastics: Theory and Applications III

CERN Document Server

Limnios, Nikolaos; Mishura, Yuliya; Sakhno, Lyudmyla; Shevchenko, Georgiy; Modern Stochastics and Applications

2014-01-01

This volume presents an extensive overview of all major modern trends in applications of probability and stochastic analysis. It will be a  great source of inspiration for designing new algorithms, modeling procedures, and experiments. Accessible to researchers, practitioners, as well as graduate and postgraduate students, this volume presents a variety of new tools, ideas, and methodologies in the fields of optimization, physics, finance, probability, hydrodynamics, reliability, decision making, mathematical finance, mathematical physics, and economics. Contributions to this Work include those of selected speakers from the international conference entitled “Modern Stochastics: Theory and Applications III,”  held on September 10 –14, 2012 at Taras Shevchenko National University of Kyiv, Ukraine. The conference covered the following areas of research in probability theory and its applications: stochastic analysis, stochastic processes and fields, random matrices, optimization methods in probability, st...

A stochastic SIS epidemic model with vaccination

Science.gov (United States)

Cao, Boqiang; Shan, Meijing; Zhang, Qimin; Wang, Weiming

2017-11-01

In this paper, we investigate the basic features of an SIS type infectious disease model with varying population size and vaccinations in presence of environment noise. By applying the Markov semigroup theory, we propose a stochastic reproduction number R0s which can be seen as a threshold parameter to utilize in identifying the stochastic extinction and persistence: If R0s disease-free absorbing set for the stochastic epidemic model, which implies that disease dies out with probability one; while if R0s > 1, under some mild extra conditions, the SDE model has an endemic stationary distribution which results in the stochastic persistence of the infectious disease. The most interesting finding is that large environmental noise can suppress the outbreak of the disease.

Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty.

Science.gov (United States)

Zhang, Huifeng; Lei, Xiaohui; Wang, Chao; Yue, Dong; Xie, Xiangpeng

2017-01-01

Since wind power is integrated into the thermal power operation system, dynamic economic emission dispatch (DEED) has become a new challenge due to its uncertain characteristics. This paper proposes an adaptive grid based multi-objective Cauchy differential evolution (AGB-MOCDE) for solving stochastic DEED with wind power uncertainty. To properly deal with wind power uncertainty, some scenarios are generated to simulate those possible situations by dividing the uncertainty domain into different intervals, the probability of each interval can be calculated using the cumulative distribution function, and a stochastic DEED model can be formulated under different scenarios. For enhancing the optimization efficiency, Cauchy mutation operation is utilized to improve differential evolution by adjusting the population diversity during the population evolution process, and an adaptive grid is constructed for retaining diversity distribution of Pareto front. With consideration of large number of generated scenarios, the reduction mechanism is carried out to decrease the scenarios number with covariance relationships, which can greatly decrease the computational complexity. Moreover, the constraint-handling technique is also utilized to deal with the system load balance while considering transmission loss among thermal units and wind farms, all the constraint limits can be satisfied under the permitted accuracy. After the proposed method is simulated on three test systems, the obtained results reveal that in comparison with other alternatives, the proposed AGB-MOCDE can optimize the DEED problem while handling all constraint limits, and the optimal scheme of stochastic DEED can decrease the conservation of interval optimization, which can provide a more valuable optimal scheme for real-world applications.

Optimal control of stochastic difference Volterra equations an introduction

CERN Document Server

Shaikhet, Leonid

2015-01-01

This book showcases a subclass of hereditary systems, that is, systems with behaviour depending not only on their current state but also on their past history; it is an introduction to the mathematical theory of optimal control for stochastic difference Volterra equations of neutral type. As such, it will be of much interest to researchers interested in modelling processes in physics, mechanics, automatic regulation, economics and finance, biology, sociology and medicine for all of which such equations are very popular tools. The text deals with problems of optimal control such as meeting given performance criteria, and stabilization, extending them to neutral stochastic difference Volterra equations. In particular, it contrasts the difference analogues of solutions to optimal control and optimal estimation problems for stochastic integral Volterra equations with optimal solutions for corresponding problems in stochastic difference Volterra equations. Optimal Control of Stochastic Difference Volterra Equation...

Factors influencing lysis time stochasticity in bacteriophage λ

Directory of Open Access Journals (Sweden)

Dennehy John J

2011-08-01

Full Text Available Abstract Background Despite identical genotypes and seemingly uniform environments, stochastic gene expression and other dynamic intracellular processes can produce considerable phenotypic diversity within clonal microbes. One trait that provides a good model to explore the molecular basis of stochastic variation is the timing of host lysis by bacteriophage (phage. Results Individual lysis events of thermally-inducible λ lysogens were observed using a temperature-controlled perfusion chamber mounted on an inverted microscope. Both mean lysis time (MLT and its associated standard deviation (SD were estimated. Using the SD as a measure of lysis time stochasticity, we showed that lysogenic cells in controlled environments varied widely in lysis times, and that the level of lysis time stochasticity depended on allelic variation in the holin sequence, late promoter (pR' activity, and host growth rate. In general, the MLT was positively correlated with the SD. Both lower pR' activities and lower host growth rates resulted in larger SDs. Results from premature lysis, induced by adding KCN at different time points after lysogen induction, showed a negative correlation between the timing of KCN addition and lysis time stochasticity. Conclusions Taken together with results published by others, we conclude that a large fraction of λ lysis time stochasticity is the result of random events following the expression and diffusion of the holin protein. Consequently, factors influencing the timing of reaching critical holin concentrations in the cell membrane, such as holin production rate, strongly influence the mean lysis time and the lysis time stochasticity.

Dynamic stochastic optimization

CERN Document Server

Ermoliev, Yuri; Pflug, Georg

2004-01-01

Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic­ itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec­ tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci­ sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu­ tions. Objective an...

MEASURING INFLATION THROUGH STOCHASTIC APPROACH TO INDEX NUMBERS FOR PAKISTAN

Directory of Open Access Journals (Sweden)

Zahid Asghar

2010-09-01

Full Text Available This study attempts to estimate the rate of inflation in Pakistan through stochastic approach to index numbers which provides not only point estimate but also confidence interval for the rate of inflation. There are two types of approaches to index number theory namely: the functional economic approaches and the stochastic approach. The attraction of stochastic approach is that it estimates the rate of inflation in which uncertainty and statistical ideas play a major roll of screening index numbers. We have used extended stochastic approach to index numbers for measuring inflation by allowing for the systematic changes in the relative prices. We use CPI data covering the period July 2001--March 2008 for Pakistan.

Learning stochastic reward distributions in a speeded pointing task.

Science.gov (United States)

Seydell, Anna; McCann, Brian C; Trommershäuser, Julia; Knill, David C

2008-04-23

Recent studies have shown that humans effectively take into account task variance caused by intrinsic motor noise when planning fast hand movements. However, previous evidence suggests that humans have greater difficulty accounting for arbitrary forms of stochasticity in their environment, both in economic decision making and sensorimotor tasks. We hypothesized that humans can learn to optimize movement strategies when environmental randomness can be experienced and thus implicitly learned over several trials, especially if it mimics the kinds of randomness for which subjects might have generative models. We tested the hypothesis using a task in which subjects had to rapidly point at a target region partly covered by three stochastic penalty regions introduced as "defenders." At movement completion, each defender jumped to a new position drawn randomly from fixed probability distributions. Subjects earned points when they hit the target, unblocked by a defender, and lost points otherwise. Results indicate that after approximately 600 trials, subjects approached optimal behavior. We further tested whether subjects simply learned a set of stimulus-contingent motor plans or the statistics of defenders' movements by training subjects with one penalty distribution and then testing them on a new penalty distribution. Subjects immediately changed their strategy to achieve the same average reward as subjects who had trained with the second penalty distribution. These results indicate that subjects learned the parameters of the defenders' jump distributions and used this knowledge to optimally plan their hand movements under conditions involving stochastic rewards and penalties.

Environment, energy, and economic performance

Energy Technology Data Exchange (ETDEWEB)

Oberndorfer, Ulrich

2009-09-25

This thesis analyzes the relationship between environmental regulation as well as energy market developments on the one hand, and economic performance on the other. Due to its economic effects environmental regulation is controversially disputed. The thesis shows, however, that the economic impacts of the recently adopted climate policy in Europe, namely of the implementation of the European Union Emission Trading Scheme, have been modest at most. Consistent with economic theory, the low stringency of this regulatory measure that is aimed at combating man-made climate change is identified as one important driver of this result. Moreover, results presented in this thesis also indicate the important role which the political economy plays for the design of environmental regulation in general. These mechanisms are shown to be a driver of the low stringency and, consequently, of the small economic effects during the first phase of the European Union Emission Trading Scheme. The thesis highlights the role of investment stimulation if the goal of environmental regulation is not only the protection of the environment, but also the compatibility with economic goals. This thesis also provides new insights into the role of energy market developments for the economy. In this respect, the relevance of the EU carbon market for the financial market performance of European electricity generators is shown. Besides, this thesis particularly demonstrates the paramount importance of oil market developments for the economy as a whole. It suggests that amongst all natural resources, oil is the most relevant one to the pricing of Eurozone energy stocks. It is also shown that besides oil prices, oil volatility plays an important role for stock market development. Finally, the thesis highlights the relevance of oil market developments to the overall economy, in showing that unemployment in Germany is strongly affected by oil price shocks. In this respect, it also opposes claims that the

Proximity, social capital and the Simon-model of stochastic growth

NARCIS (Netherlands)

Frenken, K.; Reggiani, A.; Nijkamp, P.

2009-01-01

It is customary to define economic geography as a discipline that deals with the uneven distribution of economic activity across space. From a historical perspective, stochastic growth models are of particular use (Simon 1955). Such models explain the current distribution of activities from the

The Family Economic Environment as a Context for Children's Development.

Science.gov (United States)

Farran, Dale Clark; Margolis, Lewis H.

1987-01-01

Longitudinally examines how the complexities of the family economic environment may affect children's health, behavior, and ideas about the world of work. Family economic factors considered include father's/mother's work status (especially parental unemployment); per-capita income; health insurance; father's job security; and satisfaction with…

Stochastic Fatigue Analysis of Jacket Type Offshore Structures

DEFF Research Database (Denmark)

Sigurdsson, Gudfinnur

In this paper, a stochastic reliability assessment for jacket type offshore structures subjected to wave loads in deep water environments is outlined. In the reliability assessment, structural and loading uncertainties are taken into account by means of some stochastic variables. To estimate stat...... statistical measures of structural stress variations the modal spectral analysis method is applied....

Mathematical modeling in economics, ecology and the environment

CERN Document Server

Hritonenko, Natali

2013-01-01

Updated to textbook form by popular demand, this second edition discusses diverse mathematical models used in economics, ecology, and the environmental sciences with emphasis on control and optimization. It is intended for graduate and upper-undergraduate course use, however, applied mathematicians, industry practitioners, and a vast number of interdisciplinary academics will find the presentation highly useful. Core topics of this text are: ·         Economic growth and technological development ·         Population dynamics and human impact on the environment ·         Resource extraction and scarcity ·         Air and water contamination ·         Rational management of the economy and environment ·         Climate change and global dynamics The step-by-step approach taken is problem-based and easy to follow. The authors aptly demonstrate that the same models may be used to describe different economic and environmental processes and that similar invest...

Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage

Science.gov (United States)

Guo, Wenjuan; Cai, Yongli; Zhang, Qimin; Wang, Weiming

2018-02-01

This paper aims to study an SIS epidemic model with media coverage from a general deterministic model to a stochastic differential equation with environment fluctuation. Mathematically, we use the Markov semigroup theory to prove that the basic reproduction number R0s can be used to control the dynamics of stochastic system. Epidemiologically, we show that environment fluctuation can inhibit the occurrence of the disease, namely, in the case of disease persistence for the deterministic model, the disease still dies out with probability one for the stochastic model. So to a great extent the stochastic perturbation under media coverage affects the outbreak of the disease.

Permutation Tests for Stochastic Ordering and ANOVA

CERN Document Server

Basso, Dario; Salmaso, Luigi; Solari, Aldo

2009-01-01

Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents advanced methods and related R codes to perform complex multivariate analyses

International Conference on Modern Problems of Stochastic Analysis and Statistics

CERN Document Server

2017-01-01

This book brings together the latest findings in the area of stochastic analysis and statistics. The individual chapters cover a wide range of topics from limit theorems, Markov processes, nonparametric methods, acturial science, population dynamics, and many others. The volume is dedicated to Valentin Konakov, head of the International Laboratory of Stochastic Analysis and its Applications on the occasion of his 70th birthday. Contributions were prepared by the participants of the international conference of the international conference “Modern problems of stochastic analysis and statistics”, held at the Higher School of Economics in Moscow from May 29 - June 2, 2016. It offers a valuable reference resource for researchers and graduate students interested in modern stochastics.

An inexact multistage fuzzy-stochastic programming for regional electric power system management constrained by environmental quality.

Science.gov (United States)

Fu, Zhenghui; Wang, Han; Lu, Wentao; Guo, Huaicheng; Li, Wei

2017-12-01

Electric power system involves different fields and disciplines which addressed the economic system, energy system, and environment system. Inner uncertainty of this compound system would be an inevitable problem. Therefore, an inexact multistage fuzzy-stochastic programming (IMFSP) was developed for regional electric power system management constrained by environmental quality. A model which concluded interval-parameter programming, multistage stochastic programming, and fuzzy probability distribution was built to reflect the uncertain information and dynamic variation in the case study, and the scenarios under different credibility degrees were considered. For all scenarios under consideration, corrective actions were allowed to be taken dynamically in accordance with the pre-regulated policies and the uncertainties in reality. The results suggest that the methodology is applicable to handle the uncertainty of regional electric power management systems and help the decision makers to establish an effective development plan.

Stochasticity and determinism in models of hematopoiesis.

Science.gov (United States)

Kimmel, Marek

2014-01-01

This chapter represents a novel view of modeling in hematopoiesis, synthesizing both deterministic and stochastic approaches. Whereas the stochastic models work in situations where chance dominates, for example when the number of cells is small, or under random mutations, the deterministic models are more important for large-scale, normal hematopoiesis. New types of models are on the horizon. These models attempt to account for distributed environments such as hematopoietic niches and their impact on dynamics. Mixed effects of such structures and chance events are largely unknown and constitute both a challenge and promise for modeling. Our discussion is presented under the separate headings of deterministic and stochastic modeling; however, the connections between both are frequently mentioned. Four case studies are included to elucidate important examples. We also include a primer of deterministic and stochastic dynamics for the reader's use.

COSMIC DUST AGGREGATION WITH STOCHASTIC CHARGING

International Nuclear Information System (INIS)

Matthews, Lorin S.; Hyde, Truell W.; Shotorban, Babak

2013-01-01

The coagulation of cosmic dust grains is a fundamental process which takes place in astrophysical environments, such as presolar nebulae and circumstellar and protoplanetary disks. Cosmic dust grains can become charged through interaction with their plasma environment or other processes, and the resultant electrostatic force between dust grains can strongly affect their coagulation rate. Since ions and electrons are collected on the surface of the dust grain at random time intervals, the electrical charge of a dust grain experiences stochastic fluctuations. In this study, a set of stochastic differential equations is developed to model these fluctuations over the surface of an irregularly shaped aggregate. Then, employing the data produced, the influence of the charge fluctuations on the coagulation process and the physical characteristics of the aggregates formed is examined. It is shown that dust with small charges (due to the small size of the dust grains or a tenuous plasma environment) is affected most strongly

Dynamic and stochastic multi-project planning

CERN Document Server

Melchiors, Philipp

2015-01-01

This book deals with dynamic and stochastic methods for multi-project planning. Based on the idea of using queueing networks for the analysis of dynamic-stochastic multi-project environments this book addresses two problems: detailed scheduling of project activities, and integrated order acceptance and capacity planning. In an extensive simulation study, the book thoroughly investigates existing scheduling policies. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision processes and Approximate Dynamic programming.

Stochastic thermodynamics

Science.gov (United States)

Eichhorn, Ralf; Aurell, Erik

2014-04-01

'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response

Monte Carlo simulation of fully Markovian stochastic geometries

International Nuclear Information System (INIS)

Lepage, Thibaut; Delaby, Lucie; Malvagi, Fausto; Mazzolo, Alain

2010-01-01

The interest in resolving the equation of transport in stochastic media has continued to increase these last years. For binary stochastic media it is often assumed that the geometry is Markovian, which is never the case in usual environments. In the present paper, based on rigorous mathematical theorems, we construct fully two-dimensional Markovian stochastic geometries and we study their main properties. In particular, we determine a percolation threshold p c , equal to 0.586 ± 0.0015 for such geometries. Finally, Monte Carlo simulations are performed through these geometries and the results compared to homogeneous geometries. (author)

The Influence of Changes in the Market Environment on Economic Production Characteristics of Pangasius Farming in the Mekong Delta (Vietnam)

NARCIS (Netherlands)

Binh, Van T.; Haese, D' M.F.C.; Speelman, S.; Haese, D' L.

2010-01-01

The Mekong Delta in Vietnam has become an important production area for pangasius. The importance of the sector in providing an income to many households means that it is relevant to study its economic production characteristics. In this article we use a stochastic cost frontier model to assess the

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies

NARCIS (Netherlands)

Osiewalski, J.; Koop, G.; Steel, M.F.J.

1997-01-01

This paper uses Bayesian stochastic frontier methods to measure the productivity gap between Poland and Western countries that existed before the beginning of the main Polish economic reform. Using data for 20 Western economies, Poland and Yugoslavia (1980-1990) we estimate a translog stochastic

Some recent developments in stochastic volatility modelling

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Nicolato, Elisa; Shephard, N.

2002-01-01

This paper reviews and puts in context some of our recent work on stochastic volatility (SV) modelling for financial economics. Here our main focus is on: (i) the relationship between subordination and SV, (ii) OU based volatility models, (iii) exact option pricing, (iv) realized power variation...

Optimization of environmental management strategies through a dynamic stochastic possibilistic multiobjective program

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaodong, E-mail: xiaodong.zhang@beg.utexas.edu [Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78713 (United States); Huang, Gordon [Institute of Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)

2013-02-15

Highlights: ► A dynamic stochastic possibilistic multiobjective programming model is developed. ► Greenhouse gas emission control is considered. ► Three planning scenarios are analyzed and compared. ► Optimal decision schemes under three scenarios and different p{sub i} levels are obtained. ► Tradeoffs between economics and environment are reflected. -- Abstract: Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p{sub i} levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help

Facilitated diffusion in a crowded environment: from kinetics to stochastics

International Nuclear Information System (INIS)

Meroz, Yasmine; Klafter, Joseph; Eliazar, Iddo

2009-01-01

Facilitated diffusion is a fundamental search process used to describe the problem of a searcher protein finding a specific target site over a very large DNA strand. In recent years macromolecular crowding has been recognized to affect this search process. In this paper, we bridge between two different modelling methodologies of facilitated diffusion: the physics-oriented kinetic approach, which yields the reaction rate of the search process, and the probability-oriented stochastic approach, which yields the probability distribution of the search duration. We translate the former approach to the latter, ascertaining that the two approaches yield coinciding results, both with and without macromolecular crowding. We further show that the stochastic approach markedly generalizes the kinetic approach by accommodating a vast array of search mechanisms, including mechanisms having no reaction rates, and thus being beyond the realm of the kinetic approach.

Stochastic bio-economic modeling of mastitis in Ethiopian dairy farms.

Science.gov (United States)

Getaneh, Abraham Mekibeb; Mekonnen, Sefinew Alemu; Hogeveen, Henk

2017-03-01

Mastitis is an inflammation of the mammary gland that is considered to be one of the most frequent and costly diseases in the dairy industry. Also in Ethiopia, bovine mastitis is one of the most frequently encountered diseases of dairy cows. However, there was no study, so far, regarding the costs of clinical mastitis and only two studies were reported on costs of subclinical mastitis. Presenting an appropriate and complete study of the costs of mastitis will help farmers in making management decisions for mastitis control. The objective of this study was to estimate the economic effects of mastitis on Ethiopian market-oriented dairy farms. Market-oriented dairy farming is driven by making profits through selling milk in the market on a regular basis. A dynamic stochastic Monte-Carlo simulation model (bio-economic model) was developed taking into account both clinical and subclinical mastitis. Production losses, culling, veterinarian costs, treatment, discarded milk, and labour were the main cost factors which were modeled in this study. The annual incidence of clinical mastitis varied from 0 to 50% with a mean annual incidence of 21.6%, whereas the mean annual incidence of subclinical mastitis was 36.2% which varied between 0 and 75%. The total costs due to mastitis for a default farm size of 8 lactating cows were 6,709 ETB per year (838 ETB per cow per year). The costs varied considerably, with 5th and 95th percentiles of 109 ETB and 22,009 ETB, respectively. The factor most contributing to the total annual cost of mastitis was culling. On average a clinical case costs 3,631 ETB, varying from 0 to 12,401, whereas a sub clinical case costs 147 ETB, varying from 0 to 412. The sensitivity analysis showed that the total costs at the farm level were most sensitive for variation in the probability of occurrence of clinical mastitis and the probability of culling. This study helps farmers to raise awareness about the actual costs of mastitis and motivate them to timely

Stochastic modelling to assess economic effects of treatment of chronic subclinical mastitis caused by Streptococcus uberis.

Science.gov (United States)

Steeneveld, Wilma; Swinkels, Jantijn; Hogeveen, Henk

2007-11-01

Chronic subclinical mastitis is usually not treated during the lactation. However, some veterinarians regard treatment of some types of subclinical mastitis to be effective. The goal of this research was to develop a stochastic Monte Carlo simulation model to support decisions around treatment of chronic subclinical mastitis caused by Streptococcus uberis. Factors in the model included the probability of cure after treatment, probability of the cow becoming clinically diseased, transmission of infection to other cows, and physiological effects of the infection. Using basic input parameters for Dutch circumstances, the average economic costs per cow of an untreated chronic subclinical mastitis case caused by Str. uberis in a single quarter from day of diagnosis onwards was euro109. With treatment, the average costs were higher (euro120). Thus, for the average cow, treatment was not efficient economically. However, the risk of high costs was much higher when cows with chronic subclinical mastitis were not treated. A sensitivity analysis showed that profitability of treatment of chronic subclinical Str. uberis mastitis depended on farm-specific factors (such as economic value of discarded milk) and cow-specific factors (such as day of diagnosis, duration of infection, amount of transmission to other cows and cure rate). Therefore, herd level protocols are not sufficient and decision support should be cow specific. Given the importance of cow-specific factors, information from the current model could be applied to automatic decision support systems.

The effect of stochasticity on the lac operon: an evolutionary perspective.

Directory of Open Access Journals (Sweden)

Milan van Hoek

2007-06-01

Full Text Available The role of stochasticity on gene expression is widely discussed. Both potential advantages and disadvantages have been revealed. In some systems, noise in gene expression has been quantified, in among others the lac operon of Escherichia coli. Whether stochastic gene expression in this system is detrimental or beneficial for the cells is, however, still unclear. We are interested in the effects of stochasticity from an evolutionary point of view. We study this question in the lac operon, taking a computational approach: using a detailed, quantitative, spatial model, we evolve through a mutation-selection process the shape of the promoter function and therewith the effective amount of stochasticity. We find that noise values for lactose, the natural inducer, are much lower than for artificial, nonmetabolizable inducers, because these artificial inducers experience a stronger positive feedback. In the evolved promoter functions, noise due to stochasticity in gene expression, when induced by lactose, only plays a very minor role in short-term physiological adaptation, because other sources of population heterogeneity dominate. Finally, promoter functions evolved in the stochastic model evolve to higher repressed transcription rates than those evolved in a deterministic version of the model. This causes these promoter functions to experience less stochasticity in gene expression. We show that a high repression rate and hence high stochasticity increases the delay in lactose uptake in a variable environment. We conclude that the lac operon evolved such that the impact of stochastic gene expression is minor in its natural environment, but happens to respond with much stronger stochasticity when confronted with artificial inducers. In this particular system, we have shown that stochasticity is detrimental. Moreover, we demonstrate that in silico evolution in a quantitative model, by mutating the parameters of interest, is a promising way to unravel

Stochastic Calculus and Differential Equations for Physics and Finance

Science.gov (United States)

McCauley, Joseph L.

2013-02-01

1. Random variables and probability distributions; 2. Martingales, Markov, and nonstationarity; 3. Stochastic calculus; 4. Ito processes and Fokker-Planck equations; 5. Selfsimilar Ito processes; 6. Fractional Brownian motion; 7. Kolmogorov's PDEs and Chapman-Kolmogorov; 8. Non Markov Ito processes; 9. Black-Scholes, martingales, and Feynman-Katz; 10. Stochastic calculus with martingales; 11. Statistical physics and finance, a brief history of both; 12. Introduction to new financial economics; 13. Statistical ensembles and time series analysis; 14. Econometrics; 15. Semimartingales; References; Index.

An Empirical Application of a Two-Factor Model of Stochastic Volatility

Czech Academy of Sciences Publication Activity Database

Kuchyňka, Alexandr

2008-01-01

Roč. 17, č. 3 (2008), s. 243-253 ISSN 1210-0455 R&D Projects: GA ČR GA402/07/1113; GA MŠk(CZ) LC06075 Institutional research plan: CEZ:AV0Z10750506 Keywords : stochastic volatility * Kalman filter Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2008/E/kuchynka-an empirical application of a two-factor model of stochastic volatility.pdf

Changes of the agricultural enterprises economic environment originated by the agribusiness development

Directory of Open Access Journals (Sweden)

Věra Bečvářová

2004-01-01

Full Text Available Based upon analyses of the Common Agricultural Policy development and its economic tools reforming the process of changing is characterised there. It deals with the multifunctionality of agriculture as well as the influence of the CAP on environment of the production tasks of agriculture and food processing industry accomplishment. Paper generalises results of new trends of the agribusiness economic environment development and the opportunity of an effective utilization of production factors in agriculture. It deals with the sources and economic implications of partial enhancement of interest and redirection of support within framework and type of tools of agrarian policy. New quality of structure of relevant information needs and economic support for agricultural enterprises decision making process are pointed out.

Electricity price modeling with stochastic time change

International Nuclear Information System (INIS)

Borovkova, Svetlana; Schmeck, Maren Diane

2017-01-01

In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.

Stochastic and information-thermodynamic structures of population dynamics in a fluctuating environment

Science.gov (United States)

Kobayashi, Tetsuya J.; Sughiyama, Yuki

2017-07-01

Adaptation in a fluctuating environment is a process of fueling environmental information to gain fitness. Living systems have gradually developed strategies for adaptation from random and passive diversification of the phenotype to more proactive decision making, in which environmental information is sensed and exploited more actively and effectively. Understanding the fundamental relation between fitness and information is therefore crucial to clarify the limits and universal properties of adaptation. In this work, we elucidate the underlying stochastic and information-thermodynamic structure in this process, by deriving causal fluctuation relations (FRs) of fitness and information. Combined with a duality between phenotypic and environmental dynamics, the FRs reveal the limit of fitness gain, the relation of time reversibility with the achievability of the limit, and the possibility and condition for gaining excess fitness due to environmental fluctuation. The loss of fitness due to causal constraints and the limited capacity of real organisms is shown to be the difference between time-forward and time-backward path probabilities of phenotypic and environmental dynamics. Furthermore, the FRs generalize the concept of the evolutionary stable state (ESS) for fluctuating environment by giving the probability that the optimal strategy on average can be invaded by a suboptimal one owing to rare environmental fluctuation. These results clarify the information-thermodynamic structures in adaptation and evolution.

Vehicle routing with stochastic time-dependent travel times

NARCIS (Netherlands)

Lecluyse, C.; Woensel, van T.; Peremans, H.

2009-01-01

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the

Vehicle routing with stochastic time-dependent travel times

NARCIS (Netherlands)

Lecluyse, C.; Woensel, van T.; Peremans, H.

2007-01-01

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the

A Compositional Semantics for Stochastic Reo Connectors

Directory of Open Access Journals (Sweden)

Young-Joo Moon

2010-07-01

Full Text Available In this paper we present a compositional semantics for the channel-based coordination language Reo which enables the analysis of quality of service (QoS properties of service compositions. For this purpose, we annotate Reo channels with stochastic delay rates and explicitly model data-arrival rates at the boundary of a connector, to capture its interaction with the services that comprise its environment. We propose Stochastic Reo automata as an extension of Reo automata, in order to compositionally derive a QoS-aware semantics for Reo. We further present a translation of Stochastic Reo automata to Continuous-Time Markov Chains (CTMCs. This translation enables us to use third-party CTMC verification tools to do an end-to-end performance analysis of service compositions.

Distributed EMPC of multiple microgrids for coordinated stochastic energy management

International Nuclear Information System (INIS)

Kou, Peng; Liang, Deliang; Gao, Lin

2017-01-01

Highlights: • Reducing the system wide operating cost compared to the no-cooperation energy management strategy. • Maintaining the supply and demand balance within each microgrid. • Handling the uncertainties in both supply and demand. • Converting the stochastic optimization problems to standard quadratic and linear programming problems. • Achieving a good balance between control performance and computationally feasibility. - Abstract: The concept of multi-microgrids has the potential to improve the reliability and economic performance of a distribution system. To realize this potential, a coordination among multiple microgrids is needed. In this context, this paper presents a new distributed economic model predictive control scheme for the coordinated stochastic energy management of multi-microgrids. By optimally coordinating the operation of individual microgrids, this scheme maintains the system-wide supply and demand balance in an economical manner. Based on the probabilistic forecasts of renewable power generation and microgrid load, this scheme effectively handles the uncertainties in both supply and demand. Using the Chebyshev inequality and the Delta method, the corresponding stochastic optimization problems have been converted to quadratic and linear programs. The proposed scheme is evaluated on a large-scale case that includes ten interconnected microgrids. The results indicated that the proposed scheme successfully reduces the system wide operating cost, achieves the supply-demand balance in each microgrid, and brings the energy exchange between DNO and main grid to a predefined trajectory.

Essentials of stochastic processes

CERN Document Server

Durrett, Richard

2016-01-01

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...

Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model.

Science.gov (United States)

Mostert, P F; Bokkers, E A M; van Middelaar, C E; Hogeveen, H; de Boer, I J M

2018-01-01

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of

[Evaluation of comprehensive capacity of resources and environments in Poyang Lake Eco-economic Zone].

Science.gov (United States)

Song, Yan-Chun; Yu, Dan

2014-10-01

With the development of the society and economy, the contradictions among population, resources and environment are increasingly worse. As a result, the capacity of resources and environment becomes one of the focal issues for many countries and regions. Through investigating and analyzing the present situation and the existing problems of resources and environment in Poyang Lake Eco-economic Zone, seven factors were chosen as the evaluation criterion layer, namely, land resources, water resources, biological resources, mineral resources, ecological-geological environment, water environment and atmospheric environment. Based on the single factor evaluation results and with the county as the evaluation unit, the comprehensive capacity of resources and environment was evaluated by using the state space method in Poyang Lake Eco-economic Zone. The results showed that it boasted abundant biological resources, quality atmosphere and water environment, and relatively stable geological environment, while restricted by land resource, water resource and mineral resource. Currently, although the comprehensive capacity of the resources and environments in Poyang Lake Eco-economic Zone was not overloaded as a whole, it has been the case in some counties/districts. State space model, with clear indication and high accuracy, could serve as another approach to evaluating comprehensive capacity of regional resources and environment.

Stochastic modeling for reliability shocks, burn-in and heterogeneous populations

CERN Document Server

Finkelstein, Maxim

2013-01-01

Focusing on shocks modeling, burn-in and heterogeneous populations, Stochastic Modeling for Reliability naturally combines these three topics in the unified stochastic framework and presents numerous practical examples that illustrate recent theoretical findings of the authors.  The populations of manufactured items in industry are usually heterogeneous. However, the conventional reliability analysis is performed under the implicit assumption of homogeneity, which can result in distortion of the corresponding reliability indices and various misconceptions. Stochastic Modeling for Reliability fills this gap and presents the basics and further developments of reliability theory for heterogeneous populations. Specifically, the authors consider burn-in as a method of elimination of ‘weak’ items from heterogeneous populations. The real life objects are operating in a changing environment. One of the ways to model an impact of this environment is via the external shocks occurring in accordance with some stocha...

Stochastic switching in biology: from genotype to phenotype

International Nuclear Information System (INIS)

Bressloff, Paul C

2017-01-01

There has been a resurgence of interest in non-equilibrium stochastic processes in recent years, driven in part by the observation that the number of molecules (genes, mRNA, proteins) involved in gene expression are often of order 1–1000. This means that deterministic mass-action kinetics tends to break down, and one needs to take into account the discrete, stochastic nature of biochemical reactions. One of the major consequences of molecular noise is the occurrence of stochastic biological switching at both the genotypic and phenotypic levels. For example, individual gene regulatory networks can switch between graded and binary responses, exhibit translational/transcriptional bursting, and support metastability (noise-induced switching between states that are stable in the deterministic limit). If random switching persists at the phenotypic level then this can confer certain advantages to cell populations growing in a changing environment, as exemplified by bacterial persistence in response to antibiotics. Gene expression at the single-cell level can also be regulated by changes in cell density at the population level, a process known as quorum sensing. In contrast to noise-driven phenotypic switching, the switching mechanism in quorum sensing is stimulus-driven and thus noise tends to have a detrimental effect. A common approach to modeling stochastic gene expression is to assume a large but finite system and to approximate the discrete processes by continuous processes using a system-size expansion. However, there is a growing need to have some familiarity with the theory of stochastic processes that goes beyond the standard topics of chemical master equations, the system-size expansion, Langevin equations and the Fokker–Planck equation. Examples include stochastic hybrid systems (piecewise deterministic Markov processes), large deviations and the Wentzel–Kramers–Brillouin (WKB) method, adiabatic reductions, and queuing/renewal theory. The major aim of

ECONOMIC COMPETTION ENVIRONMENT IN ROMANIA

Directory of Open Access Journals (Sweden)

EMILIA UNGUREANU

2012-12-01

Full Text Available For realizing the paper “Economic Competition Environment in Romania”, I considered the analysis of antitrust norms appliance, the economic concentration control and the control of state aids in Romania. In 2010, the Council activity was impacted by a series of important changes from a legislative point of view, but also by the internal organization. In his modified form, the Competition Law and the new adopted secondary legislation offers to the Competition Council the necessary instruments for efficiently acting in ensuring the market functionality on competition bases. In 2011, the competition authority efforts will be focused on improving the appliance of completion legislation, mainly, by concentrating the analysis on very big violation of law and by finalizing the investigations older than 3 years, on the intensifying the cooperation with implied institutions from the state aid domain, but also on implementing some internal measures, designed to develop the administrative capacity of the institution. The legislative modifications of the Council expected since 2010 for 2011, have like final output the adoption of a new variant of Competition Law 211/1996, some of the adjustments being made since last year, by O.U.G. no. 75/2010, and in 2011 this was approved.

Stochastic Analysis 2010

CERN Document Server

Crisan, Dan

2011-01-01

"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa

Uncertainties must be expected. Stochastic methods support power plant control; Mit Unsicherheiten ist zu rechnen. Stochastische Methoden unterstuetzen Kraftwerkssteuerung

Energy Technology Data Exchange (ETDEWEB)

Syben, Olaf; Dehery, Francois-Regis [ProCom GmbH, Aachen (Germany)

2012-07-01

Uncertainties must be considered for successful portfolio management in the energy markets. This is not only a structural aspect of the increasingly complex interdependences between raw materials, technical assets and economic considerations but also covers the distortion of degrees of freedom in time, which require ever faster decision processes. Stochastic methods make it possible to judge uncertainties even in complex planning problems. Integration of the mathematical methods in an efficient IT environment ensures that a verifiable decision basis is available at any time. (orig./AKB)

Stochastic Strategy Adjustment in Coordination Games

NARCIS (Netherlands)

Kosfeld, M.

1999-01-01

We explore a model of equilibrium selection in coordination games, where agents stochastically adjust their strategies to changes in their local environment. Instead of playing perturbed best-response, we assume that agents follow a rule of "switching to better strategies more likely". We relate

Multistage Stochastic Programming via Autoregressive Sequences

Czech Academy of Sciences Publication Activity Database

Kaňková, Vlasta

2007-01-01

Roč. 15, č. 4 (2007), s. 99-110 ISSN 0572-3043 R&D Projects: GA ČR GA402/07/1113; GA ČR(CZ) GA402/06/0990; GA ČR GD402/03/H057 Institutional research plan: CEZ:AV0Z10750506 Keywords : Economic proceses * Multistage stochastic programming * autoregressive sequences * individual probability constraints Subject RIV: BB - Applied Statistics, Operational Research

Dynamic optimization deterministic and stochastic models

CERN Document Server

Hinderer, Karl; Stieglitz, Michael

2016-01-01

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

Stochastic models for predicting pitting corrosion damage of HLRW containers

International Nuclear Information System (INIS)

Henshall, G.A.

1991-10-01

Stochastic models for predicting aqueous pitting corrosion damage of high-level radioactive-waste containers are described. These models could be used to predict the time required for the first pit to penetrate a container and the increase in the number of breaches at later times, both of which would be useful in the repository system performance analysis. Monte Carlo implementations of the stochastic models are described, and predictions of induction time, survival probability and pit depth distributions are presented. These results suggest that the pit nucleation probability decreases with exposure time and that pit growth may be a stochastic process. The advantages and disadvantages of the stochastic approach, methods for modeling the effects of environment, and plans for future work are discussed

Economic policy and the environment (Republic of Macedonia)

International Nuclear Information System (INIS)

1997-01-01

In general, the areas of significant environmental concerns in Macedonia are located near large urban areas, with industrial sources being the major polluters.Reduced industrial production in the last five years decreased the level of pollutants being discharged in air, water and soil compared in the 1980s. However, if industries resume previous levels of production, without proper environmental checks the pollution load to various media will increase. Today, in Macedonia there is willingness to treat environmental issues as an integral part of the overall strategy for economic and social development during the transition to a market economy. Further, Macedonia plans to harmonize its policies, including the ones on environment, with those of EU so as to promote closer integration with other European countries. The effects of economic restructuring may not be favorable for the environment if environmental policies are not developed soon. In the process of developing a policy to finance environmental protection, two principles need to be adopted and followed at all levels of government, namely 'polluter pays' and 'user pays' principles. This will strengthen the role of local communities in financing environmental protection. (author)

Stochastic analysis of a novel nonautonomous periodic SIRI epidemic system with random disturbances

Science.gov (United States)

Zhang, Weiwei; Meng, Xinzhu

2018-02-01

In this paper, a new stochastic nonautonomous SIRI epidemic model is formulated. Given that the incidence rates of diseases may change with the environment, we propose a novel type of transmission function. The main aim of this paper is to obtain the thresholds of the stochastic SIRI epidemic model. To this end, we investigate the dynamics of the stochastic system and establish the conditions for extinction and persistence in mean of the disease by constructing some suitable Lyapunov functions and using stochastic analysis technique. Furthermore, we show that the stochastic system has at least one nontrivial positive periodic solution. Finally, numerical simulations are introduced to illustrate our results.

Hope for the environment: Free enterprise and other economic regimes

OpenAIRE

Baumol, William Jack

1998-01-01

This paper is the keynote speech delivered by Professor William Baumol at the First World Congress of Environmental Economists that was held in Venice on June 25-27, 1998. It analyses the situation of the environment under different economic regimes: the feudal society, Marxism and capitalism. After a brief description of the environmental situation in medieval England, in the Soviet Nations, in Eastern Europe, in China and in capitalist countries, the author concludes that each economic regi...

Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions

Science.gov (United States)

A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting fram...

Socio-Economic Environment as the Basis for Innovation Economy

Directory of Open Access Journals (Sweden)

Marina Akhmetova

2017-06-01

Full Text Available The authors carried out a correlation analysis of the socio-economic environment factors, which have a decisive influence on the territorial innovative development according to data for the year 2012. The paper discloses socio-economic determinants that provide to reinforce territory’s innovative development. These determinants are higher education development, improving of social and transport infrastructure, growth in small business and trade. The paper also carried out a dynamic analysis according to data for period of 2012 - 2014 in the group of regions (Russian Federation "Generators of Innovations" and disclosed the positive impact of selected key determinants on the regional innovative development. The results of this research may be used in the government practice of different territories (countries, regions for decision-making in the field of socio-economic development.

ROMANIAN ECONOMIC ENVIRONMENT – RESPONSIBILITY POLICIES AND BUSINESS ETHICS

Directory of Open Access Journals (Sweden)

GHEORGHE Stefan

2013-06-01

Full Text Available Corporations regarded as socially responsible can benefit from a large satisfied clientage while the public image of social irresponsibility can end up with a boycott or any other hostile actions from costumers. Positive contributions to social development can be considered by companies as long term investments in the consolidation of a safer community life, better educated and much more equitable which corporations can benefit from by unfolding their activities in a more dynamic, stable and resourceful environment. These are serious economic reasons which can be in the advantage of economic agents who can commit towards different social groups.

Ecological-economical approach to assessment of environment state at the Semipalatinsk test site

International Nuclear Information System (INIS)

Chugunova, N.S.; Balykbaeva, S.Y.

2002-01-01

The paper presents methods used for ecological-economical assessment of the environment condition at the former Semipalatinsk Test Site. It also presents methodology of calculating ecological and economical parameters for different options. Besides, the paper provides data describing assessment of ecological and economical damage caused by defense establishment activities at the Semipalatinsk Test Site. (author)

Stochastic and non-stochastic effects - a conceptual analysis

International Nuclear Information System (INIS)

Karhausen, L.R.

1980-01-01

The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)

Stochastic techno-economic assessment based on Monte Carlo simulation and the Response Surface Methodology: The case of an innovative linear Fresnel CSP (concentrated solar power) system

International Nuclear Information System (INIS)

Bendato, Ilaria; Cassettari, Lucia; Mosca, Marco; Mosca, Roberto

2016-01-01

Combining technological solutions with investment profitability is a critical aspect in designing both traditional and innovative renewable power plants. Often, the introduction of new advanced-design solutions, although technically interesting, does not generate adequate revenue to justify their utilization. In this study, an innovative methodology is developed that aims to satisfy both targets. On the one hand, considering all of the feasible plant configurations, it allows the analysis of the investment in a stochastic regime using the Monte Carlo method. On the other hand, the impact of every technical solution on the economic performance indicators can be measured by using regression meta-models built according to the theory of Response Surface Methodology. This approach enables the design of a plant configuration that generates the best economic return over the entire life cycle of the plant. This paper illustrates an application of the proposed methodology to the evaluation of design solutions using an innovative linear Fresnel Concentrated Solar Power system. - Highlights: • A stochastic methodology for solar plants investment evaluation. • Study of the impact of new technologies on the investment results. • Application to an innovative linear Fresnel CSP system. • A particular application of Monte Carlo simulation and response surface methodology.

Theoretical approach on microscopic bases of stochastic functional self-organization: quantitative measures of the organizational degree of the environment

Energy Technology Data Exchange (ETDEWEB)

Oprisan, Sorinel Adrian [Department of Psychology, University of New Orleans, New Orleans, LA (United States)]. E-mail: soprisan@uno.edu

2001-11-30

There has been increased theoretical and experimental research interest in autonomous mobile robots exhibiting cooperative behaviour. This paper provides consistent quantitative measures of organizational degree of a two-dimensional environment. We proved, by the way of numerical simulations, that the theoretically derived values of the feature are reliable measures of aggregation degree. The slope of the feature's dependence on memory radius leads to an optimization criterion for stochastic functional self-organization. We also described the intellectual heritages that have guided our research, as well as possible future developments. (author)

Symbolic Computing in Probabilistic and Stochastic Analysis

Directory of Open Access Journals (Sweden)

Kamiński Marcin

2015-12-01

Full Text Available The main aim is to present recent developments in applications of symbolic computing in probabilistic and stochastic analysis, and this is done using the example of the well-known MAPLE system. The key theoretical methods discussed are (i analytical derivations, (ii the classical Monte-Carlo simulation approach, (iii the stochastic perturbation technique, as well as (iv some semi-analytical approaches. It is demonstrated in particular how to engage the basic symbolic tools implemented in any system to derive the basic equations for the stochastic perturbation technique and how to make an efficient implementation of the semi-analytical methods using an automatic differentiation and integration provided by the computer algebra program itself. The second important illustration is probabilistic extension of the finite element and finite difference methods coded in MAPLE, showing how to solve boundary value problems with random parameters in the environment of symbolic computing. The response function method belongs to the third group, where interference of classical deterministic software with the non-linear fitting numerical techniques available in various symbolic environments is displayed. We recover in this context the probabilistic structural response in engineering systems and show how to solve partial differential equations including Gaussian randomness in their coefficients.

Economic Security Environment and Implementation of Planning, Programming, Budgeting, Execution (PPBE) System in Georgia

Science.gov (United States)

2004-06-01

Roy J. What Determines Economic Growth? Economic Review – Second Quarter 1993 [References: Barro (1991); Mankiw , Romer, and Well (1992); De Long...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release: distribution unlimited ECONOMIC SECURITY...DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE: Economic Security Environment and Implementation of Planning, Programming, Budgeting, Execution

Stochastic simulation using @Risk for dairy business investment decisions

NARCIS (Netherlands)

Bewley, J.D.; Boehlje, M.D.; Gray, A.W.; Hogeveen, H.; Kenyon, S.J.; Eicher, S.D.; Schutz, M.M.

2010-01-01

Purpose – The purpose of this paper is to develop a dynamic, stochastic, mechanistic simulation model of a dairy business to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm

Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming

Energy Technology Data Exchange (ETDEWEB)

Cardoso, Goncalo; Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; DeForest, Nicholas; Barbosa-Povoa, Ana; Ferrao, Paulo

2013-05-23

This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6percent.

Parameter estimation in stochastic differential equations

CERN Document Server

Bishwal, Jaya P N

2008-01-01

Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume.

Stochastic Modeling of Past Volcanic Crises

Science.gov (United States)

Woo, Gordon

2018-01-01

The statistical foundation of disaster risk analysis is past experience. From a scientific perspective, history is just one realization of what might have happened, given the randomness and chaotic dynamics of Nature. Stochastic analysis of the past is an exploratory exercise in counterfactual history, considering alternative possible scenarios. In particular, the dynamic perturbations that might have transitioned a volcano from an unrest to an eruptive state need to be considered. The stochastic modeling of past volcanic crises leads to estimates of eruption probability that can illuminate historical volcanic crisis decisions. It can also inform future economic risk management decisions in regions where there has been some volcanic unrest, but no actual eruption for at least hundreds of years. Furthermore, the availability of a library of past eruption probabilities would provide benchmark support for estimates of eruption probability in future volcanic crises.

An Innovative Economic Incentive Model for Improvement of the Working Environment in Europe

DEFF Research Database (Denmark)

Koch, Christian

1997-01-01

work injury compensation system, that a number of European countries operate. Building on an understanding of enterprise decision processes and ressources, it is suggested to implement a range of tools targetting different groups of enterprises. The central tools are bonus schemes, a special scheme......The design of economic incentive schemes to promote working environment embetterment has proven complicated. The contribution list some central preconditions and tools of an economic incentive model for improving the working environment. The economic incentive is proposed built into the compulsory...... for small enterprises, a marketing label and low interest investment aid. It is finally discussed what contrains the implementation of such a scheme can be confronted with....

Short-term Probabilistic Forecasting of Wind Speed Using Stochastic Differential Equations

DEFF Research Database (Denmark)

Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg

2016-01-01

and uncertain nature. In this paper, we propose a modeling framework for wind speed that is based on stochastic differential equations. We show that stochastic differential equations allow us to naturally capture the time dependence structure of wind speed prediction errors (from 1 up to 24 hours ahead) and......It is widely accepted today that probabilistic forecasts of wind power production constitute valuable information for both wind power producers and power system operators to economically exploit this form of renewable energy, while mitigating the potential adverse effects related to its variable......, most importantly, to derive point and quantile forecasts, predictive distributions, and time-path trajectories (also referred to as scenarios or ensemble forecasts), all by one single stochastic differential equation model characterized by a few parameters....

Libor at crossroads: Stochastic switching detection using information theory quantifiers

International Nuclear Information System (INIS)

Bariviera, Aurelio F.; Guercio, M. Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

2016-01-01

Highlights: • 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years, were considered. • The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. • Our analysis unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. • This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”. - Abstract: This paper studies the 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years. The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. This planar representation allows the discrimination of different stochastic and chaotic regimes. Using a temporal analysis based on moving windows, this paper unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”, i.e. the manipulation of interest rates carried out by several prime banks. We argue that our methodology is suitable as a market watch mechanism, as it makes visible the temporal redution in informational efficiency of the market.

Effects of stochastic noise on dynamical decoupling procedures

Energy Technology Data Exchange (ETDEWEB)

Bernad, Jozsef Zsolt; Frydrych, Holger; Alber, Gernot [Institut fuer Angewandte Physik, Technische Universitaet Darmstadt, D-64289 Darmstadt (Germany)

2013-07-01

Dynamical decoupling is a well-established technique to protect quantum systems from unwanted influences of their environment by exercising active control. It has been used experimentally to drastically increase the lifetime of qubit states in various implementations. The efficiency of different dynamical decoupling schemes defines the lifetime. However, errors in control operations always limit this efficiency. We propose a stochastic model as a possible description of imperfect control pulses and discuss the impact of this kind of error on different decoupling schemes. In the limit of continuous control, i.e. if the number of pulses N → ∞, we derive a stochastic differential equation for the evolution of the density operator of the controlled system and its environment. In the context of this modified time evolution we discuss possibilities of protecting qubit states against environmental noise.

Continuous-Time Public Good Contribution Under Uncertainty: A Stochastic Control Approach

International Nuclear Information System (INIS)

Ferrari, Giorgio; Riedel, Frank; Steg, Jan-Henrik

2017-01-01

In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private consumption and irreversible contributions to increase the level of some public good. We investigate the corresponding social planner problem and the case of strategic interaction between the agents, i.e. the public good contribution game. We show existence and uniqueness of the social planner’s optimal policy, we characterize it by necessary and sufficient stochastic Kuhn–Tucker conditions and we provide its expression in terms of the unique optional solution of a stochastic backward equation. Similar stochastic first order conditions prove to be very useful for studying any Nash equilibria of the public good contribution game. In the symmetric case they allow us to prove (qualitative) uniqueness of the Nash equilibrium, which we again construct as the unique optional solution of a stochastic backward equation. We finally also provide a detailed analysis of the so-called free rider effect.

Continuous-Time Public Good Contribution Under Uncertainty: A Stochastic Control Approach

Energy Technology Data Exchange (ETDEWEB)

Ferrari, Giorgio, E-mail: giorgio.ferrari@uni-bielefeld.de; Riedel, Frank, E-mail: frank.riedel@uni-bielefeld.de; Steg, Jan-Henrik, E-mail: jsteg@uni-bielefeld.de [Bielefeld University, Center for Mathematical Economics (Germany)

2017-06-15

In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private consumption and irreversible contributions to increase the level of some public good. We investigate the corresponding social planner problem and the case of strategic interaction between the agents, i.e. the public good contribution game. We show existence and uniqueness of the social planner’s optimal policy, we characterize it by necessary and sufficient stochastic Kuhn–Tucker conditions and we provide its expression in terms of the unique optional solution of a stochastic backward equation. Similar stochastic first order conditions prove to be very useful for studying any Nash equilibria of the public good contribution game. In the symmetric case they allow us to prove (qualitative) uniqueness of the Nash equilibrium, which we again construct as the unique optional solution of a stochastic backward equation. We finally also provide a detailed analysis of the so-called free rider effect.

Stochastic frontier model approach for measuring stock market efficiency with different distributions.

Science.gov (United States)

Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.

Stochastic frontier model approach for measuring stock market efficiency with different distributions.

Directory of Open Access Journals (Sweden)

Md Zobaer Hasan

Full Text Available The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.

The critical domain size of stochastic population models.

Science.gov (United States)

Reimer, Jody R; Bonsall, Michael B; Maini, Philip K

2017-02-01

Identifying the critical domain size necessary for a population to persist is an important question in ecology. Both demographic and environmental stochasticity impact a population's ability to persist. Here we explore ways of including this variability. We study populations with distinct dispersal and sedentary stages, which have traditionally been modelled using a deterministic integrodifference equation (IDE) framework. Individual-based models (IBMs) are the most intuitive stochastic analogues to IDEs but yield few analytic insights. We explore two alternate approaches; one is a scaling up to the population level using the Central Limit Theorem, and the other a variation on both Galton-Watson branching processes and branching processes in random environments. These branching process models closely approximate the IBM and yield insight into the factors determining the critical domain size for a given population subject to stochasticity.

Finite Action-Set Learning Automata for Economic Dispatch Considering Electric Vehicles and Renewable Energy Sources

Directory of Open Access Journals (Sweden)

Junpeng Zhu

2014-07-01

Full Text Available The coming interaction between a growing electrified vehicle fleet and the desired growth in renewable energy provides new insights into the economic dispatch (ED problem. This paper presents an economic dispatch model that considers electric vehicle charging, battery exchange stations, and wind farms. This ED model is a high-dimensional, non-linear, and stochastic problem and its solution requires powerful methods. A new finite action-set learning automata (FALA-based approach that has the ability to adapt to a stochastic environment is proposed. The feasibility of the proposed approach is demonstrated in a modified IEEE 30 bus system. It is compared with continuous action-set learning automata and particle swarm optimization-based approaches in terms of convergence characteristics, computational efficiency, and solution quality. Simulation results show that the proposed FALA-based approach was indeed capable of more efficiently obtaining the approximately optimal solution. In addition, by using an optimal dispatch schedule for the interaction between electric vehicle stations and power systems, it is possible to reduce the gap between demand and power generation at different times of the day.

(Ir)rational choices of humans, rhesus macaques, and capuchin monkeys in dynamic stochastic environments.

Science.gov (United States)

Watzek, Julia; Brosnan, Sarah F

2018-05-28

Human and animal decision-making is known to violate rational expectations in a variety of contexts. Previous models suggest that statistical structures of real-world environments can favor such seemingly irrational behavior, but this has not been tested empirically. We tested 16 capuchin monkeys, seven rhesus monkeys, and 30 humans in a computerized experiment that implemented such stochastic environments. Subjects chose from among up to three options of different value that disappeared and became available again with different probabilities. All species overwhelmingly chose transitively (A > B > C) in the control condition, where doing so maximized overall gain. Most subjects also adhered to transitivity in the test condition, where it was suboptimal, but ultimately led to negligible losses compared to the optimal, non-transitive strategy. We used a modelling approach to show that differences in temporal discounting may account for this pattern of choices on a proximate level. Specifically, when short- and long-term goals are valued similarly, near-optimal decision rules can map onto rational choice principles. Such cognitive shortcuts have been argued to have evolved to preserve mental resources without sacrificing good decision-making, and here we provide evidence that these heuristics can provide almost identical outcomes even in situations in which they lead to suboptimal choices. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program

International Nuclear Information System (INIS)

Nojavan, Sayyad; Zare, Kazem; Mohammadi-Ivatloo, Behnam

2017-01-01

Highlights: • Stochastic energy management of retailer under smart grid environment is proposed. • Optimal selling price is determined in the smart grid environment. • Fixed, time-of-use and real-time pricing are determined for selling to customers. • Charge/discharge of ESS is determined to increase the expected profit of retailer. • Demand response program is proposed to increase the expected profit of retailer. - Abstract: In this paper, bilateral contracting and selling price determination problems for an electricity retailer in the smart grid environment under uncertainties have been considered. Multiple energy procurement sources containing pool market (PM), bilateral contracts (BCs), distributed generation (DG) units, renewable energy sources (photovoltaic (PV) system and wind turbine (WT)) and energy storage system (ESS) as well as demand response program (DRP) as virtual generation unit are considered. The scenario-based stochastic framework is used for uncertainty modeling of pool market prices, client group demand and variable climate condition containing temperature, irradiation and wind speed. In the proposed model, the selling price is determined and compared by the retailer in the smart grid in three cases containing fixed pricing, time-of-use (TOU) pricing and real-time pricing (RTP). It is shown that the selling price determination based on RTP by the retailer leads to higher expected profit. Furthermore, demand response program (DRP) has been implemented to flatten the load profile to minimize the cost for end-user customers as well as increasing the retailer profit. To validate the proposed model, three case studies are used and the results are compared.

Marginal socio-economic effects of an employer's efforts to improve the work environment.

Science.gov (United States)

Rezagholi, Mahmoud

2018-01-01

Workplace health promotion (WHP) strongly requires the employer's efforts to improve the psychosocial, ergonomic, and physical environments of the workplace. There are many studies discussing the socio-economic advantage of WHP intervention programmes and thus the internal and external factors motivating employers to implement and integrate such programmes. However, the socio-economic impacts of the employer's multifactorial efforts to improve the work environment need to be adequately assessed. Data were collected from Swedish company Sandvik Materials Technology (SMT) through a work environment survey in April 2014. Different regression equations were analysed to assess marginal effects of the employer's efforts on overall labour effectiveness (OLE), informal work impairments (IWI), lost working hours (LWH), and labour productivity loss (LPL) in terms of money. The employer's multifactorial efforts resulted in increasing OLE, decreasing IWI and illness-related LWH, and cost savings in terms of decreasing LPL. Environmental factors at the workplace are the important determinant factor for OLE, and the latter is where socio-economic impacts of the employer's efforts primarily manifest.

Noncausal stochastic calculus

CERN Document Server

Ogawa, Shigeyoshi

2017-01-01

This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...

Economic valuation of heat pumps and electric boilers in the Danish energy system

International Nuclear Information System (INIS)

Nielsen, Maria Grønnegaard; Morales, Juan Miguel; Zugno, Marco; Pedersen, Thomas Engberg; Madsen, Henrik

2016-01-01

Highlights: • We assess the economic value of heat pumps and electric boilers in Denmark. • The daily operation of a heat and power system is modeled by stochastic programming. • Deterministic models overestimate the value of heat pumps and electric boilers. • Heat pumps and electric boilers can reduce the cost of operating the Danish system. • Falling power prices may boost the future value of heat pumps and electric boilers. - Abstract: Heat pumps (HP) and electric immersion boilers (EB) have great potential to increase flexibility in energy systems. In parallel, decreasing taxes on electricity-based heat production are creating a more favorable economic environment for the deployment of these units in Denmark. In this paper, the economic value of heat pumps and electric boilers is assessed by simulating their day-to-day market performance using a novel operational strategy based on two-stage stochastic programming. This stochastic model is employed to optimize jointly the daily operation of HPs and EBs along with the Combined Heat and Power (CHP) units in the system. Uncertainty in the heat demand and power price is modeled via scenarios representing different plausible paths for their future evolution. A series of case-studies are performed using real-world data for the heat and power systems in the Copenhagen area during four representative weeks of 2013. We show that the use of stochastic operational models is critical, as standard deterministic models provide an overestimation of the added benefits from the installation of HPs and EBs, thus leading to over-investment in capacity. Furthermore, we perform sensitivity studies to investigate the effect on market performance of varying capacity and efficiency for these units, as well as of different levels of prices in the electricity market. We find that these parameters substantially affect the profitability of heat pumps and electric boilers, hence, they must be carefully assessed by potential

Power grid operation in a market environment economic efficiency and risk mitigation

CERN Document Server

2017-01-01

This book examines both system operation and market operation perspectives, focusing on the interaction between the two. It incorporates up-to-date field experiences, presents challenges, and summarizes the latest theoretic advancements to address those challenges. The book is divided into four parts. The first part deals with the fundamentals of integrated system and market operations, including market power mitigation, market efficiency evaluation, and the implications of operation practices in energy markets. The second part discusses developing technologies to strengthen the use of the grid in energy markets. System volatility and economic impact introduced by the intermittency of wind and solar generation are also addressed. The third part focuses on stochastic applications, exploring new approaches of handling uncerta nty in Security Constrained Unit Commitment (SCUC) as well as the reserves needed for power system operation. The fourth part provides ongoing efforts of utilizing transmission facilities ...

Global economics and the environment

International Nuclear Information System (INIS)

Stone, R.D.; Hamilton, E.

1991-01-01

The rampant destruction of the rural tropics the earth's most fertile source of life will continue unchecked unless a global bargain can be reached between the capital-rich North and the economically destitute South. This report presents the findings of a colloquium sponsored by the Council on Foreign Relations and the World Resources Institute, and assesses the prospects for a global policy for sustainable growth in the Third World. It reviews how the North constrains the development of such a policy by its actions in the areas of international trade, public and private investment, and debt and recommends new efforts to foster mutual cooperation. It also outlines a series of creative recommendations from the colloquium's international and multidisciplinary panel of experts. Offering an agenda for the June 1992 United Nations Conference on Environment and Development (UNCED), this report sets the stage for one of the most important global challenges of the coming decade

Stochastic energy management of renewable micro-grids in the correlated environment using unscented transformation

International Nuclear Information System (INIS)

Tabatabaee, Sajad; Mortazavi, Seyed Saeedallah; Niknam, Taher

2016-01-01

This paper addresses the optimal stochastic scheduling of the distributed generation units in a micro-grid. In this way, it introduces a new sufficient stochastic framework to model the correlated uncertainties in the micro-grid that includes different types of RESs such as photovoltaics, wind turbines, micro-turbine, fuel cell as well as battery as the storage device. The proposed stochastic method makes use of unscented transforms to model correlated uncertain parameters. The ability of the unscented transform method to model correlated uncertain variables is particularly appealing in the context of power systems, wherein noticeable inherent correlation exists. Due to the highly complex nature of the problem, a new optimization method based on the harmony search algorithm along with an intelligent modification method is devised to solve the proposed optimization problem, efficiently. The proposed optimization algorithm is equipped with powerful search mechanisms that make it suitable for solving both discrete and continuous problems. In comparison with the original harmony search algorithm, the proposed modified optimization algorithm has few setting parameters. The new modified harmony search algorithm provides proper balance between the local and global searches. The feasibility and satisfactory performance of performance of the proposed method are examined on two typical grid-connected MGs. - Highlights: • Introducing a new artificial optimization algorithm based on HS evolutionary technique. • Introducing a new stochastic framework based on unscented transform to model the uncertainties of the problem. • Proposing a new modification method for HS to improve its total search ability.

Energy, economics, environment and politics

International Nuclear Information System (INIS)

Foster, R.J.

1993-01-01

The pressure on the Earth's environment and resources is the ultimate result of population growth and the only humane means available for stabilizing world population is to increase per capita living standards in the developing countries. However, this will require a very large increase in global energy consumption. If, as at present, the energy demand is met largely by fossil fuels, atmospheric concentrations of CO 2 will rise rapidly. Until the end of the century, and perhaps beyond it, any actions to control CO 2 emissions will be taken for precautionary reasons alone, because no reliable basis will exist for predicting their global (or regional) impact on the climate. The sustainability of the natural environment is also under threat from human activities such as the clearing of forests for crop-growing and grazing. The resulting elimination of habitats for, and genetic variability in, the victor is as serious a concern as global warming. The economic and social consequences of rigidly curtailing the growth of energy use in developed countries would be severe, and in developing countries extreme; even then greenhouse gas build up could only be slowed not prevented. On the other hand, a wealthier world would be more able to bear the financial burden of protecting biodiversity. It is concluded that since the developed countries on whom the main cost would have to fall, adequate effort into both biodiversity and greenhouse gas reduction, biodiversity must take procedence. (1 figure, 2 tables). (UK)

Stochastic modelling to evaluate the economic efficiency of treatment of chronic subclinical mastitis

NARCIS (Netherlands)

Steeneveld, W.; Hogeveen, H.; Borne, van den B.H.P.; Swinkels, J.M.

2006-01-01

Treatment of subclinical mastitis is traditionally no common practice. However, some veterinarians regard treatment of some types of subclinical mastitis to be effective. The goal of this research was to develop a stochastic Monte Carlo simulation model to support decisions around treatment of

Detecting change in stochastic sound sequences.

Directory of Open Access Journals (Sweden)

Benjamin Skerritt-Davis

2018-05-01

Full Text Available Our ability to parse our acoustic environment relies on the brain's capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance. In this work, we investigate the brain's sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects' behavior indicates an important role of perceptual constraints in listeners' ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain's ability to process stochastic sound sequences.

Polish economic clusters and their efforts to protect the environment – selected examples

Directory of Open Access Journals (Sweden)

Dyrda-Muskus Joanna

2014-01-01

Full Text Available This paper presents the benefits they can obtain business which aim to protect the environment. The environment protection has found its place and affects the process of systemic change of the Polish economy. This article assumes that building a competitive economy and enterprise development based on the principle of sustainable development requires the development of mechanisms for mutual benefits. These will be the economic mechanisms, technical and technological, and social. All these mechanisms are concentrated in clusters. Pursue sustainable development policies, an emphasis on environmental protection will be the general element for them a competitive advantage. Sustainable development will in this case be both the agent and the goal of economic and entrepreneurship development. Basing on the assumption that economic development is possible through the achievement of competitive advantage, sustainable development should be treated as its source.

Stochastic modeling concepts in groundwater and risk assessment: potential application to marine problems

International Nuclear Information System (INIS)

Hamed, Maged M.

2000-01-01

Parameter uncertainty is ubiquitous in marine environmental processes. Failure to account for this uncertainty may lead to erroneous results, and may have significant environmental and economic ramifications. Stochastic modeling of oil spill transport and fate is, therefore, central in the development of an oil spill contingency plan for new oil and gas projects. Over the past twenty years, several stochastic modeling tools have been developed for modeling parameter uncertainty, including the spectral, perturbation, and simulation methods. In this work we explore the application of a new stochastic methodology, the first-order reliability method (FORM), in oil spill modeling. FORM was originally developed in the structural reliability field and has been recently applied to various environmental problems. The method has many appealing features that makes it a powerful tool for modeling complex environmental systems. The theory of FORM is presented, identifying the features that distinguish the method from other stochastic tools. Different formulations to the reliability-based stochastic oil spill modeling are presented in a decision-analytic context. (Author)

Groundwater Management at Varamin Plain: The Consideration of Stochastic and Environmental Effects

International Nuclear Information System (INIS)

Najafi Alamdarlo, H.; Ahmadian, M.; Khalilian, S.

2016-01-01

Groundwater is one of the common resources in Varamin Plain, but due to over extraction it has been exposed to ruin. This phenomenon will lead to economic and environmental problems. On the other hand, the world is expected to face with more stochastic events of water supply. Furthermore, incorporating stochastic consideration of water supply becomes more acute in designing water facilities. Therefore, the strategies should be applied to improve managing resources and increase the efficiency of irrigation system. Hence, in this study the effect of efficiency improvement of irrigation system on the exploitation of groundwater and cropping pattern is examined in deterministic and stochastic condition using Nash bargaining theory. The results showed that farmers in B scenario are more willing to cooperate and as a result of their cooperation, they lose only 3 percentages of their present value of the objective function. Therefore, the efficiency improvement of irrigation system can result in improving the cooperation between farmers and increasing the amount of reserves.Groundwater is one of the common resources in Varamin Plain, but due to over extraction it has been exposed to ruin. This phenomenon will lead to economic and environmental problems. On the other hand, the world is expected to face with more stochastic events of water supply. Furthermore, incorporating stochastic consideration of water supply becomes more acute in designing water facilities. Therefore, the strategies should be applied to improve managing resources and increase the efficiency of irrigation system. Hence, in this study the effect of efficiency improvement of irrigation system on the exploitation of groundwater and cropping pattern is examined in deterministic and stochastic condition using Nash bargaining theory. The results showed that farmers in B scenario are more willing to cooperate and as a result of their cooperation, they lose only 3 percentages of their present value of the

Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management

Science.gov (United States)

Mo Zhou; Joseph Buongiorno

2011-01-01

Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to...

Integrated multiperiod power generation and transmission expansion planning with sustainability aspects in a stochastic environment

International Nuclear Information System (INIS)

Seddighi, Amir Hossein; Ahmadi-Javid, Amir

2015-01-01

This paper presents a multistage stochastic programming model to address sustainable power generation and transmission expansion planning. The model incorporates uncertainties about future electricity demand, fuel prices, greenhouse gas emissions, as well as possible disruptions to which the power system is subject. A number of sustainability regulations and policies are considered to establish a framework for the social responsibility of the power system. The proposed model is applied to a real-world case, and several sensitivity analyses are carried out to provide managerial insights into different aspects of the model. The results emphasize the important role played by sustainability policies on the configuration of the power grid. - Highlights: • This paper considers integrated power generation and transmission expansion planning. • Sustainability aspects are incorporated into a multiperiod stochastic setting. • A stochastic mathematical programming model is developed to address the problem. • The model is applied to a real-world case and numerical studies are carried out

STOCHASTIC FLOWS OF MAPPINGS

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.

Economic consequences of reproductive performance in dairy cattle

NARCIS (Netherlands)

Inchaisri, C.; Jorritsma, R.; Vos, P.L.A.M.; Weijden, van der G.C.; Hogeveen, H.

2010-01-01

The net economic value of reproductive efficiency in dairy cattle was estimated using a stochastic dynamic simulation model. The objective was to compare the economic consequences of reproductive performance scenarios (“average” and “poor”) of a cow having a good reproductive performance and to

An Evaluation of the Economic Theoretical Potential of the Rural Environment Mismanged During 1956-2010

Directory of Open Access Journals (Sweden)

Florentin Gabriel Niculescu

2015-09-01

Full Text Available Under the context of the essential role and growing importance of the rural environment in the development of a country, we focus on evaluating the economic theoretical potential of the rural environment that we consider to have been mismanaged during 1956-2010. For this purpose, in this paper we define, describe and explain the main concepts, as to be able to evaluate the economic potential of the rural development and further contribute to its improvement. The study focuses on the correlations between the population of working age, occupancy, unemployment and the wasted economic potential, putting forward a new concept, statistically valid, demographic named the absolute able overpopulation.

Growth structure and environment. 6 contributions to the macro economic model development

International Nuclear Information System (INIS)

Wier, Mette

1998-04-01

This thesis comprises 6 papers on the application of macro economic models to environmental problems. Interactions between the economic and the ecological models are elucidated and a description is given of a possible systematization of of the environmental-economic cycle within a macro economic model. Economic and technological limitations affecting the potential environmental advantages are discussed. In the second part of the thesis the general interdependence of production and consumption, and the various forms of environmental stress is analyzed. For this purpose an environment-related input-output model is presented, where for each industry there are given emissions and/or consumption of natural resources (so-called environmental coefficients), which are likely to originate from the activities of this industry. As examples of macro economic modelling,the nitrogen cycle in Denmark, environmental effects of consumer choice, use of building materials and emission due to energy generation and consumption etc. are analyzed. (EG) 146 refs

Modelling the interaction between flooding events and economic growth

Directory of Open Access Journals (Sweden)

J. Grames

2015-06-01

Full Text Available Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014. These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.

Stochastic processes

CERN Document Server

Parzen, Emanuel

1962-01-01

Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine

Economic Analysis of Biological Invasions in Forests

Science.gov (United States)

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

Policies and measures for economic efficiency, energy security and environment protection in India

International Nuclear Information System (INIS)

Venkaiah, M.; Kaushik, S.C.; Dewangan, M.L.

2007-01-01

India needs to sustain 8-10% economic growth to meet energy needs of people below poverty line. India would, at least, need to grow its primary energy supply (3-4 times) of present consumption to deliver a sustained growth of 8% by 2031. This paper discusses India's policies and measures for economic efficiency, environment protection and energy security (3-E). (author)

Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties

International Nuclear Information System (INIS)

Osmani, Atif; Zhang, Jun

2013-01-01

An integrated multi-feedstock (i.e. switchgrass and crop residue) lignocellulosic-based bioethanol supply chain is studied under jointly occurring uncertainties in switchgrass yield, crop residue purchase price, bioethanol demand and sales price. A two-stage stochastic mathematical model is proposed to maximize expected profit by optimizing the strategic and tactical decisions. A case study based on ND (North Dakota) state in the U.S. demonstrates that in a stochastic environment it is cost effective to meet 100% of ND's annual gasoline demand from bioethanol by using switchgrass as a primary and crop residue as a secondary biomass feedstock. Although results show that the financial performance is degraded as variability of the uncertain parameters increases, the proposed stochastic model increasingly outperforms the deterministic model under uncertainties. The locations of biorefineries (i.e. first-stage integer variables) are insensitive to the uncertainties. Sensitivity analysis shows that “mean” value of stochastic parameters has a significant impact on the expected profit and optimal values of first-stage continuous variables. Increase in level of mean ethanol demand and mean sale price results in higher bioethanol production. When mean switchgrass yield is at low level and mean crop residue price is at high level, all the available marginal land is used for switchgrass cultivation. - Highlights: • Two-stage stochastic MILP model for maximizing profit of a multi-feedstock lignocellulosic-based bioethanol supply chain. • Multiple uncertainties in switchgrass yield, crop residue purchase price, bioethanol demand, and bioethanol sale price. • Proposed stochastic model outperforms the traditional deterministic model under uncertainties. • Stochastic parameters significantly affect marginal land allocation for switchgrass cultivation and bioethanol production. • Location of biorefineries is found to be insensitive to the stochastic environment

Is economic growth good or bad for the environment? Empirical evidence from Korea

International Nuclear Information System (INIS)

Baek, Jungho; Kim, Hyun Seok

2013-01-01

The effects of economic growth on the environment in Korea, for a given level of energy consumption, and fossil fuels and nuclear energy in electricity production, are examined in a dynamic cointegration framework. To that end, the autoregressive distributed lag (ARDL) approach is used. We find empirical evidence supporting the existence of the environmental Kuznets curve (EKC) hypothesis for Korea; that is, economic growth indeed plays a favorable role in influencing environmental outcomes. It is also found that, in both the short- and long-run, nuclear energy has a beneficial effect on environmental quality, whereas fossil fuels in electricity production and energy consumption have a detrimental effect on the environment. - Highlights: ► We examine the validity of the environmental Kuznets curve hypothesis for Korea. ► The model includes the roles of energy consumption and electricity production. ► We find the existence of the EKC hypothesis for Korea. ► Nuclear energy is found to have a beneficial effect on the environment. ► Fossil fuels and energy consumption have a detrimental effect on the environment

An Evaluation of the Economic Theoretical Potential of the Rural Environment Mismanged During 1956-2010

OpenAIRE

Florentin Gabriel Niculescu

2015-01-01

Under the context of the essential role and growing importance of the rural environment in the development of a country, we focus on evaluating the economic theoretical potential of the rural environment that we consider to have been mismanaged during 1956-2010. For this purpose, in this paper we define, describe and explain the main concepts, as to be able to evaluate the economic potential of the rural development and further contribute to its improvement. The study focuses on the correlati...

Estimation of Parameters in Mean-Reverting Stochastic Systems

Directory of Open Access Journals (Sweden)

Tianhai Tian

2014-01-01

Full Text Available Stochastic differential equation (SDE is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.

Stochastic calculus for uncoupled continuous-time random walks.

Science.gov (United States)

Germano, Guido; Politi, Mauro; Scalas, Enrico; Schilling, René L

2009-06-01

The continuous-time random walk (CTRW) is a pure-jump stochastic process with several applications not only in physics but also in insurance, finance, and economics. A definition is given for a class of stochastic integrals driven by a CTRW, which includes the Itō and Stratonovich cases. An uncoupled CTRW with zero-mean jumps is a martingale. It is proved that, as a consequence of the martingale transform theorem, if the CTRW is a martingale, the Itō integral is a martingale too. It is shown how the definition of the stochastic integrals can be used to easily compute them by Monte Carlo simulation. The relations between a CTRW, its quadratic variation, its Stratonovich integral, and its Itō integral are highlighted by numerical calculations when the jumps in space of the CTRW have a symmetric Lévy alpha -stable distribution and its waiting times have a one-parameter Mittag-Leffler distribution. Remarkably, these distributions have fat tails and an unbounded quadratic variation. In the diffusive limit of vanishing scale parameters, the probability density of this kind of CTRW satisfies the space-time fractional diffusion equation (FDE) or more in general the fractional Fokker-Planck equation, which generalizes the standard diffusion equation, solved by the probability density of the Wiener process, and thus provides a phenomenologic model of anomalous diffusion. We also provide an analytic expression for the quadratic variation of the stochastic process described by the FDE and check it by Monte Carlo.

Simulation of quantum dynamics based on the quantum stochastic differential equation.

Science.gov (United States)

Li, Ming

2013-01-01

The quantum stochastic differential equation derived from the Lindblad form quantum master equation is investigated. The general formulation in terms of environment operators representing the quantum state diffusion is given. The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. The effectiveness and superiority of the algorithm are verified by the performance analysis of the accuracy and the computational cost in comparison with the classical Runge-Kutta algorithm.

A bilevel model for electricity retailers' participation in a demand response market environment

DEFF Research Database (Denmark)

Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

2013-01-01

(followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal......-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility....

Bayesian estimation and entropy for economic dynamic stochastic models: An exploration of overconsumption

International Nuclear Information System (INIS)

Argentiero, Amedeo; Bovi, Maurizio; Cerqueti, Roy

2016-01-01

This paper examines psycho-induced overconsumption in a dynamic stochastic context. As emphasized by well-established psychological results, these psycho-distortions derive from a decision making based on simple rules-of-thumb, not on analytically sounded optimizations. To our end, we therefore compare two New Keynesian models. The first is populated by optimizing Muth-rational agents and acts as the normative benchmark. The other is a “psycho-perturbed” version of the benchmark that allows for the potential presence of overoptimism and, hence, of overconsumption. The parameters of these models are estimated through a Bayesian-type procedure, and performances are evaluated by employing an entropy measure. Such methodologies are particularly appropriate here since they take in full consideration the complexity generated by the randomness of the considered systems. In particular, they let to derive a not negligible information on the size and on the cyclical properties of the biases. In line with cognitive psychology suggestions our evidence shows that the overoptimism/overconsumption is: widespread—it is detected in nation-wide data; persistent—it emerges in full-sample estimations; it moves according to the expected cyclical behavior—larger in booms, and it disappears in crises. Moreover, by taking into account the effect of these psycho-biases, the model fits actual data better than the benchmark. All considered, then, enhancing the existing literature our findings: i) sustain the importance of inserting psychological distortions in macroeconomic models and ii) underline that system dynamics and psycho biases have statistically significant and economically important connections.

Economic consequences of biological variation

DEFF Research Database (Denmark)

Otto, Lars

2005-01-01

We present an economic decision support model, based on a Bayesian network, for Mycoplasma infection in slaughter swine production. The model describes the various risk factors for Mycoplasma infection and their interactions. This leads to a stochastic determination of the consequences of product...

Improved operating strategies for uranium extraction: a stochastic simulation

International Nuclear Information System (INIS)

Broekman, B.R.

1986-01-01

Deterministic and stochastic simulations of a Western Transvaal uranium process are used in this research report to determine more profitable uranium plant operating strategies and to gauge the potential financial benefits of automatic process control. The deterministic simulation model was formulated using empirical and phenomenological process models. The model indicated that profitability increases significantly as the uranium leaching strategy becomes harsher. The stochastic simulation models use process variable distributions corresponding to manually and automatically controlled conditions to investigate the economic gains that may be obtained if a change is made from manual to automatic control of two important process variables. These lognormally distributed variables are the pachuca 1 sulphuric acid concentration and the ferric to ferrous ratio. The stochastic simulations show that automatic process control is justifiable in certain cases. Where the leaching strategy is relatively harsh, such as that in operation during January 1986, it is not possible to justify an automatic control system. Automatic control is, however, justifiable if a relatively mild leaching strategy is adopted. The stochastic and deterministic simulations represent two different approaches to uranium process modelling. This study has indicated the necessity for each approach to be applied in the correct context. It is contended that incorrect conclusions may have been drawn by other investigators in South Africa who failed to consider the two approaches separately

Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants

International Nuclear Information System (INIS)

Niknam, Taher; Kavousi Fard, Abdollah; Baziar, Aliasghar

2012-01-01

This paper assesses the operation and management of electrical energy, hydrogen production and thermal load supplement by the Fuel Cell Power Plants (FCPP) in the distribution systems with regard to the uncertainties which exist in the load demand as well as the price of buying natural gas for FCPPs, fuel cost for residential loads, tariff for purchasing electricity, tariff for selling electricity, hydrogen selling price, operation and maintenance cost and the price of purchasing power from the grid. Therefore, a new modified multi-objective optimization algorithm called Teacher-Learning Algorithm (TLA) is proposed to integrate the optimal operation management of Proton Exchange Membrane FCPPs (PEM-FCPPs) and the optimal configuration of the system through an economic model of the PEM-FCPP. In order to improve the total ability of TLA for global search and exploration, a new modification process is suggested such that the algorithm will search the total search space globally. Also, regarding the uncertainties of the new complicated power systems, in this paper for the first time, the DFR problem is investigated in a stochastic environment by the use of probabilistic load flow technique based on Point Estimate Method (PEM). In order to see the feasibility and the superiority of the proposed method, a standard test system is investigated as the case study. The simulation results are investigated in four different scenarios to show the effect of hydrogen production and thermal recovery more evidently. -- Highlights: ► Present an economical and thermal modeling of PEM-FCPPs. ► Present an approach for optimal operation of PEM-FCPPs in a stochastic environment. ► Consider benefits of thermal recovery and Hydrogen production for PEM-FCPPs. ► Present several scenarios for management of PEM-FCPPs.

Joint  effects of habitat configuration and temporal stochasticity on population dynamics

Science.gov (United States)

Jennifer M. Fraterrigo; Scott M. Pearson; Monica G. Turner

2009-01-01

Habitat configuration and temporal stochasticity in the environment are recognized as important drivers of population structure, yet few studies have examined the combined influence of these factors....

Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

NARCIS (Netherlands)

van Haastrecht, A.; Lord, R.; Pelsser, A.; Schrager, D.

2009-01-01

We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of

Economic Feasibility of Recirculating Aquaculture Systems in Pangasius Farming

NARCIS (Netherlands)

Pham, T.A.N.; Gielen-Meuwissen, M.P.M.; Le, T.C.; Verreth, J.A.J.; Bosma, R.H.; Oude Lansink, A.G.J.M.

2016-01-01

This study aims to analyze the economic feasibility of recirculating aquaculture systems (RAS) in pangasius farming in Vietnam. The study uses a capital budgeting approach and accounts for uncertainty in key parameters. Stochastic simulation is used to simulate the economic performance of medium and

Health safety nets can break cycles of poverty and disease: a stochastic ecological model.

Science.gov (United States)

Plucinski, Mateusz M; Ngonghala, Calistus N; Bonds, Matthew H

2011-12-07

The persistence of extreme poverty is increasingly attributed to dynamic interactions between biophysical processes and economics, though there remains a dearth of integrated theoretical frameworks that can inform policy. Here, we present a stochastic model of disease-driven poverty traps. Whereas deterministic models can result in poverty traps that can only be broken by substantial external changes to the initial conditions, in the stochastic model there is always some probability that a population will leave or enter a poverty trap. We show that a 'safety net', defined as an externally enforced minimum level of health or economic conditions, can guarantee ultimate escape from a poverty trap, even if the safety net is set within the basin of attraction of the poverty trap, and even if the safety net is only in the form of a public health measure. Whereas the deterministic model implies that small improvements in initial conditions near the poverty-trap equilibrium are futile, the stochastic model suggests that the impact of changes in the location of the safety net on the rate of development may be strongest near the poverty-trap equilibrium.

Geocapacity: economic feasibility of CCS in networked systems

NARCIS (Netherlands)

Neele, F.; Hendriks, C.; Brandsma, R.

2009-01-01

A Decision Support System (DSS) has been developed to evaluate the technical and economical feasibility of CO2 storage in the subsurface. The DSS performs a detailed, stochastic analysis of the technical and economical aspects of a CCS project, which consists of any number of CO2 sources and sinks

The interpolation method of stochastic functions and the stochastic variational principle

International Nuclear Information System (INIS)

Liu Xianbin; Chen Qiu

1993-01-01

Uncertainties have been attaching more importance to increasingly in modern engineering structural design. Viewed on an appropriate scale, the inherent physical attributes (material properties) of many structural systems always exhibit some patterns of random variation in space and time, generally the random variation shows a small parameter fluctuation. For a linear mechanical system, the random variation is modeled as a random one of a linear partial differential operator and, in stochastic finite element method, a random variation of a stiffness matrix. Besides the stochasticity of the structural physical properties, the influences of random loads which always represent themselves as the random boundary conditions bring about much more complexities in structural analysis. Now the stochastic finite element method or the probabilistic finite element method is used to study the structural systems with random physical parameters, whether or not the loads are random. Differing from the general finite element theory, the main difficulty which the stochastic finite element method faces is the inverse operation of stochastic operators and stochastic matrices, since the inverse operators and the inverse matrices are statistically correlated to the random parameters and random loads. So far, many efforts have been made to obtain the reasonably approximate expressions of the inverse operators and inverse matrices, such as Perturbation Method, Neumann Expansion Method, Galerkin Method (in appropriate Hilbert Spaces defined for random functions), Orthogonal Expansion Method. Among these methods, Perturbation Method appear to be the most available. The advantage of these methods is that the fairly accurate response statistics can be obtained under the condition of the finite information of the input. However, the second-order statistics obtained by use of Perturbation Method and Neumann Expansion Method are not always the appropriate ones, because the relevant second

Application of Stochastic Partial Differential Equations to Reservoir Property Modelling

KAUST Repository

Potsepaev, R.

2010-09-06

Existing algorithms of geostatistics for stochastic modelling of reservoir parameters require a mapping (the \\'uvt-transform\\') into the parametric space and reconstruction of a stratigraphic co-ordinate system. The parametric space can be considered to represent a pre-deformed and pre-faulted depositional environment. Existing approximations of this mapping in many cases cause significant distortions to the correlation distances. In this work we propose a coordinate free approach for modelling stochastic textures through the application of stochastic partial differential equations. By avoiding the construction of a uvt-transform and stratigraphic coordinates, one can generate realizations directly in the physical space in the presence of deformations and faults. In particular the solution of the modified Helmholtz equation driven by Gaussian white noise is a zero mean Gaussian stationary random field with exponential correlation function (in 3-D). This equation can be used to generate realizations in parametric space. In order to sample in physical space we introduce a stochastic elliptic PDE with tensor coefficients, where the tensor is related to correlation anisotropy and its variation is physical space.

The Reality of Economic Growth towards Green Environment: A Study of Selected OECD Countries 1990-2010

Directory of Open Access Journals (Sweden)

Shilpi Gupta

2014-09-01

Full Text Available Economic growth and green environment has a direct relation with health, habitat and well being of our society which depends largely on the natural environment. But on the other side the society is neglecting and often ignoring the benefits that nature provides for economic prosperity. This paper studies the role of environment in economic growth, the role of environmental policy in achieving improved environmental results, closely examine the evidence of decoupling production from environmental damages and discuss decoupling in the context of global economy. In order to study these aspects, we explored our comparative research with special reference to selected eight OECD nations namely-France, Germany, Ireland, Japan, Portugal, Turkey, UK and USA with coverage period of 1990-2010. The selection of the countries is based on their prominence in industrialised world and their close economic bounding with each other over a considerable period. The coverage period in the study is 20 years because some of the emission data are available till 2013 and some only up to 2010. In order to do a comparative research on various dimensions we take in to our study period between1990-2010. DOI: http://dx.doi.org/10.3126/ije.v3i3.11065 International Journal of Environment Vol.3(3 2014: 78-88

Symposium on Pacific Energy Cooperation '99. Changing economic environment and energy cooperation in Asia

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-02-16

Compiled in this publication are the papers delivered at the above conference held in Tokyo on February 16-17, 1999. Presented in Session 1, entitled 'economic reforms and energy situation in Asian countries,' are the causes and lessons of economic and financial crisis in the Asian countries and the prospect of restoration; the outlook of energy supply and demand in the Asia Pacific region; and a message from APEC (Asia-Pacific Economic Cooperation Conference) Okinawa Energy Ministers' Meeting. Discussed in Session 2, entitled 'energy security in the Asia Pacific region,' are the outlook for world oil prices; and the stable supply of oil and gas in the Asia Pacific region. Discussed in Session 3, entitled the 'deregulation of the energy sector in the Asia Pacific region,' are the deregulation of the power sector, progress and problems; and the privatization of the oil and gas sectors. Many papers are presented also in Session 4, entitled the 'energy and environment in the Asia Pacific region, and in Session 5 entitled 'pacific energy cooperation in the changing economic and energy environment.' (NEDO)

SELANSI: a toolbox for simulation of stochastic gene regulatory networks.

Science.gov (United States)

Pájaro, Manuel; Otero-Muras, Irene; Vázquez, Carlos; Alonso, Antonio A

2018-03-01

Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding Chemical Master Equation with a partial integral differential equation that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. SELANSI runs under the MATLAB environment, and is available under GPLv3 license at https://sites.google.com/view/selansi. antonio@iim.csic.es. © The Author(s) 2017. Published by Oxford University Press.

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

Science.gov (United States)

Varga, Katherine Yvonne

2015-01-01

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

Consensus states of local majority rule in stochastic process

Energy Technology Data Exchange (ETDEWEB)

Luo, Yu-Pin [Department of Electronic Engineering, National Formosa University, Huwei, 63201, Taiwan (China); Tang, Chia-Wei; Xu, Hong-Yuan [Department of Physics, Chung-Yuan Christian University, Chungli, 32023, Taiwan (China); Wu, Jinn-Wen [Department of Applied Mathematics, Chung-Yuan Christian University, Chungli, 32023, Taiwan (China); Huang, Ming-Chang, E-mail: mchuang@cycu.edu.tw [Center for Theoretical Science and Department of Physics, Chung-Yuan Christian University, Chungli, 32023, Taiwan (China)

2015-04-03

A sufficient condition for a network system to reach a consensus state of the local majority rule is shown. The influence of interpersonal environment on the occurrence probability of consensus states for Watts–Strogatz and scale-free networks with random initial states is analyzed by numerical method. We also propose a stochastic local majority rule to study the mean first passage time from a random state to a consensus and the escape rate from a consensus state for systems in a noisy environment. Our numerical results show that there exists a window of fluctuation strengths for which the mean first passage time from a random to a consensus state reduces greatly, and the escape rate of consensus states obeys the Arrhenius equation in the window. - Highlights: • A sufficient condition for reaching a consensus. • The relation between the geometry of networks and the reachability of a consensus. • Stochastic local majority rule. • The mean first-passage time and the escape rate of consensus states.

Consensus states of local majority rule in stochastic process

International Nuclear Information System (INIS)

Luo, Yu-Pin; Tang, Chia-Wei; Xu, Hong-Yuan; Wu, Jinn-Wen; Huang, Ming-Chang

2015-01-01

A sufficient condition for a network system to reach a consensus state of the local majority rule is shown. The influence of interpersonal environment on the occurrence probability of consensus states for Watts–Strogatz and scale-free networks with random initial states is analyzed by numerical method. We also propose a stochastic local majority rule to study the mean first passage time from a random state to a consensus and the escape rate from a consensus state for systems in a noisy environment. Our numerical results show that there exists a window of fluctuation strengths for which the mean first passage time from a random to a consensus state reduces greatly, and the escape rate of consensus states obeys the Arrhenius equation in the window. - Highlights: • A sufficient condition for reaching a consensus. • The relation between the geometry of networks and the reachability of a consensus. • Stochastic local majority rule. • The mean first-passage time and the escape rate of consensus states

Effects of regulation and economic environment on the electricity industry's competitiveness: A study based on OECD countries

International Nuclear Information System (INIS)

Baek, Chulwoo; Jung, Euy-Young; Lee, Jeong-Dong

2014-01-01

We propose a competitiveness index for the electricity industry based on efficiency, stability, and growth factors identified from previous studies subject to data accessibility. These are then weighted appropriately through the application of the analytical hierarchy process. This index is an alternative tool to capture the diverse characteristics of the electricity industry in order to analyze performance after deregulation. Using the competitiveness index, we analyze the effect of regulation change in specific economic environments represented by the level of economic development, energy intensity, and manufacturing share, for example. According to the results, deregulation generally increases competitiveness, but the effect depends on the economic environment and the type of regulation. Deregulating entry and vertical integration to increase competitiveness is more effective in countries where the level of economic development, energy intensity, and manufacturing share are low. The manner in which the privatization effect is related to the economic environment is, however, unclear. - Highlights: • This study proposes a competitiveness index for the electricity industry. • It examines the effects of electricity industry deregulation in OECD countries. • It suggests an economic environment in which deregulation can contribute to competitiveness

The threshold of a stochastic avian-human influenza epidemic model with psychological effect

Science.gov (United States)

Zhang, Fengrong; Zhang, Xinhong

2018-02-01

In this paper, a stochastic avian-human influenza epidemic model with psychological effect in human population and saturation effect within avian population is investigated. This model describes the transmission of avian influenza among avian population and human population in random environments. For stochastic avian-only system, persistence in the mean and extinction of the infected avian population are studied. For the avian-human influenza epidemic system, sufficient conditions for the existence of an ergodic stationary distribution are obtained. Furthermore, a threshold of this stochastic model which determines the outcome of the disease is obtained. Finally, numerical simulations are given to support the theoretical results.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Stochastic abstract policies: generalizing knowledge to improve reinforcement learning.

Science.gov (United States)

Koga, Marcelo L; Freire, Valdinei; Costa, Anna H R

2015-01-01

Reinforcement learning (RL) enables an agent to learn behavior by acquiring experience through trial-and-error interactions with a dynamic environment. However, knowledge is usually built from scratch and learning to behave may take a long time. Here, we improve the learning performance by leveraging prior knowledge; that is, the learner shows proper behavior from the beginning of a target task, using the knowledge from a set of known, previously solved, source tasks. In this paper, we argue that building stochastic abstract policies that generalize over past experiences is an effective way to provide such improvement and this generalization outperforms the current practice of using a library of policies. We achieve that contributing with a new algorithm, AbsProb-PI-multiple and a framework for transferring knowledge represented as a stochastic abstract policy in new RL tasks. Stochastic abstract policies offer an effective way to encode knowledge because the abstraction they provide not only generalizes solutions but also facilitates extracting the similarities among tasks. We perform experiments in a robotic navigation environment and analyze the agent's behavior throughout the learning process and also assess the transfer ratio for different amounts of source tasks. We compare our method with the transfer of a library of policies, and experiments show that the use of a generalized policy produces better results by more effectively guiding the agent when learning a target task.

Stochastic Methods Applied to Power System Operations with Renewable Energy: A Review

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z. [Argonne National Lab. (ANL), Argonne, IL (United States); Liu, C. [Argonne National Lab. (ANL), Argonne, IL (United States); Electric Reliability Council of Texas (ERCOT), Austin, TX (United States); Botterud, A. [Argonne National Lab. (ANL), Argonne, IL (United States)

2016-08-01

Renewable energy resources have been rapidly integrated into power systems in many parts of the world, contributing to a cleaner and more sustainable supply of electricity. Wind and solar resources also introduce new challenges for system operations and planning in terms of economics and reliability because of their variability and uncertainty. Operational strategies based on stochastic optimization have been developed recently to address these challenges. In general terms, these stochastic strategies either embed uncertainties into the scheduling formulations (e.g., the unit commitment [UC] problem) in probabilistic forms or develop more appropriate operating reserve strategies to take advantage of advanced forecasting techniques. Other approaches to address uncertainty are also proposed, where operational feasibility is ensured within an uncertainty set of forecasting intervals. In this report, a comprehensive review is conducted to present the state of the art through Spring 2015 in the area of stochastic methods applied to power system operations with high penetration of renewable energy. Chapters 1 and 2 give a brief introduction and overview of power system and electricity market operations, as well as the impact of renewable energy and how this impact is typically considered in modeling tools. Chapter 3 reviews relevant literature on operating reserves and specifically probabilistic methods to estimate the need for system reserve requirements. Chapter 4 looks at stochastic programming formulations of the UC and economic dispatch (ED) problems, highlighting benefits reported in the literature as well as recent industry developments. Chapter 5 briefly introduces alternative formulations of UC under uncertainty, such as robust, chance-constrained, and interval programming. Finally, in Chapter 6, we conclude with the main observations from our review and important directions for future work.

Stochastic neuron models

CERN Document Server

Greenwood, Priscilla E

2016-01-01

This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

Pricing real estate index options under stochastic interest rates

Science.gov (United States)

Gong, Pu; Dai, Jun

2017-08-01

Real estate derivatives as new financial instruments are not merely risk management tools but also provide a novel way to gain exposure to real estate assets without buying or selling the physical assets. Although real estate derivatives market has exhibited a rapid development in recent years, the valuation challenge of real estate derivatives remains a great obstacle for further development in this market. In this paper, we derive a partial differential equation contingent on a real estate index in a stochastic interest rate environment and propose a modified finite difference method that adopts the non-uniform grids to solve this problem. Numerical results confirm the efficiency of the method and indicate that constant interest rate models lead to the mispricing of options and the effects of stochastic interest rates on option prices depend on whether the term structure of interest rates is rising or falling. Finally, we have investigated and compared the different effects of stochastic interest rates on European and American option prices.

Climate Change and Integrodifference Equations in a Stochastic Environment.

Science.gov (United States)

Bouhours, Juliette; Lewis, Mark A

2016-09-01

Climate change impacts population distributions, forcing some species to migrate poleward if they are to survive and keep up with the suitable habitat that is shifting with the temperature isoclines. Previous studies have analysed whether populations have the capacity to keep up with shifting temperature isoclines, and have mathematically determined the combination of growth and dispersal that is needed to achieve this. However, the rate of isocline movement can be highly variable, with much uncertainty associated with yearly shifts. The same is true for population growth rates. Growth rates can be variable and uncertain, even within suitable habitats for growth. In this paper, we reanalyse the question of population persistence in the context of the uncertainty and variability in isocline shifts and rates of growth. Specifically, we employ a stochastic integrodifference equation model on a patch of suitable habitat that shifts poleward at a random rate. We derive a metric describing the asymptotic growth rate of the linearised operator of the stochastic model. This metric yields a threshold criterion for population persistence. We demonstrate that the variability in the yearly shift and in the growth rate has a significant negative effect on the persistence in the sense that it decreases the threshold criterion for population persistence. Mathematically, we show how the persistence metric can be connected to the principal eigenvalue problem for a related integral operator, at least for the case where isocline shifting speed is deterministic. Analysis of dynamics for the case where the dispersal kernel is Gaussian leads to the existence of a critical shifting speed, above which the population will go extinct, and below which the population will persist. This leads to clear bounds on rate of environmental change if the population is to persist. Finally, we illustrate our different results for butterfly population using numerical simulations and demonstrate how

Stochastic tools in turbulence

CERN Document Server

Lumey, John L

2012-01-01

Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the

Optimal Stochastic Control Problem for General Linear Dynamical Systems in Neuroscience

Directory of Open Access Journals (Sweden)

Yan Chen

2017-01-01

Full Text Available This paper considers a d-dimensional stochastic optimization problem in neuroscience. Suppose the arm’s movement trajectory is modeled by high-order linear stochastic differential dynamic system in d-dimensional space, the optimal trajectory, velocity, and variance are explicitly obtained by using stochastic control method, which allows us to analytically establish exact relationships between various quantities. Moreover, the optimal trajectory is almost a straight line for a reaching movement; the optimal velocity bell-shaped and the optimal variance are consistent with the experimental Fitts law; that is, the longer the time of a reaching movement, the higher the accuracy of arriving at the target position, and the results can be directly applied to designing a reaching movement performed by a robotic arm in a more general environment.

Stochastic resonance and noise delayed extinction in a model of two competing species

Science.gov (United States)

Valenti, D.; Fiasconaro, A.; Spagnolo, B.

2004-01-01

We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species as a function of the additive noise intensity.

Public economics and the environment in an imperfect world

International Nuclear Information System (INIS)

Bovenberg, L.; Cnossen, S.

1995-01-01

Growing populations and economies have increased the public's awareness that the world's environment resources are finite. The issues of global warming and depletion of the ozone layer have given universal significance to what were once local and regional pollution problems. In this book the interface between public economics and environmental economics is examined. It is evident that Coasian negotiations fail to internalize the costs of environmental degradation often calling for public intervention through the market mechanism. In this book those issues are considered and contributions on assessment problems, institutional aspects, the need for coordination and efficiency and distribution issues are included. The papers in this volume were selected from 64 papers, presented at the 50th IIPF (International Institute of Public Finance) congress. 15 contributions are grouped under the headings Introduction (Part 1), An Imperfect World (Part 2), Assessment Problems (Part 3), Institutional Aspects (Part 4), The Need for Coordination (Part 5), and Efficiency and Distribution Issues (Part 6). 25 figs., 39 tabs., 380 refs

[Coupling coordination evaluation method between eco-environment quality and economic development level in contiguous special poverty-stricken areas of China].

Science.gov (United States)

Wang, Yan-hui; Li, Jing-yi

2015-05-01

It is one of the important strategies in the new period of national poverty alleviation and development to maintain the basic balance between the ecological environment and economic development, and to promote the coordinated sustainable development of economy and ecological environment. Taking six contiguous special poverty-stricken areas as the study areas, a coupling coordination evaluation method between eco-environment quality and economic development level in contiguous special poverty-stricken areas was explored in this paper. The region' s ecological poverty index system was proposed based on the natural attribute of ecological environment, and the ecological environment quality evaluation method was built up by using AHP weighting method, followed by the design of the coupling coordination evaluation method between the ecological environment indices and the county economic poverty comprehensive indices. The coupling coordination degrees were calculated and their spatial representation differentiations were analyzed respectively at district, province, city, and county scales. Results showed that approximately half of the counties in the study areas achieved the harmoniously coordinated development. However, the ecological environmental quality and the economic development in most counties could not be synchronized, where mountains, rivers and other geographic features existed roughly as a dividing line of the coordinated development types. The phenomena of dislocation between the ecological environment and economic development in state-level poor counties were more serious than those of local poor counties.

Evaluating Kuala Lumpur stock exchange oriented bank performance with stochastic frontiers

International Nuclear Information System (INIS)

Baten, M. A.; Maznah, M. K.; Razamin, R.; Jastini, M. J.

2014-01-01

Banks play an essential role in the economic development and banks need to be efficient; otherwise, they may create blockage in the process of development in any country. The efficiency of banks in Malaysia is important and should receive greater attention. This study formulated an appropriate stochastic frontier model to investigate the efficiency of banks which are traded on Kuala Lumpur Stock Exchange (KLSE) market during the period 2005–2009. All data were analyzed to obtain the maximum likelihood method to estimate the parameters of stochastic production. Unlike the earlier studies which use balance sheet and income statements data, this study used market data as the input and output variables. It was observed that banks listed in KLSE exhibited a commendable overall efficiency level of 96.2% during 2005–2009 hence suggesting minimal input waste of 3.8%. Among the banks, the COMS (Cimb Group Holdings) bank is found to be highly efficient with a score of 0.9715 and BIMB (Bimb Holdings) bank is noted to have the lowest efficiency with a score of 0.9582. The results also show that Cobb-Douglas stochastic frontier model with truncated normal distributional assumption is preferable than Translog stochastic frontier model

Evaluating Kuala Lumpur stock exchange oriented bank performance with stochastic frontiers

Energy Technology Data Exchange (ETDEWEB)

Baten, M. A.; Maznah, M. K.; Razamin, R.; Jastini, M. J. [School of Quantitative Sciences, Universiti Utara Malaysia 06010, Sintok, Kedah (Malaysia)

2014-12-04

Banks play an essential role in the economic development and banks need to be efficient; otherwise, they may create blockage in the process of development in any country. The efficiency of banks in Malaysia is important and should receive greater attention. This study formulated an appropriate stochastic frontier model to investigate the efficiency of banks which are traded on Kuala Lumpur Stock Exchange (KLSE) market during the period 2005–2009. All data were analyzed to obtain the maximum likelihood method to estimate the parameters of stochastic production. Unlike the earlier studies which use balance sheet and income statements data, this study used market data as the input and output variables. It was observed that banks listed in KLSE exhibited a commendable overall efficiency level of 96.2% during 2005–2009 hence suggesting minimal input waste of 3.8%. Among the banks, the COMS (Cimb Group Holdings) bank is found to be highly efficient with a score of 0.9715 and BIMB (Bimb Holdings) bank is noted to have the lowest efficiency with a score of 0.9582. The results also show that Cobb-Douglas stochastic frontier model with truncated normal distributional assumption is preferable than Translog stochastic frontier model.

On the size distribution of cities: an economic interpretation of the Pareto coefficient.

Science.gov (United States)

Suh, S H

1987-01-01

"Both the hierarchy and the stochastic models of size distribution of cities are analyzed in order to explain the Pareto coefficient by economic variables. In hierarchy models, it is found that the rate of variation in the productivity of cities and that in the probability of emergence of cities can explain the Pareto coefficient. In stochastic models, the productivity of cities is found to explain the Pareto coefficient. New city-size distribution functions, in which the Pareto coefficient is decomposed by economic variables, are estimated." excerpt

Comparison of the Valuations of Alternatives Based on Cumulative Prospect Theory and Almost Stochastic Dominance

Directory of Open Access Journals (Sweden)

Ewa Michalska

2012-01-01

Full Text Available There are commonly accepted and objective decision rules, which are consistent with rationality, for example stochastic dominance rules. But, as can be seen in many research studies in behavioral economics, decision makers do not always act rationally. Rules based on cumulative prospect theory or almost stochastic dominance are relatively new tools which model real choices. Both approaches take into account some behavioral factors. The aim of this paper is to check the consistency of orders of the valuations of random alternatives based on these behavioral rules. The order of the alternatives is generated by a preference relation over the decision set. In this paper, we show that the methodology for creating rankings based on total orders can be used for the preference relations considered, because they enable comparison of all the elements in a set of random alternatives. For almost second degree stochastic dominance, this is possible due to its particular properties, which stochastic dominance does not possess. (original abstract

Stochastic feeding dynamics arise from the need for information and energy.

Science.gov (United States)

Scholz, Monika; Dinner, Aaron R; Levine, Erel; Biron, David

2017-08-29

Animals regulate their food intake in response to the available level of food. Recent observations of feeding dynamics in small animals showed feeding patterns of bursts and pauses, but their function is unknown. Here, we present a data-driven decision-theoretical model of feeding in Caenorhabditis elegans Our central assumption is that food intake serves a dual purpose: to gather information about the external food level and to ingest food when the conditions are good. The model recapitulates experimentally observed feeding patterns. It naturally implements trade-offs between speed versus accuracy and exploration versus exploitation in responding to a dynamic environment. We find that the model predicts three distinct regimes in responding to a dynamical environment, with a transition region where animals respond stochastically to periodic signals. This stochastic response accounts for previously unexplained experimental data.

Can a stochastic cusp catastrophe model explain stock market crashes?

Czech Academy of Sciences Publication Activity Database

Baruník, Jozef; Vošvrda, Miloslav

2009-01-01

Roč. 33, č. 10 (2009), s. 1824-1836 ISSN 0165-1889 R&D Projects: GA ČR GD402/09/H045; GA ČR GA402/09/0965 Grant - others:GAUK(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : Stochastic cusp catastrophe * Bifurcations * Singularity * Nonlinear dynamics * Stock market crash Subject RIV: AH - Economics Impact factor: 1.097, year: 2009

Stochastic ground-water flow analysis FY-81 status report. Assessment of effectiveness of geologic isolation systems

International Nuclear Information System (INIS)

Kincaid, C.T.; Vail, L.W.; Devary, J.L.

1983-07-01

Research was conducted at Pacific Northwest Laboratory to develop a research computational package for the stochastic analysis of ground-water flow. Both unsteady and steady-state analysis were examined, and a steady-state research code was developed for the study of stochastic processes. This report describes the theoretical development of both unsteady and steady analyses, and presents the preliminary studies undertaken to verify and exercise the encoded algorithm. The stochastic analysis of ground-water flow is a promising new method which can supply more comprehensive analyses of the ground-water environment. The work reported herein provided experience in the methodology while producing a research-oriented stochastic analysis capability. Single-layer aquifers of horizontal extent were selected for this effort. Kriging has been employed to describe the uncertainty in field data. The resulting stochastic parameters enter the problem physics through boundary conditions and Darcy's equation. The mean and variance of the piezometric head are estimated by the stochastic analysis

Stochastic modelling to evaluate the economic efficiency of treatment of chronic subclinical mastitis

OpenAIRE

Steeneveld, W.; Hogeveen, H.; Borne, van den, B.H.P.; Swinkels, J.M.

2006-01-01

Treatment of subclinical mastitis is traditionally no common practice. However, some veterinarians regard treatment of some types of subclinical mastitis to be effective. The goal of this research was to develop a stochastic Monte Carlo simulation model to support decisions around treatment of chronic subclinical mastitis caused by Streptococcus uberis. Factors in the model include, amongst others, the probability of spontaneous cure, probability of the cow becoming clinically diseased, trans...

On the Stochastic Properties of Carbon Futures Prices

International Nuclear Information System (INIS)

Chevallier, Julien; Sevi, Benoit

2012-10-01

Pricing carbon is a central concern in environmental economics, due to the importance of emissions trading schemes worldwide to regulate pollution. This paper documents the presence of small and large jumps in the stochastic process of the CO 2 futures price. The large jumps have a discrete origin, i.e. they can arise from various demand factors or institutional decisions on the tradable permits market. Contrary to the previously established literature, we show that the stochastic process of the carbon futures prices does not contain a continuous component (Brownian motion). The results are derived by using high-frequency data in the activity signature function framework (Todorov and Tauchen (2010, 2011)). The implication is that the carbon futures price should be rather modelled as an appropriately sampled, centered Levy or Poisson process. The pure-jump behavior of the carbon price could be explained by the lower volume of trades on this allowance market (compared to other highly liquid financial markets). (authors)

Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods

Directory of Open Access Journals (Sweden)

Huiru Zhao

2016-01-01

Full Text Available As an efficient way to deal with the global climate change and energy shortage problems, a strong, self-healing, compatible, economic and integrative smart gird is under construction in China, which is supported by large amounts of investments and advanced technologies. To promote the construction, operation and sustainable development of Strong Smart Grid (SSG, a novel hybrid framework for evaluating the performance of SSG is proposed from the perspective of sustainability. Based on a literature review, experts’ opinions and the technical characteristics of SSG, the evaluation model involves four sustainability criteria defined as economy, society, environment and technology aspects associated with 12 sub-criteria. Considering the ambiguity and vagueness of the subjective judgments on sub-criteria, fuzzy TOPSIS method is employed to evaluate the performance of SSG. In addition, different from previous research, this paper adopts the stochastic Analytical Hierarchy Process (AHP method to upgrade the traditional Technique for Order Preference by Similarity to Ideal Solution (TOPSIS by addressing the fuzzy and stochastic factors within weights calculation. Finally, four regional smart grids in China are ranked by employing the proposed framework. The results show that the sub-criteria affiliated with environment obtain much more attention than that of economy from experts group. Moreover, the sensitivity analysis indicates the ranking list remains stable no matter how sub-criteria weights are changed, which verifies the robustness and effectiveness of the proposed model and evaluation results. This study provides a comprehensive and effective method for performance evaluation of SSG and also innovates the weights calculation for traditional TOPSIS.

Assessment of the Impact of Stochastic Day-Ahead SCUC on Economic and Reliability Metrics at Multiple Timescales: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wu, H.; Ela, E.; Krad, I.; Florita, A.; Zhang, J.; Hodge, B. M.; Ibanez, E.; Gao, W.

2015-03-01

This paper incorporates the stochastic day-ahead security-constrained unit commitment (DASCUC) within a multi-timescale, multi-scheduling application with commitment, dispatch, and automatic generation control. The stochastic DASCUC is solved using a progressive hedging algorithm with constrained ordinal optimization to accelerate the individual scenario solution. Sensitivity studies are performed in the RTS-96 system, and the results show how this new scheduling application would impact costs and reliability with a closer representation of timescales of system operations in practice.

Scheduling stochastic two-machine flow shop problems to minimize expected makespan

Directory of Open Access Journals (Sweden)

Mehdi Heydari

2013-07-01

Full Text Available During the past few years, despite tremendous contribution on deterministic flow shop problem, there are only limited number of works dedicated on stochastic cases. This paper examines stochastic scheduling problems in two-machine flow shop environment for expected makespan minimization where processing times of jobs are normally distributed. Since jobs have stochastic processing times, to minimize the expected makespan, the expected sum of the second machine’s free times is minimized. In other words, by minimization waiting times for the second machine, it is possible to reach the minimum of the objective function. A mathematical method is proposed which utilizes the properties of the normal distributions. Furthermore, this method can be used as a heuristic method for other distributions, as long as the means and variances are available. The performance of the proposed method is explored using some numerical examples.

Numerical modeling of economic uncertainty

DEFF Research Database (Denmark)

Schjær-Jacobsen, Hans

2007-01-01

Representation and modeling of economic uncertainty is addressed by different modeling methods, namely stochastic variables and probabilities, interval analysis, and fuzzy numbers, in particular triple estimates. Focusing on discounted cash flow analysis numerical results are presented, comparisons...... are made between alternative modeling methods, and characteristics of the methods are discussed....

Sequential stochastic optimization

CERN Document Server

Cairoli, Renzo

1996-01-01

Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet

Transformation of the Terminological Apparatus of Economic Development of Innovation Activity under Conditions of Dynamic Changes in the External Environment

Directory of Open Access Journals (Sweden)

Sharko Margarita V.

2017-12-01

Full Text Available The aim of the article is to analyze the content interpretation of categorical concepts of economic development of production functioning under conditions of dynamic changes in the exploitation of the external environment. The article presents the author’s interpretation of the concepts of economic development and economic growth under conditions of dynamic changes in the external environment. The urgency of unification and systematization of the main interpretations of economic growth as a means of choosing and using certain management solutions under specific production conditions is substantiated. Based on the construction of the Ishikawa diagram, the reasons and difficulties of the economic growth of enterprises are graded. The conditions and factors of the conceptual apparatus of innovation activity under uncertainty are structured. It is shown that the complex application of iterative methods and methods of factor analysis provides a holistic perception of the dominant tendencies of economic development under conditions of dynamic changes in the external environment.

Volatility Degree Forecasting of Stock Market by Stochastic Time Strength Neural Network

Directory of Open Access Journals (Sweden)

Haiyan Mo

2013-01-01

Full Text Available In view of the applications of artificial neural networks in economic and financial forecasting, a stochastic time strength function is introduced in the backpropagation neural network model to predict the fluctuations of stock price changes. In this model, stochastic time strength function gives a weight for each historical datum and makes the model have the effect of random movement, and then we investigate and forecast the behavior of volatility degrees of returns for the Chinese stock market indexes and some global market indexes. The empirical research is performed in testing the prediction effect of SSE, SZSE, HSI, DJIA, IXIC, and S&P 500 with different selected volatility degrees in the established model.

Some variance reduction methods for numerical stochastic homogenization.

Science.gov (United States)

Blanc, X; Le Bris, C; Legoll, F

2016-04-28

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte

2010-01-01

This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...

The contribution of childhood environment to the explanation of socio-economic inequalities in health in adult life: A retrospective study

NARCIS (Netherlands)

van de Mheen, H.; Stronks, K.; van den Bos, J.; Mackenbach, J. P.

1997-01-01

In this study the contribution of childhood environment to the explanation of socio-economic inequalities in health in adulthood is examined. Childhood environment was measured using indicators of social, socio-economic and material aspects. Retrospective data obtained from an oral interview, part

Singular stochastic differential equations

CERN Document Server

Cherny, Alexander S

2005-01-01

The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.

Economics and the environment

International Nuclear Information System (INIS)

Alm, A.L.

1991-01-01

There is no reason to believe that strict environmental controls are inconsistent with economic well-being and competitiveness. In fact, firms in nations with tough standards have a competitive edge. They have already made some of the capital investments, are finding ways to eliminate wastes, and are developing exportable technologies and skills. The economic argument in the US should not be focused on how pollution control affects the domestic economy. It should be focused on how we can create a framework for technological innovation to solve problems more efficiently and effectively and then to actively propel this innovation into global markets

Adaptive control of chaotic systems with stochastic time varying unknown parameters

Energy Technology Data Exchange (ETDEWEB)

Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

2008-10-15

In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

Modeling Uncertainty and the Economics of Climate Change. Recommendations for Robust Energy Policy

International Nuclear Information System (INIS)

Haurie, A.; Tavoni, M.; Van der Zwaan, B.C.C.

2011-01-01

This special issue is meant to gather front-edge research and innovative analysis in the modeling of uncertainty related to the economics of climate change. The focus is notably on advancements in probabilistic integrated assessment modeling and stochastic analysis of climate futures. The possibility to use non-probabilistic economic methods to treat uncertainty in global or regional dynamic climate change models is explored as well. Given the intimate link between climate change and the nature of mankind's energy production and consumption system, this special issue also proffers direct practical recommendations for energy decision making at the global, regional, and national levels. The special issue originated from a series of research tasks carried out under the PLANETS project, funded by the European Commission under its 7th Framework Programme and co-coordinated by the Fondazione Eni Enrico Mattei (FEEM) and the Energy research Centre of the Netherlands (ECN). This project, accomplished in 2010, had, as main focus, how to incorporate uncertainty when carrying out numerical analysis of climate and energy policies. A special PLANETS session was organized during the 2010 edition of the International Energy Workshop (IEW 2010, Royal Institute of Technology, Stockholm), which generated broad expert discussion on both methodology and policy-related issues. The recognition of the importance of these topics and the diversity of approaches undertaken, plus a concern over them becoming fragmented in the literature, constituted the motivation to edit this special issue gathering the generated material in one orchestrated publication. Several contributions, in the form of 12 papers, have been brought together with the aim of providing a comprehensive overview of some of the main recent developments in the modeling of uncertainty in the economics of climate change. We categorize these 12 articles in five distinct domains in hybrid integrated assessment EEE (Energy-Environment

Modeling Uncertainty and the Economics of Climate Change. Recommendations for Robust Energy Policy

Energy Technology Data Exchange (ETDEWEB)

Haurie, A. [ORDECSYS, Geneva (Switzerland); Tavoni, M. [Princeton University, Princeton, NJ (United States); Van der Zwaan, B.C.C. [Policy Studies Department, Energy research Centre of the Netherlands ECN, Amsterdam (Netherlands)

2011-07-15

This special issue is meant to gather front-edge research and innovative analysis in the modeling of uncertainty related to the economics of climate change. The focus is notably on advancements in probabilistic integrated assessment modeling and stochastic analysis of climate futures. The possibility to use non-probabilistic economic methods to treat uncertainty in global or regional dynamic climate change models is explored as well. Given the intimate link between climate change and the nature of mankind's energy production and consumption system, this special issue also proffers direct practical recommendations for energy decision making at the global, regional, and national levels. The special issue originated from a series of research tasks carried out under the PLANETS project, funded by the European Commission under its 7th Framework Programme and co-coordinated by the Fondazione Eni Enrico Mattei (FEEM) and the Energy research Centre of the Netherlands (ECN). This project, accomplished in 2010, had, as main focus, how to incorporate uncertainty when carrying out numerical analysis of climate and energy policies. A special PLANETS session was organized during the 2010 edition of the International Energy Workshop (IEW 2010, Royal Institute of Technology, Stockholm), which generated broad expert discussion on both methodology and policy-related issues. The recognition of the importance of these topics and the diversity of approaches undertaken, plus a concern over them becoming fragmented in the literature, constituted the motivation to edit this special issue gathering the generated material in one orchestrated publication. Several contributions, in the form of 12 papers, have been brought together with the aim of providing a comprehensive overview of some of the main recent developments in the modeling of uncertainty in the economics of climate change. We categorize these 12 articles in five distinct domains in hybrid integrated assessment EEE (Energy-Environment

Control strategies for a stochastic model of host-parasite interaction in a seasonal environment.

Science.gov (United States)

Gómez-Corral, A; López García, M

2014-08-07

We examine a nonlinear stochastic model for the parasite load of a single host over a predetermined time interval. We use nonhomogeneous Poisson processes to model the acquisition of parasites, the parasite-induced host mortality, the natural (no parasite-induced) host mortality, and the reproduction and death of parasites within the host. Algebraic results are first obtained on the age-dependent distribution of the number of parasites infesting the host at an arbitrary time t. The interest is in control strategies based on isolation of the host and the use of an anthelmintic at a certain intervention instant t0. This means that the host is free living in a seasonal environment, and it is transferred to a uninfected area at age t0. In the uninfected area, the host does not acquire new parasites, undergoes a treatment to decrease the parasite load, and its natural and parasite-induced mortality are altered. For a suitable selection of t0, we present two control criteria that appropriately balance effectiveness and cost of intervention. Our approach is based on simple probabilistic principles, and it allows us to examine seasonal fluctuations of gastrointestinal nematode burden in growing lambs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Essays on economic development, energy demand, and the environment

Science.gov (United States)

Medlock, Kenneth Barry, III

2000-10-01

The rapid expansion of industry at the outset of economic development and the subsequent growth of the transportation and residential and commercial sectors dictate both the rate at which energy demand increases and the composition of primary fuel sources used to meet secondary requirements. Each of these factors each has an impact on the pollution problems that nations may face. Growth in consumer wealth, however, appears to eventually lead to a shift in priorities. In particular, the importance of the environment begins to take precedent over the acquisition of goods. Accordingly, cleaner energy alternatives are sought out. The approach taken here is to determine the energy profile of an average nation, and apply those results to a model of economic growth. Dematerialization of production and saturation of consumer bundles results in declining rates of growth of energy demand in broadly defined end-use sectors. The effects of technological change in fossil fuel efficiency, fossil fuel recovery, and 'backstop' energy resources on economic growth and the emissions of carbon dioxide are then analyzed. A central planner is assumed to optimize the consumption of goods and services subject to capital and resource constraints. Slight perturbations in the parameters are used to determine their local elasticities with respect to different endogenous variables, and give an indication of the effects of changes in the various assumptions.

Quantum stochastic walks on networks for decision-making.

Science.gov (United States)

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-03-31

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce's response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process' degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.

Quantum stochastic walks on networks for decision-making

Science.gov (United States)

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-03-01

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.

Redesign of a supply network by considering stochastic demand

Directory of Open Access Journals (Sweden)

Juan Camilo Paz

2015-09-01

Full Text Available This paper presents the problem of redesigning a supply network of large scale by considering variability of the demand. The central problematic takes root in determining strategic decisions of closing and adjusting of capacity of some network echelons and the tactical decisions concerning to the distribution channels used for transporting products. We have formulated a deterministic Mixed Integer Linear Programming Model (MILP and a stochastic MILP model (SMILP whose objective functions are the maximization of the EBITDA (Earnings before Interest, Taxes, Depreciation and Amortization. The decisions of Network Design on stochastic model as capacities, number of warehouses in operation, material and product flows between echelons, are determined in a single stage by defining an objective function that penalizes unsatisfied demand and surplus of demand due to demand changes. The solution strategy adopted for the stochastic model is a scheme denominated as Sample Average Approximation (SAA. The model is based on the case of a Colombian company dedicated to production and marketing of foodstuffs and supplies for the bakery industry. The results show that the proposed methodology was a solid reference for decision support regarding to the supply networks redesign by considering the expected economic contribution of products and variability of the demand.

Stochastic Evolution Equations Driven by Fractional Noises

Science.gov (United States)

2016-11-28

paper is to establish the weak convergence, in the topology of the Skorohod space, of the ν-symmetric Riemann sums for functionals of the fractional...stochastic heat equation with fractional-colored noise: existence of the solution. ALEA Lat. Am. J. Probab. Math . Stat. 4 (2008), 57–87. [8] P. Carmona, Y...Hu: Strong disorder implies strong localization for directed polymers in a random environment. ALEA Lat. Am. J. Probab. Math . Stat. 2 (2006), 217

Impact of stochasticity in immigration and reintroduction on colonizing and extirpating populations.

Science.gov (United States)

Rajakaruna, Harshana; Potapov, Alexei; Lewis, Mark

2013-05-01

A thorough quantitative understanding of populations at the edge of extinction is needed to manage both invasive and extirpating populations. Immigration can govern the population dynamics when the population levels are low. It increases the probability of a population establishing (or reestablishing) before going extinct (EBE). However, the rate of immigration can be highly fluctuating. Here, we investigate how the stochasticity in immigration impacts the EBE probability for small populations in variable environments. We use a population model with an Allee effect described by a stochastic differential equation (SDE) and employ the Fokker-Planck diffusion approximation to quantify the EBE probability. We find that, the effect of the stochasticity in immigration on the EBE probability depends on both the intrinsic growth rate (r) and the mean rate of immigration (p). In general, if r is large and positive (e.g. invasive species introduced to favorable habitats), or if p is greater than the rate of population decline due to the demographic Allee effect (e.g., effective stocking of declining populations), then the stochasticity in immigration decreases the EBE probability. If r is large and negative (e.g. endangered populations in unfavorable habitats), or if the rate of decline due to the demographic Allee effect is much greater than p (e.g., weak stocking of declining populations), then the stochasticity in immigration increases the EBE probability. However, the mean time for EBE decreases with the increasing stochasticity in immigration with both positive and negative large r. Thus, results suggest that ecological management of populations involves a tradeoff as to whether to increase or decrease the stochasticity in immigration in order to optimize the desired outcome. Moreover, the control of invasive species spread through stochastic means, for example, by stochastic monitoring and treatment of vectors such as ship-ballast water, may be suitable strategies

Impact of stochasticity in immigration and reintroduction on colonizing and extirpating populations

KAUST Repository

Rajakaruna, Harshana

2013-05-01

A thorough quantitative understanding of populations at the edge of extinction is needed to manage both invasive and extirpating populations. Immigration can govern the population dynamics when the population levels are low. It increases the probability of a population establishing (or reestablishing) before going extinct (EBE). However, the rate of immigration can be highly fluctuating. Here, we investigate how the stochasticity in immigration impacts the EBE probability for small populations in variable environments. We use a population model with an Allee effect described by a stochastic differential equation (SDE) and employ the Fokker-Planck diffusion approximation to quantify the EBE probability.Wefind that, the effect of the stochasticity in immigration on the EBE probability depends on both the intrinsic growth rate (r) and the mean rate of immigration (p). In general, if r is large and positive (e.g. invasive species introduced to favorable habitats), or if p is greater than the rate of population decline due to the demographic Allee effect (e.g., effective stocking of declining populations), then the stochasticity in immigration decreases the EBE probability. If r is large and negative (e.g. endangered populations in unfavorable habitats), or if the rate of decline due to the demographic Allee effect is much greater than p (e.g., weak stocking of declining populations), then the stochasticity in immigration increases the EBE probability. However, the mean time for EBE decreases with the increasing stochasticity in immigration with both positive and negative large r. Thus, results suggest that ecological management of populations involves a tradeoff as to whether to increase or decrease the stochasticity in immigration in order to optimize the desired outcome. Moreover, the control of invasive species spread through stochastic means, for example, by stochastic monitoring and treatment of vectors such as ship-ballast water, may be suitable strategies given

Recent advances in ambit stochastics with a view towards tempo-spatial stochastic volatility/intermittency

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Veraart, Almut

Ambit stochastics is the name for the theory and applications of ambit fields and ambit processes and constitutes a new research area in stochastics for tempo-spatial phenomena. This paper gives an overview of the main findings in ambit stochastics up to date and establishes new results on genera...

Quantitative sociodynamics stochastic methods and models of social interaction processes

CERN Document Server

Helbing, Dirk

1995-01-01

Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioural changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics but they have very often proved their explanatory power in chemistry, biology, economics and the social sciences. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces the most important concepts from nonlinear dynamics (synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches a very fundamental dynamic model is obtained which seems to open new perspectives in the social sciences. It includes many established models as special cases, e.g. the log...

Quantitative Sociodynamics Stochastic Methods and Models of Social Interaction Processes

CERN Document Server

Helbing, Dirk

2010-01-01

This new edition of Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioral changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics and mathematics, but they have very often proven their explanatory power in chemistry, biology, economics and the social sciences as well. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces important concepts from nonlinear dynamics (e.g. synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches, a fundamental dynamic model is obtained, which opens new perspectives in the social sciences. It includes many established models a...

Functional Abstraction of Stochastic Hybrid Systems

NARCIS (Netherlands)

Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.

2006-01-01

The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways

Stochastic quantisation: theme and variation

International Nuclear Information System (INIS)

Klauder, J.R.; Kyoto Univ.

1987-01-01

The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)

STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...

African Journals Online (AJOL)

eobe

STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.

Economic Reforms and Cost Efficiency of Coffee Farmers in Central Kenya: A Stochastic-Translog Approach

NARCIS (Netherlands)

Karanja, A.M.; Kuyvenhoven, A.; Moll, H.A.J.

2007-01-01

Work reported in this paper analyses the cost efficiency levels of small-holder coffee farmers in four districts in Central Province, Kenya. The level of efficiency is analysed using a stochastic cost frontier model based on household cross-sectional data collected in 1999 and 2000. The 200 surveyed

Symposium on Pacific Energy Cooperation '99. Changing economic environment and energy cooperation in Asia

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-02-16

Compiled in this publication are the papers delivered at the above conference held in Tokyo on February 16-17, 1999. Presented in Session 1, entitled 'economic reforms and energy situation in Asian countries,' are the causes and lessons of economic and financial crisis in the Asian countries and the prospect of restoration; the outlook of energy supply and demand in the Asia Pacific region; and a message from APEC (Asia-Pacific Economic Cooperation Conference) Okinawa Energy Ministers' Meeting. Discussed in Session 2, entitled 'energy security in the Asia Pacific region,' are the outlook for world oil prices; and the stable supply of oil and gas in the Asia Pacific region. Discussed in Session 3, entitled the 'deregulation of the energy sector in the Asia Pacific region,' are the deregulation of the power sector, progress and problems; and the privatization of the oil and gas sectors. Many papers are presented also in Session 4, entitled the 'energy and environment in the Asia Pacific region, and in Session 5 entitled 'pacific energy cooperation in the changing economic and energy environment.' (NEDO)

Stochastic quantization and gravity

International Nuclear Information System (INIS)

Rumpf, H.

1984-01-01

We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)

Stochastic climate theory

NARCIS (Netherlands)

Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.

2017-01-01

In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of

Stochastic modeling of reinforced concrete structures exposed to chloride attack

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Frier, Christian

2004-01-01

For many reinforced concrete structures corrosion of reinforcement is an important problem since it can result in expensive maintenance and repair actions. Further, a significant reduction of the load-bearing capacity can occur. One mode of corrosion initiation is that the chloride content around...... concentration and reinforcement cover depth are modeled by stochastic fields. The paper contains a description of the parameters to be included in a stochastic model and a proposal for the information needed to obtain values for the parameters in order to be able to perform reliability investigations....... The distribution of the time to initiation of corrosion is estimated by simulation. As an example a bridge pier in a marine environment is considered....

Stochastic Modeling of Reinforced Concrete Structures Exposed to Chloride Attack

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Frier, Christian

2003-01-01

For many reinforced concrete structures corrosion of reinforcement is an important problem since it can result in expensive maintenance and repair actions. Further, a significant reduction of the load-bearing capacity can occur. One mode of corrosion initiation is that the chloride content around...... concentration and reinforcement cover depth are modeled by stochastic fields. The paper contains a description of the parameters to be included in a stochastic model and a proposal for the information needed to obtain values for the parameters in order to be ab le to perform reliability investigations....... The distribution of the time to initiation of corrosion is estimated by simulation. As an example a bridge pier in a marine environment is considered....

A stochastic dynamic model of a dairy farm to evaluate the technical and economic performance under different scenarios.

Science.gov (United States)

Calsamiglia, S; Astiz, S; Baucells, J; Castillejos, L

2018-05-23

Dairy farms need to improve their competitiveness through decisions that are often difficult to evaluate because they are highly dependent on many economic and technical factors. The objective of this project was to develop a stochastic and dynamic mathematical model to simulate the functioning of a dairy farm to evaluate the effect of changes in technical or economic factors on performance and profitability. Submodels were developed for reproduction, feeding, diseases, heifers, environmental factors, facilities, management, and economics. All these submodels were simulated on an animal-by-animal and day-by-day basis. Default values for all variables are provided, but the user can change them. The outcome provides a list of technical and economic indicators essential for the decision-making process. Performance of the program was verified by evaluating the effects and sensitivity analysis of different scenarios in 20 different dairy farms. As an example, a case study of a dairy farm with 300 cows producing 40 L/d and a 12% pregnancy rate (PR) was used. The effect of using a time-fixed artificial insemination (TFAI) protocol in the first insemination at 77 d in milk, with 45 and 40% conception rates for first-lactation and older cows, respectively, and a cost of €13 was explored. During the 5-yr simulation, the TFAI increased PR (12 to 17%) and milk yield per milking cow (39.8 to 41.2 L/d) and reduced days to first AI (93 to 74), days open (143 to 116), and the proportion of problem cows (24.3 to 15.9%). In the TFAI, cows were dried 30 d earlier, resulting in more dry cows, and a smaller difference in milk yield by present cows (35.5 vs 36.0 L/d for control and TFAI, respectively). A longer productive life (2.56 vs. 2.79 yr) with shorter lactations in TFIA resulted in less first-lactation cows (42 vs 36%), 32 more calvings per year, and, therefore, more cases of postpartum diseases. Total (32.5 to 29.9%) and reproductive (10.5 vs 6.8%) culling rates decreased in

Marketing of Public and Business Affairs Subsystems of Socio-Economic Environment

Directory of Open Access Journals (Sweden)

Adriana Grigorescu

2008-04-01

Full Text Available The Romanian society is crossing one of the most important stages of its transition toward the integration in the European Union started with January 1st, 2007; this will define the final processes bound for the socio-economic reconstruction. Based on the previous experiences, an assumption rose up that, at this moment in the Romanian society there are two systems business and public administration, placed on opposite, antagonistic, unfriendly sides. At the same time, there is the opinion that a proper public and private marketing could be the link between them. The link between these systems should make the relation useful to create and handle the cooperation and cooperation climate in these two environments. The paper aims to present the systems, their characteristics, the opinion about the other, the identified link components, and to propose a solution for the link improvement. A small survey of the members opinions, in both systems, will be the base of the analysis. The first stage is to analyze each environment as an independent system: business system (BSy and public administration system (PASy. We will present the structure, characteristics, interactions with other socio-economic components, etc. The second stage will focus on the role of public and private marketing as tools of feedback reaction of the systems to the general environment dynamics. The marketing behavior is typical for the BSy and its level of marketing knowledge is higher than the poor level of marketing knowledge in PASy lacking the marketing attitude about public services.

2–stage stochastic Runge–Kutta for stochastic delay differential equations

Energy Technology Data Exchange (ETDEWEB)

Rosli, Norhayati; Jusoh Awang, Rahimah [Faculty of Industrial Science and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang (Malaysia); Bahar, Arifah; Yeak, S. H. [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

2015-05-15

This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching

CSIR Research Space (South Africa)

Moodley, D

2016-12-01

Full Text Available This article presents an agent architecture for controlling an autonomous agent in stochastic, noisy environments. The architecture combines the partially observable Markov decision process (POMDP) model with the belief-desire-intention (BDI...

Space-time-modulated stochastic processes

Science.gov (United States)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

RES: Regularized Stochastic BFGS Algorithm

Science.gov (United States)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

Elitism and Stochastic Dominance

OpenAIRE

Bazen, Stephen; Moyes, Patrick

2011-01-01

Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...

Mathematical Optimiation in Economics

CERN Document Server

De Finetti, Bruno

2011-01-01

Preface by B. de Finetti.- G.Th. Guilbaud: Les equilibres dans les modeles economiques.-H.W. Kuhn: Locational problems and mathematical programming.- M. Morishima: The multi-sectoral theory of economic growth.- B. Martos, J. Kornai: Experiments in Hungary with industry-wide and economy wide programming.- A. Prekopa: Probability distribution problems concerning stochastic programming problems.- R. Frisch: General principles and mathematical techniques of macroeconomic programming.

New "Tau-Leap" Strategy for Accelerated Stochastic Simulation.

Science.gov (United States)

Ramkrishna, Doraiswami; Shu, Che-Chi; Tran, Vu

2014-12-10

The "Tau-Leap" strategy for stochastic simulations of chemical reaction systems due to Gillespie and co-workers has had considerable impact on various applications. This strategy is reexamined with Chebyshev's inequality for random variables as it provides a rigorous probabilistic basis for a measured τ-leap thus adding significantly to simulation efficiency. It is also shown that existing strategies for simulation times have no probabilistic assurance that they satisfy the τ-leap criterion while the use of Chebyshev's inequality leads to a specified degree of certainty with which the τ-leap criterion is satisfied. This reduces the loss of sample paths which do not comply with the τ-leap criterion. The performance of the present algorithm is assessed, with respect to one discussed by Cao et al. ( J. Chem. Phys. 2006 , 124 , 044109), a second pertaining to binomial leap (Tian and Burrage J. Chem. Phys. 2004 , 121 , 10356; Chatterjee et al. J. Chem. Phys. 2005 , 122 , 024112; Peng et al. J. Chem. Phys. 2007 , 126 , 224109), and a third regarding the midpoint Poisson leap (Peng et al., 2007; Gillespie J. Chem. Phys. 2001 , 115 , 1716). The performance assessment is made by estimating the error in the histogram measured against that obtained with the so-called stochastic simulation algorithm. It is shown that the current algorithm displays notably less histogram error than its predecessor for a fixed computation time and, conversely, less computation time for a fixed accuracy. This computational advantage is an asset in repetitive calculations essential for modeling stochastic systems. The importance of stochastic simulations is derived from diverse areas of application in physical and biological sciences, process systems, and economics, etc. Computational improvements such as those reported herein are therefore of considerable significance.

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

On Stochastic Dependence

Science.gov (United States)

Meyer, Joerg M.

2018-01-01

The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.

Stochastic massless fields I: Integer spin

International Nuclear Information System (INIS)

Lim, S.C.

1981-04-01

Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)

Stochastic processes inference theory

CERN Document Server

Rao, Malempati M

2014-01-01

This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan

2018-04-08

Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

Quantum stochastics

CERN Document Server

Chang, Mou-Hsiung

2015-01-01

The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...

Stochastic cooling

International Nuclear Information System (INIS)

Bisognano, J.; Leemann, C.

1982-03-01

Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron

Stochastic optimal control, forward-backward stochastic differential equations and the Schroedinger equation

Energy Technology Data Exchange (ETDEWEB)

Paul, Wolfgang; Koeppe, Jeanette [Institut fuer Physik, Martin Luther Universitaet, 06099 Halle (Germany); Grecksch, Wilfried [Institut fuer Mathematik, Martin Luther Universitaet, 06099 Halle (Germany)

2016-07-01

The standard approach to solve a non-relativistic quantum problem is through analytical or numerical solution of the Schroedinger equation. We show a way to go around it. This way is based on the derivation of the Schroedinger equation from conservative diffusion processes and the establishment of (several) stochastic variational principles leading to the Schroedinger equation under the assumption of a kinematics described by Nelson's diffusion processes. Mathematically, the variational principle can be considered as a stochastic optimal control problem linked to the forward-backward stochastic differential equations of Nelson's stochastic mechanics. The Hamilton-Jacobi-Bellmann equation of this control problem is the Schroedinger equation. We present the mathematical background and how to turn it into a numerical scheme for analyzing a quantum system without using the Schroedinger equation and exemplify the approach for a simple 1d problem.

Analysis on the relationship between economic development and water environment pollution in Shandong province

Science.gov (United States)

Liu, Yi; Zhang, Zhengxian

2018-02-01

With the continuous development of the economy of the Shandong Province watershed, a large number of pollutant emission, resulting in water quality of the basin has undergone significant changes. To study the Shandong Province watershed economic development and the relationship between the discharge of pollutants, in this paper, the relationship between economic growth and pollutant emissions in the Shandong Province watershed was established by Shandong Province watershed in 2002-2015 per capita GDP and wastewater, COD, ammonia nitrogen(AN) pollutant emissions. The data were analyzed by software such as SPSS, and the cubic equation model between various pollutants and economic indexes was fitted. To further make the relationship between pollutants and economic development map to study the conventional pollutant emissions and economic development trends. It is found that only the relationship between industrial wastewater discharge and per capita GDP is most coordinated, that is, industrial wastewater emissions with the continuous development of the basin economy, showing a tendency to rise first and then fall. Finally, ultimately based on the results of the study of the water environment and economic development proposals were proposed.

Discrete stochastic charging of aggregate grains

Science.gov (United States)

Matthews, Lorin S.; Shotorban, Babak; Hyde, Truell W.

2018-05-01

Dust particles immersed in a plasma environment become charged through the collection of electrons and ions at random times, causing the dust charge to fluctuate about an equilibrium value. Small grains (with radii less than 1 μm) or grains in a tenuous plasma environment are sensitive to single additions of electrons or ions. Here we present a numerical model that allows examination of discrete stochastic charge fluctuations on the surface of aggregate grains and determines the effect of these fluctuations on the dynamics of grain aggregation. We show that the mean and standard deviation of charge on aggregate grains follow the same trends as those predicted for spheres having an equivalent radius, though aggregates exhibit larger variations from the predicted values. In some plasma environments, these charge fluctuations occur on timescales which are relevant for dynamics of aggregate growth. Coupled dynamics and charging models show that charge fluctuations tend to produce aggregates which are much more linear or filamentary than aggregates formed in an environment where the charge is stationary.

Stochastic Analysis : A Series of Lectures

CERN Document Server

Dozzi, Marco; Flandoli, Franco; Russo, Francesco

2015-01-01

This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...

Paracousti-UQ: A Stochastic 3-D Acoustic Wave Propagation Algorithm.

Energy Technology Data Exchange (ETDEWEB)

Preston, Leiph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

Acoustic full waveform algorithms, such as Paracousti, provide deterministic solutions in complex, 3-D variable environments. In reality, environmental and source characteristics are often only known in a statistical sense. Thus, to fully characterize the expected sound levels within an environment, this uncertainty in environmental and source factors should be incorporated into the acoustic simulations. Performing Monte Carlo (MC) simulations is one method of assessing this uncertainty, but it can quickly become computationally intractable for realistic problems. An alternative method, using the technique of stochastic partial differential equations (SPDE), allows computation of the statistical properties of output signals at a fraction of the computational cost of MC. Paracousti-UQ solves the SPDE system of 3-D acoustic wave propagation equations and provides estimates of the uncertainty of the output simulated wave field (e.g., amplitudes, waveforms) based on estimated probability distributions of the input medium and source parameters. This report describes the derivation of the stochastic partial differential equations, their implementation, and comparison of Paracousti-UQ results with MC simulations using simple models.

Stochastic Analysis with Financial Applications

CERN Document Server

Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi

2011-01-01

Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li

Robust synthetic biology design: stochastic game theory approach.

Science.gov (United States)

Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching

2009-07-15

Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.

Estimation of an Optimal Stimulus Amplitude for Using Vestibular Stochastic Stimulation to Improve Balance Function

Science.gov (United States)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Peters, B.; Cohen, H.;

Problematic aspects of the economic value added measure in environment of the Czech Republic

Directory of Open Access Journals (Sweden)

Michaela Beranová

2010-01-01

Full Text Available The EVA indicator has been constructed in the recent past as a reaction to requirements of the new economic environment. As the EVA indicator has been introduced by Stewart Stern & Co. in the early nineties, past two decades many economists have been discussing the pros and cons of EVA application as well as various adjustments needed to calculate some relevant result. A range of attitudes to the adjustments to accounting data towards economic data exist there. As the indicator of economic value added is considered to be a criterion of company’s real economic performance it is necessary to be very careful at applying encouraged adjustments. In this article, the authors compare and discuss these adjustments advised in order to reach some ideal number. Accounting differences of US GAAP, IFRS and Czech Accounting Standards are taken into consideration.

Course of change in economic and social environment associated with energy. Population, life, industry

Energy Technology Data Exchange (ETDEWEB)

Yoshimatsu, Michio

1988-03-01

As regards long-term forecast of economic and social environment in Japan, STANDARD economic and social vision based on the course of economical growth was adopted in the report of LONG-TERM VISION OF ENERGY INDUSTRY. The average annual economic growth rate is expected to be still a little higher than the average of that of the developed countries, being supported by the industiral activities by industries engaged in frontier science, manufacturing industries engaged in electrical processing and assembling, etc. In the primary and secondary industries, the number of employees may drop down to about one third. Tokyo may become the center of finance and information surpassing New York and London. The people may enjoy a rich, confortable and cultural life. Problems may arise from enhancement of individualism, increase in advanced aged population, acturization of regional differentials, etc. (3 figs, 3 tabs)

Approaches towards airport economic performance measurement

Directory of Open Access Journals (Sweden)

Ivana STRYČEKOVÁ

2011-01-01

Full Text Available The paper aims to assess how economic benchmarking is being used by airports as a means of performance measurement and comparison of major international airports in the world. The study focuses on current benchmarking practices and methods by taking into account different factors according to which it is efficient to benchmark airports performance. As methods are considered mainly data envelopment analysis and stochastic frontier analysis. Apart from them other approaches are discussed by airports to provide economic benchmarking. The main objective of this article is to evaluate the efficiency of the airports and answer some undetermined questions involving economic benchmarking of the airports.

Stochastic Approach to Determine CO2 Hydrate Induction Time in Clay Mineral Suspensions

Science.gov (United States)

Lee, K.; Lee, S.; Lee, W.

2008-12-01

A large number of induction time data for carbon dioxide hydrate formation were obtained from a batch reactor consisting of four independent reaction cells. Using resistance temperature detector(RTD)s and a digital microscope, we successfully monitored the whole process of hydrate formation (i.e., nucleation and crystal growth) and detected the induction time. The experiments were carried out in kaolinite and montmorillonite suspensions at temperatures between 274 and 277 K and pressures ranging from 3.0 to 4.0 MPa. Each set of data was analyzed beforehand whether to be treated by stochastic manner or not. Geochemical factors potentially influencing the hydrate induction time under different experimental conditions were investigated by stochastic analyses. We observed that clay mineral type, pressure, and temperature significantly affect the stochastic behavior of the induction times for CO2 hydrate formation in this study. The hydrate formation kinetics along with stochastic analyses can provide basic understanding for CO2 hydrate storage in deep-sea sediment and geologic formation, securing its stability under the environments.

Stochastic Reachability Analysis of Hybrid Systems

CERN Document Server

Bujorianu, Luminita Manuela

2012-01-01

Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist.

Directory of Open Access Journals (Sweden)

Brian Drawert

2016-12-01

Full Text Available We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.

Stochastic modelling to assess economic effects of treatment of chronic subclinical mastitis caused by Streptococcus uberis

NARCIS (Netherlands)

Steeneveld, W.; Swinkels, J.; Hogeveen, H.

2007-01-01

Chronic subclinical mastitis is usually not treated during the lactation. However, some veterinarians regard treatment of some types of subclinical mastitis to be effective. The goal of this research was to develop a stochastic Monte Carlo simulation model to support decisions around treatment of

Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

KAUST Repository

Bessaih, Hakima

2015-11-02

The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling (ᵋ for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling (ᵋ, β > 1) is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.

Stochastic Estimation via Polynomial Chaos

Science.gov (United States)

2015-10-01

AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic

Remarks on stochastic acceleration

International Nuclear Information System (INIS)

Graeff, P.

1982-12-01

Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)

Assessing debt sustainability in a stochastic environment: 200 years of Dutch debt and deficit management

NARCIS (Netherlands)

van Wijnbergen, S.; France, A.

2012-01-01

When debt levels approach critical levels, tax payers may revolt against the associated debt service burden. Funding problems may arise in capital markets when lenders anticipate such revolts and refuse to participate in debt auctions. We provide a stochastic framework to assess whether such

Deterministic and stochastic models for middle east respiratory syndrome (MERS)

Science.gov (United States)

Suryani, Dessy Rizki; Zevika, Mona; Nuraini, Nuning

2018-03-01

World Health Organization (WHO) data stated that since September 2012, there were 1,733 cases of Middle East Respiratory Syndrome (MERS) with 628 death cases that occurred in 27 countries. MERS was first identified in Saudi Arabia in 2012 and the largest cases of MERS outside Saudi Arabia occurred in South Korea in 2015. MERS is a disease that attacks the respiratory system caused by infection of MERS-CoV. MERS-CoV transmission occurs directly through direct contact between infected individual with non-infected individual or indirectly through contaminated object by the free virus. Suspected, MERS can spread quickly because of the free virus in environment. Mathematical modeling is used to illustrate the transmission of MERS disease using deterministic model and stochastic model. Deterministic model is used to investigate the temporal dynamic from the system to analyze the steady state condition. Stochastic model approach using Continuous Time Markov Chain (CTMC) is used to predict the future states by using random variables. From the models that were built, the threshold value for deterministic models and stochastic models obtained in the same form and the probability of disease extinction can be computed by stochastic model. Simulations for both models using several of different parameters are shown, and the probability of disease extinction will be compared with several initial conditions.

EFFECTS OF HIGH ECONOMIC IMPORTANCE OF INDUSTRIAL BRANCHES ON HUMAN LIFE QUALITY AND ENVIRONMENT

Directory of Open Access Journals (Sweden)

Doguş Deniz Özarslan

2012-01-01

Full Text Available Importance of industrialization which has a role in determination of the civilization levels of societies is increasing everyday due to meet rapidly increasing demands. However this process has led up to environmental problems with time and thus effects on quality of human life also brought along. In this study, three sectors were selected among different branches of industry according to their economical importance in Turkey. These sectors are paper, metal and construction chemicals industry. Production processes of selected sectors were examined and effects of production stages on the environment and human health as well as their contribution to sustainable development were investigated. Well known Turkish companies from each industrial branch were evaluated in detail. These industrial sectors having economic importance are compared to each other according to their effects on quality of human life and environment and the results are evaluated accordingly.

Stochastic parameterizing manifolds and non-Markovian reduced equations stochastic manifolds for nonlinear SPDEs II

CERN Document Server

Chekroun, Mickaël D; Wang, Shouhong

2015-01-01

In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.

Stochastic spin-one massive field

International Nuclear Information System (INIS)

Lim, S.C.

1984-01-01

Stochastic quantization schemes of Nelson and Parisi and Wu are applied to a spin-one massive field. Unlike the scalar case Nelson's stochastic spin-one massive field cannot be identified with the corresponding euclidean field even if the fourth component of the euclidean coordinate is taken as equal to the real physical time. In the Parisi-Wu quantization scheme the stochastic Proca vector field has a similar property as the scalar field; which has an asymptotically stationary part and a transient part. The large equal-time limit of the expectation values of the stochastic Proca field are equal to the expectation values of the corresponding euclidean field. In the Stueckelberg formalism the Parisi-Wu scheme gives rise to a stochastic vector field which differs from the massless gauge field in that the gauge cannot be fixed by the choice of boundary condition. (orig.)

Methodological Tools for the Assessment of Ecological and Socio-Economic Environment in the Region within the Limits of the Sustainability of Biosphere

Directory of Open Access Journals (Sweden)

Aleksey Yuryevich Davankov

2016-12-01

Full Text Available The article is devoted to the study of ecological and socio-economic environment as well as the development of effective methodological tool for the assessment of its stability. This tool allows to ascertain the level of economic activity of the regions within the limits of the sustainability of biosphere. In the article, the regional system is considered as the total of industrial enterprises, social infrastructure and natural environment creating a specific territorial ecological and socio-economic environment, whose stability depends on the level of economic activity measured by the capacity of territorial ecosystem. The use of a technique for the comparative assessment of the energy indicators of economic activity creating a specific ecological and socio-economic environment of the region as well as of the indicator of the ecological capacity of the territory is proved. The ecological capacity of the territory enables to better estimate the level of the sustainability of the region within the limits of sustainability of biosphere. This method allows to forecast the development of the studied territory by the measurement of general energy flow on the basis of closed material and energy flows. The research revealed an indicator of the sustainability of ecological and socio-economic environment of Ural Federal District. Yamalo-Nenets Autonomous District is the most stable, the Chelyabinsk region is the least stable, which is associated with both natural conditions and the specificities of economic structure. The labour productivity indicator, expressed in energy units, has revealed regions with rich natural resources. It was found that in these regions, there are significant material flows in the electricity industry that leads to a large proportion of greenhouse gas emissions. The assessment of the demographic capacity fully correlates with the calculations of the stability indicator of the regional system and the analysis of labour

Management of Ecological-Economic Processes of Pollution Accumulation and Assimilation in the Coastal Zone Marine Environment

Directory of Open Access Journals (Sweden)

I.E. Timchenko

2017-02-01

Full Text Available A model for managing the balance of pollution (getting into the sea with the coastal runoff assimilation and accumulation, based on the negative feedback between the coastal economic system efficiency and penalties for the sea coastal zone pollution is proposed. The model is constructed by the Adaptive Balance of Causes method and is intended for finding a rational balance of profit from the use of assimilative resources of the marine environment and the costs of maintaining its quality. The increase of pollutions in the coastal zone is taken as proportional to the volume of product realization. The decrease of pollution concentration is related to the environment protection activities paid for by the production. The model contains the agents for managing the volume of the economic system generalized production release. The agents control pollution accumulation rate at different ones of the bio-chemical processes resulting in the marine environment natural purification. Scenario analysis of ecological-economic processes in the “Land–Sea” system is carried out, and the dependencies of economic subsystem production profitability on penalty sanctions limiting the pollutant flux getting into the sea are constructed. Sea temperature and water mass dynamics effect on these processes is considered. The scenarios of their intra-annual variability are constructed. It is shown that the sea temperature and near-water wind consideration in the model have a significant effect on marine environment pollution level and production profitability. The conclusion is that the proposed adaptive simulation model “Sea–Land” can be used for forecasting the scenarios of coastal subsystem production processes (the volume of generalized product manufacturing, production cost, profitability in parallel with the forecast of pollution concentration in the sea scenarios.

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

Energy Technology Data Exchange (ETDEWEB)

Hosking, John Joseph Absalom, E-mail: j.j.a.hosking@cma.uio.no [University of Oslo, Centre of Mathematics for Applications (CMA) (Norway)

2012-12-15

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966-979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197-216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

International Nuclear Information System (INIS)

Hosking, John Joseph Absalom

2012-01-01

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966–979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197–216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

Absorptive and dispersive optical profiles in fluctuating environments: A stochastic model

International Nuclear Information System (INIS)

Paz, J.L.; Mendoza-Garcia, A.; Mastrodomenico, A.

2011-01-01

In this study, we determined the absorptive and dispersive optical profiles of a molecular system coupled with a thermal bath. Solvent effects were explicitly considered by modelling the non-radiative interaction with the solute as a random variable. The optical stochastical Bloch equations (OSBE) were solved using a time-ordered cumulant expansion with white noise as a correlation function. We found a solution for the Fourier component of coherence at the third order of perturbation for the nonlinear Four-wave mixing signal and produced analytical expressions for the optical responses of the system. Finally, we examined the behaviour of these properties with respect to the noise parameter, frequency detuning of the dynamic perturbation, and relaxation times.

Stochastic TDHF and the Boltzman-Langevin equation

International Nuclear Information System (INIS)

Suraud, E.; Reinhard, P.G.

1991-01-01

Outgoing from a time-dependent theory of correlations, we present a stochastic differential equation for the propagation of ensembles of Slater determinants, called Stochastic Time-Dependent Hartree-Fock (Stochastic TDHF). These ensembles are allowed to develop large fluctuations in the Hartree-Fock mean fields. An alternative stochastic differential equation, the Boltzmann-Langevin equation, can be derived from Stochastic TDHF by averaging over subensembles with small fluctuations

Stochastic resonance in a stochastic bistable system with additive noises and square–wave signal

International Nuclear Information System (INIS)

Feng, Guo; Xiang-Dong, Luo; Shao-Fu, Li; Yu-Rong, Zhou

2010-01-01

This paper considers the stochastic resonance in a stochastic bistable system driven by a periodic square-wave signal and a static force as well as by additive white noise and dichotomous noise from the viewpoint of signal-to-noise ratio. It finds that the signal-to-noise ratio appears as stochastic resonance behaviour when it is plotted as a function of the noise strength of the white noise and dichotomous noise, as a function of the system parameters, or as a function of the static force. Moreover, the influence of the strength of the stochastic potential force and the correlation rate of the dichotomous noise on the signal-to-noise ratio is investigated. (general)

Stochastic quantization of Proca field

International Nuclear Information System (INIS)

Lim, S.C.

1981-03-01

We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)

Stochastic optimization methods

CERN Document Server

Marti, Kurt

2005-01-01

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

The constitutional tutelage between economic development and balanced ecological environment; A tutela constitucional entre desenvolvimento economico e meio ambiente ecologicamente equilibrado

Energy Technology Data Exchange (ETDEWEB)

Tavares, Andre Ramos [Pontificia Univ. Catolica de Sao Paulo (PUC-SP), SP (Brazil). Programa de Pos-graduacao em Direito

2004-10-15

This article defends the inclusion of the environment defence as a constitution and economical principle which assures the maintenance of the present environmental media. This principle when inserted in the context of the existent economical order is an instrument for the intervention of the State in the economy, viewing the environment tutelage.

Environment and sustainability

DEFF Research Database (Denmark)

Paavola, Jouni; Røpke, Inge

2015-01-01

This chapter reviews socio-economic research on the environment and sustainability. The chapter first explores core aspects of socio-economics, examines how socio-economics has related to the agenda of research on the environment, and assesses how socio-economic research on the environment became...... institutionalized. We consider that the environment has not been high on the agenda of the socio-economic research community but that there is a substantial amount of socio-economic research on the environment in the ecological economics and other research communities. The chapter then examines the research...... on institutional sources of environmental problems on monetary valuation and environmental decision-making as two areas where socio-economics has had a particularly strong influence. The chapter concludes that the acknowledgement in these areas of research of ecological and social embeddedness has given rise...

The Monte Carlo approach to the economics of a DEMO-like power plant

Energy Technology Data Exchange (ETDEWEB)

Bustreo, Chiara, E-mail: chiara.bustreo@igi.cnr.it; Bolzonella, Tommaso; Zollino, Giuseppe

2015-10-15

Highlights: • A steady state DEMO-like power plant is modelled with the FRESCO code. • The Monte Carlo method is used to assess the probability distribution of the COE. • Uncertainties on technical and economical aspects make the COE vary in a large range. • The COE can be nearly 2/3 to nearly 4 times the cost derived deterministically. - Abstract: An early assessment of the economics of a fusion power plant is a key step to ensure the technology viability in a future global energy system. The FRESCO code is here used to generate the technical, physical and economic model of a steady state DEMO-like power plant whose features are taken from the current European research activities on the DEMO design definition. The Monte Carlo method is used to perform stochastic analyses in order to assess the weight on the cost of electricity of uncertainties on technical and economical aspects. This study demonstrates that a stochastic approach offers a much better perspective over the spectrum of values that could be expected for the cost of electricity from fusion. Specifically, this analysis proves that the cost of electricity of the DEMO-like power plant studied could vary in quite large range, from nearly 2/3 to nearly 4 times the cost derived through a deterministic approach, by choosing reference values for all the stochastic parameters, taken from the literature.

Revealing Forest Harvesting Effects on Large Peakflows in Rain-On-Snow Environment with a New Stochastic Framework

Science.gov (United States)

Rong, W. N.; Alila, Y.

2017-12-01

Using nine pairs of control-treatment watersheds with varying climate, physiography, and harvesting practices in the Rain-On-Snow (ROS) environment of the Pacific Northwest region, we explore the linkage between environmental control and the sensitivity of peakflow response to harvesting effects. Compared to previous paired watershed studies in ROS environment, we employed an experimental design of Frequency Pairing to isolate the effects of disturbances on systems' response. In contrary, the aspect of changing frequency distributions is not commonly invoked in previous literatures on the topic of forests and floods. Our results show how harvesting can dramatically increase the magnitude of all peakflows on record and how such effects can increase with increasing return periods, as a consequence of substantial increases to the mean and variance of the peakflow frequency distribution. Most critically, peakflows with return period larger than 10 years can increase in frequency, where the larger the peakflow event the more frequent it may become. The sensitivity of the upper tail of the frequency distribution of peakflows was found to be linked to the physiographic and climatic characteristics via a unifying synchronization / desynchronization spatial scaling mechanism that controls the generation of rain-on-snow runoff. This new physically-based stochastic hydrology understanding on the response of watersheds in ROS environments runs counter the deterministic prevailing wisdom of forest hydrology, which presumes a limited and diminishing role of forest cover as the magnitude of the peakflow event increases. By demonstrating the need for invoking the dimension of frequency in the understanding and prediction of the effects of harvesting on peakflows, findings from this study suggested that pure deterministic hypotheses and experimental designs that solely focusing on the changing magnitude of peakflows have been misguiding forest hydrology research for over a century

Assessing the potential value for an automated dairy cattle body condition scoring system through stochastic simulation

NARCIS (Netherlands)

Bewley, J.M.; Boehlje, M.D.; Gray, A.W.; Hogeveen, H.; Kenyon, S.J.; Eicher, S.D.; Schutz, M.M.

2010-01-01

Purpose – The purpose of this paper is to develop a dynamic, stochastic, mechanistic simulation model of a dairy business to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm

HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks

Directory of Open Access Journals (Sweden)

Luca Marchetti

2017-01-01

Full Text Available HSimulator is a multithread simulator for mass-action biochemical reaction systems placed in a well-mixed environment. HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA. HRSSA, the fastest hybrid algorithm to date, allows for an efficient simulation of the models while ensuring the exact simulation of a subset of the reaction network modeling slow reactions. Benchmarks show that HSimulator is often considerably faster than the other considered simulators. The software, running on Java v6.0 or higher, offers a simulation GUI for modeling and visually exploring biological processes and a Javadoc-documented Java library to support the development of custom applications. HSimulator is released under the COSBI Shared Source license agreement (COSBI-SSLA.

Phenomenology of stochastic exponential growth

Science.gov (United States)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

The Effect of Green Taxation and Economic Growth on Environment Hazards: The Case of Malaysia

OpenAIRE

Nanthakumar, Loganathan; Shahbaz, Muhammad; Taha, Roshaiza

2014-01-01

This paper explores how carbon taxation and economic growth affect environment hazards in Malaysia using time series data over the period of 1974-2010. We applied cointegration and causality approaches to determine long term and the direction of causal relationship between these variables. Based on the results, we found the cointegration relationship between the variables. Furthermore, we noted that Kuznets’ theory i.e. inverted-U shaped curve between economic growth and CO2 emissions is vali...

Community health centers' impact on the political and economic environment: the Massachusetts example.

Science.gov (United States)

Hunt, James W

2005-01-01

Since their inception in 1965, community health centers have thrived against tough odds, including patchwork funding, an unpredictable public policy environment, and a volatile healthcare marketplace. Much of this long-term success has been attributed to the centers' ability to affect their economic and political environment. Massachusetts provides an excellent example of this outward orientation. It was here that the centers first took hold, grew rapidly as a result of grassroots activity, and came together as a group for advocacy and mutual assistance. This article examines the Massachusetts experience in light of the health centers' ability to survive and grow.

Jumps and stochastic volatility in oil prices: Time series evidence

International Nuclear Information System (INIS)

Larsson, Karl; Nossman, Marcus

2011-01-01

In this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices. We compare four different models and estimate them using the Markov Chain Monte Carlo method. The support for a stochastic volatility model including jumps in both prices and volatility is strong and the model clearly outperforms the others in terms of a superior fit to data. Our estimation method allows us to obtain a detailed study of oil prices during two periods of extreme market stress included in our sample; the Gulf war and the recent financial crisis. We also address the economic significance of model choice in two option pricing applications. The implied volatilities generated by the different estimated models are compared and we price a real option to develop an oil field. Our findings indicate that model choice can have a material effect on the option values.

Optimal Control for Stochastic Delay Evolution Equations

Energy Technology Data Exchange (ETDEWEB)

Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)

2016-08-15

In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.

Stochastic representation of fire behavior in a wildland fire protection planning model for California.

Science.gov (United States)

J. Keith Gilless; Jeremy S. Fried

1998-01-01

A fire behavior module was developed for the California Fire Economics Simulator version 2 (CFES2), a stochastic simulation model of initial attack on wildland fire used by the California Department of Forestry and Fire Protection. Fire rate of spread (ROS) and fire dispatch level (FDL) for simulated fires "occurring" on the same day are determined by making...

Introduction to stochastic calculus

CERN Document Server

Karandikar, Rajeeva L

2018-01-01

This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...

Brownian motion, martingales, and stochastic calculus

CERN Document Server

Le Gall, Jean-François

2016-01-01

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested i...

Fourier Methods for Multidimensional Problems and Backward SDEs in Finance and Economics

OpenAIRE

Ruijter, M.J.

2015-01-01

In this thesis we deal with processes with uncertainties, such as financial asset prices and the global temperature. We model their evolutions by so-called stochastic processes. Many of these stochastic processes are based on the Wiener process, whose increments are normally distributed. Other models may contain jump components, to model, for example, economic disasters or degradation failures. An important class of models is the Levy class, where successive increments are independent and sta...

Stochastic line motion and stochastic flux conservation for nonideal hydromagnetic models

International Nuclear Information System (INIS)

Eyink, Gregory L.

2009-01-01

We prove that smooth solutions of nonideal (viscous and resistive) incompressible magnetohydrodynamic (MHD) equations satisfy a stochastic law of flux conservation. This property implies that the magnetic flux through a surface is equal to the average of the magnetic fluxes through an ensemble of surfaces advected backward in time by the plasma velocity perturbed with a random white noise. Our result is an analog of the well-known Alfven theorem of ideal MHD and is valid for any value of the magnetic Prandtl number. A second stochastic conservation law is shown to hold at unit Prandtl number, a random version of the generalized Kelvin theorem derived by Bekenstein and Oron for ideal MHD. These stochastic conservation laws are not only shown to be consequences of the nonideal MHD equations but are proved in fact to be equivalent to those equations. We derive similar results for two more refined hydromagnetic models, Hall MHD and the two-fluid plasma model, still assuming incompressible velocities and isotropic transport coefficients. Finally, we use these results to discuss briefly the infinite-Reynolds-number limit of hydromagnetic turbulence and to support the conjecture that flux conservation remains stochastic in that limit.

Optimizing Green Computing Awareness for Environmental Sustainability and Economic Security as a Stochastic Optimization Problem

Directory of Open Access Journals (Sweden)

Emmanuel Okewu

2017-10-01

Full Text Available The role of automation in sustainable development is not in doubt. Computerization in particular has permeated every facet of human endeavour, enhancing the provision of information for decision-making that reduces cost of operation, promotes productivity and socioeconomic prosperity and cohesion. Hence, a new field called information and communication technology for development (ICT4D has emerged. Nonetheless, the need to ensure environmentally friendly computing has led to this research study with particular focus on green computing in Africa. This is against the backdrop that the continent is feared to suffer most from the vulnerability of climate change and the impact of environmental risk. Using Nigeria as a test case, this paper gauges the green computing awareness level of Africans via sample survey. It also attempts to institutionalize green computing maturity model with a view to optimizing the level of citizens awareness amid inherent uncertainties like low bandwidth, poor network and erratic power in an emerging African market. Consequently, we classified the problem as a stochastic optimization problem and applied metaheuristic search algorithm to determine the best sensitization strategy. Although there are alternative ways of promoting green computing education, the metaheuristic search we conducted indicated that an online real-time solution that not only drives but preserves timely conversations on electronic waste (e-waste management and energy saving techniques among the citizenry is cutting edge. The authors therefore reviewed literature, gathered requirements, modelled the proposed solution using Universal Modelling Language (UML and developed a prototype. The proposed solution is a web-based multi-tier e-Green computing system that educates computer users on innovative techniques of managing computers and accessories in an environmentally friendly way. We found out that such a real-time web-based interactive forum does not

New analytic solutions of stochastic coupled KdV equations

International Nuclear Information System (INIS)

Dai Chaoqing; Chen Junlang

2009-01-01

In this paper, firstly, we use the exp-function method to seek new exact solutions of the Riccati equation. Then, with the help of Hermit transformation, we employ the Riccati equation and its new exact solutions to find new analytic solutions of the stochastic coupled KdV equation in the white noise environment. As some special examples, some analytic solutions can degenerate into these solutions reported in open literatures.

A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties

International Nuclear Information System (INIS)

Zhang, X.Y.; Huang, G.H.; Zhu, H.; Li, Y.P.

2017-01-01

In this study, a fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed for supporting sustainable management of electric power system (EPS) under dual uncertainties. As an improvement upon the mixed-integer linear fractional programming, FSDFP can not only tackle multi-objective issues effectively without setting weights, but also can deal with uncertain parameters which have both stochastic and fuzzy characteristics. Thus, the developed method can help provide valuable information for supporting capacity-expansion planning and in-depth policy analysis of EPS management problems. For demonstrating these advantages, FSDFP has been applied to a case study of a typical regional EPS planning, where the decision makers have to deal with conflicts between economic development that maximizes the system profit and environmental protection that minimizes the carbon dioxide emissions. The obtained results can be analyzed to generate several decision alternatives, and can then help decision makers make suitable decisions under different input scenarios. Furthermore, comparisons of the solution from FSDFP method with that from fuzzy stochastic dynamic linear programming, linear fractional programming and dynamic stochastic fractional programming methods are undertaken. The contrastive analysis reveals that FSDFP is a more effective approach that can better characterize the complexities and uncertainties of real EPS management problems. - Highlights: • A fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed. • FSDFP can address multiple conflicting objectives without setting weights. • FSDFP can reflect dual uncertainties with both stochastic and fuzzy characteristics. • Some reasonable solutions for a case of power system sustainable planning are generated. • Comparisons of the solutions from FSDFP with other optimization methods are undertaken.

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan

2016-11-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan; Al-Shedivat, Maruan; Neftci, Emre; Cauwenberghs, Gert; Salama, Khaled N.

2016-01-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Economically viable and environment-friendly hydro energy in Estonia

International Nuclear Information System (INIS)

Saks, Ants; Velner, Harald

2001-01-01

Hydro energy has been in oblivion in Estonia for about 30 years now. During the 1960s, most of Estonia's small hydropower plants were closed down, just as it was done in the whole Soviet Union. As the only larger hydro plant, the 125 MW plant in Narva, was situated on the Russian side of the Narva River, there were only two or three small hydro plants left. Even those were exploited at low capacity and mainly for heating the buildings. It was not until the 1990s that a number of enthusiasts started to re-establish the hydro plants by reconstructing old installations. The pre-feasibility study 'Hydropower in Estonia' proposed by Estonian and Swedish experts, showed that the restoration of the hydropower plants and watermills is economically feasible and technically possible if advanced technology is used. Hydropower as an alternative ('green') energy source should be used in the best technical-economical way. The first pilot plant in Estonia, the 200 kW Kamari plant was constructed in 1998 with compact-propeller units, in co-operation with Waterpumps WP Oy and ABB. Today, ten new plants have been constructed or are under construction. Hydropower plants/watermills should be reconstructed in accordance with the legislative acts on environment protection

THE IMPACT OF COMPETITIVENESS ON TRADE EFFICIENCY: THE ASIAN EXPERIENCE BY USING THE STOCHASTIC FRONTIER GRAVITY MODEL

Directory of Open Access Journals (Sweden)

Memduh Alper Demir

2017-12-01

Full Text Available The purpose of this study is to examine the bilateral machinery and transport equipment trade efficiency of selected fourteen Asian countries by applying stochastic frontier gravity model. These selected countries have the top machinery and transport equipment trade (both export and import volumes in Asia. The model we use includes variables such as income, market size of trading partners, distance, common culture, common border, common language and global economic crisis similar to earlier studies using the stochastic frontier gravity models. Our work, however, includes an extra variable called normalized revealed comparative advantage (NRCA index additionally. The NRCA index is comparable across commodity, country and time. Thus, the NRCA index is calculated and then included in our stochastic frontier gravity model to see the impact of competitiveness (here measured by the NRCA index on the efficiency of trade.

The stochastic effects on the Brazilian Electrical Sector

International Nuclear Information System (INIS)

Ferreira, Pedro Guilherme Costa; Oliveira, Fernando Luiz Cyrino; Souza, Reinaldo Castro

2015-01-01

The size and characteristics of the Brazilian Electrical Sector (BES) are unique. The system includes a large-scale hydrothermal power system with many hydroelectric plants and multiple owners. Due to the historical harnessing of natural resources, the National Interconnected System (NIS) was developed outside of the economic scale of the BES. The central components of the NIS enable energy generated in any part of Brazil to be consumed in distant regions, considering certain technical configurations. This interconnection results in a large-scale complex system and is controlled by robust computational models, used to support the planning and operation of the NIS. This study presents a different vision of the SEB, demonstrating the intrinsic relationship between hydrological stochasticity and the activities executed by the system, which is an important sector of the infrastructure in Brazil. The simulation of energy scenarios is crucial to the optimal manner to operate the sector and to supporting decisions about whether expansion is necessary, thus, avoiding unnecessary costs and/or losses. These scenarios are an imposing factor in the determination of the spot cost of electrical energy, given that the simulated quantities of water in the reservoirs are one of the determinants for the short-term energy price. - Highlights: • The relationship between the hydrological regimes and the energy policy and planning in Brazil; • An overview about the stochastic effects on the Brazilian Electrical Sector; • The stochasticity associated with the Brazilian electrical planning; • The importance of hydro resources management for energy generation in Brazil;

Economic and social development, energy and environment in Latin America and the West Indies - an ovierview

International Nuclear Information System (INIS)

Suding, P.H.

1995-01-01

After giving a short overview of the economic and social development of Latin America since 1980 the present article deals with the various problems relating to the energy supply of that region, namely economic growth, diversification, inefficiency, and environmental effects. If discusses the relationships that exist in Latin America between energy, environment, and the social situation and endeavours to outline possible approaches towards a socially and environmentally sustainable development. (UA) [de

An introduction to probability and stochastic processes

CERN Document Server

Melsa, James L

2013-01-01

Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Stochastic Systems Uncertainty Quantification and Propagation

CERN Document Server

Grigoriu, Mircea

2012-01-01

Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: ·         A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis   ·          Probabilistic models for random variables an...

Stochastic-field cavitation model

International Nuclear Information System (INIS)

Dumond, J.; Magagnato, F.; Class, A.

2013-01-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations

Stochastic-field cavitation model

Science.gov (United States)

Dumond, J.; Magagnato, F.; Class, A.

2013-07-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

How to weigh coastal hazard against economic consequence (poster)

NARCIS (Netherlands)

Wainwright, D.; Callaghan, D.; Jongejan, R.B.; Ranasinghe, R.; Cowell, P.

2012-01-01

It is well recognised that sea level change over the coming century will have an extraordinary economic impact on coastal communities. To overcome the uncertainty that still surrounds the mechanics of shoreline recession and stochastic forcing, landuse planning and management decisions will require

A Stochastic Bi-Level Scheduling Approach for the Participation of EV Aggregators in Competitive Electricity Markets

DEFF Research Database (Denmark)

Rashidizaheh-Kermani, Homa; Vahedipour-Dahraie, Mostafa; Najafi, Hamid Reza

2017-01-01

are modeled via stochastic programming. Therefore, a two-level problem is formulated here, in which the aggregator makes decision in the upper level and the EV clients purchase energy to charge their EVs in the lower level. Then the obtained nonlinear bi-level framework is transformed into a single......This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggregator in a competitive environment. In this approach, the EV aggregator decides to participate in day-ahead (DA) and balancing markets and provides energy price offers to the EV owners in order...... is assessed in a realistic case study and the results show that the proposed model would be effective for an EV aggregator decision-making problem in a competitive environment....

Stochastic calculus of protein filament formation under spatial confinement

Science.gov (United States)

Michaels, Thomas C. T.; Dear, Alexander J.; Knowles, Tuomas P. J.

2018-05-01

The growth of filamentous aggregates from precursor proteins is a process of central importance to both normal and aberrant biology, for instance as the driver of devastating human disorders such as Alzheimer's and Parkinson's diseases. The conventional theoretical framework for describing this class of phenomena in bulk is based upon the mean-field limit of the law of mass action, which implicitly assumes deterministic dynamics. However, protein filament formation processes under spatial confinement, such as in microdroplets or in the cellular environment, show intrinsic variability due to the molecular noise associated with small-volume effects. To account for this effect, in this paper we introduce a stochastic differential equation approach for investigating protein filament formation processes under spatial confinement. Using this framework, we study the statistical properties of stochastic aggregation curves, as well as the distribution of reaction lag-times. Moreover, we establish the gradual breakdown of the correlation between lag-time and normalized growth rate under spatial confinement. Our results establish the key role of spatial confinement in determining the onset of stochasticity in protein filament formation and offer a formalism for studying protein aggregation kinetics in small volumes in terms of the kinetic parameters describing the aggregation dynamics in bulk.

Perturbation expansions of stochastic wavefunctions for open quantum systems

Science.gov (United States)

Ke, Yaling; Zhao, Yi

2017-11-01

Based on the stochastic unravelling of the reduced density operator in the Feynman path integral formalism for an open quantum system in touch with harmonic environments, a new non-Markovian stochastic Schrödinger equation (NMSSE) has been established that allows for the systematic perturbation expansion in the system-bath coupling to arbitrary order. This NMSSE can be transformed in a facile manner into the other two NMSSEs, i.e., non-Markovian quantum state diffusion and time-dependent wavepacket diffusion method. Benchmarked by numerically exact results, we have conducted a comparative study of the proposed method in its lowest order approximation, with perturbative quantum master equations in the symmetric spin-boson model and the realistic Fenna-Matthews-Olson complex. It is found that our method outperforms the second-order time-convolutionless quantum master equation in the whole parameter regime and even far better than the fourth-order in the slow bath and high temperature cases. Besides, the method is applicable on an equal footing for any kind of spectral density function and is expected to be a powerful tool to explore the quantum dynamics of large-scale systems, benefiting from the wavefunction framework and the time-local appearance within a single stochastic trajectory.

Stochastic Delay Population Dynamics under Regime Switching: Global Solutions and Extinction

Directory of Open Access Journals (Sweden)

Zheng Wu

2013-01-01

Full Text Available This paper is concerned with a delay Lotka-Volterra model under regime switching diffusion in random environment. By using generalized Itô formula, Gronwall inequality and Young’s inequality, some sufficient conditions for existence of global positive solutions and stochastically ultimate boundedness are obtained, respectively. Finally, an example is given to illustrate the main results.

Non-Markovian dissipative quantum mechanics with stochastic trajectories

International Nuclear Information System (INIS)

Koch, Werner

2010-01-01

All fields of physics - be it nuclear, atomic and molecular, solid state, or optical - offer examples of systems which are strongly influenced by the environment of the actual system under investigation. The scope of what is called ''the environment'' may vary, i.e., how far from the system of interest an interaction between the two does persist. Typically, however, it is much larger than the open system itself. Hence, a fully quantum mechanical treatment of the combined system without approximations and without limitations of the type of system is currently out of reach. With the single assumption of the environment to consist of an internally thermalized set of infinitely many harmonic oscillators, the seminal work of Stockburger and Grabert [Chem. Phys., 268:249-256, 2001] introduced an open system description that captures the environmental influence by means of a stochastic driving of the reduced system. The resulting stochastic Liouville-von Neumann equation describes the full non-Markovian dynamics without explicit memory but instead accounts for it implicitly through the correlations of the complex-valued noise forces. The present thesis provides a first application of the Stockburger-Grabert stochastic Liouville-von Neumann equation to the computation of the dynamics of anharmonic, continuous open systems. In particular, it is demonstrated that trajectory based propagators allow for the construction of a numerically stable propagation scheme. With this approach it becomes possible to achieve the tremendous increase of the noise sample count necessary to stochastically converge the results when investigating such systems with continuous variables. After a test against available analytic results for the dissipative harmonic oscillator, the approach is subsequently applied to the analysis of two different realistic, physical systems. As a first example, the dynamics of a dissipative molecular oscillator is investigated. Long time propagation - until

Tourism Environment Cost Economics Interpretation%旅游环境成本的经济学诠释

Institute of Scientific and Technical Information of China (English)

黄强叶

2011-01-01

Based on the perspective of environment cost of tourism development of unsustainable phenomenon from externality is analyzed, and the basic attribute of tourism environment cost, combining with the special properties of the tourism industry, Combining tourism environment cost the historical evolution and economics cost attributes, analyzes tourism environment cost economic meaning. Put forward the tourism carrying capacity utilization point of view, Think tourism environment cost biochemistry inside is the key to solve an externality.%基于环境成本视角对旅游发展中的不可持续现象进行分析,从外部性这一旅游环境成本的基本属性出发,结合旅游环境成本的历史演变和经济学的成本属性,剖析旅游环境成本的经济涵义,提出旅游容量资源化的观点,认为旅游环境成本内生化是解决外部性问题的关键.

Stochastic simulation of biological reactions, and its applications for studying actin polymerization.

Science.gov (United States)

Ichikawa, Kazuhisa; Suzuki, Takashi; Murata, Noboru

2010-11-30

Molecular events in biological cells occur in local subregions, where the molecules tend to be small in number. The cytoskeleton, which is important for both the structural changes of cells and their functions, is also a countable entity because of its long fibrous shape. To simulate the local environment using a computer, stochastic simulations should be run. We herein report a new method of stochastic simulation based on random walk and reaction by the collision of all molecules. The microscopic reaction rate P(r) is calculated from the macroscopic rate constant k. The formula involves only local parameters embedded for each molecule. The results of the stochastic simulations of simple second-order, polymerization, Michaelis-Menten-type and other reactions agreed quite well with those of deterministic simulations when the number of molecules was sufficiently large. An analysis of the theory indicated a relationship between variance and the number of molecules in the system, and results of multiple stochastic simulation runs confirmed this relationship. We simulated Ca²(+) dynamics in a cell by inward flow from a point on the cell surface and the polymerization of G-actin forming F-actin. Our results showed that this theory and method can be used to simulate spatially inhomogeneous events.

Stochastic simulation of biological reactions, and its applications for studying actin polymerization

International Nuclear Information System (INIS)

Ichikawa, Kazuhisa; Suzuki, Takashi; Murata, Noboru

2010-01-01

Molecular events in biological cells occur in local subregions, where the molecules tend to be small in number. The cytoskeleton, which is important for both the structural changes of cells and their functions, is also a countable entity because of its long fibrous shape. To simulate the local environment using a computer, stochastic simulations should be run. We herein report a new method of stochastic simulation based on random walk and reaction by the collision of all molecules. The microscopic reaction rate P r is calculated from the macroscopic rate constant k. The formula involves only local parameters embedded for each molecule. The results of the stochastic simulations of simple second-order, polymerization, Michaelis–Menten-type and other reactions agreed quite well with those of deterministic simulations when the number of molecules was sufficiently large. An analysis of the theory indicated a relationship between variance and the number of molecules in the system, and results of multiple stochastic simulation runs confirmed this relationship. We simulated Ca 2+ dynamics in a cell by inward flow from a point on the cell surface and the polymerization of G-actin forming F-actin. Our results showed that this theory and method can be used to simulate spatially inhomogeneous events

Stochastic analysis of uncertain thermal characteristic of foundation soils surrounding the crude oil pipeline in permafrost regions

International Nuclear Information System (INIS)

Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhao, Xiaodong

2016-01-01

Highlights: • The influence of stochastic properties and conditions on permafrost foundation was investigated. • A stochastic analysis for the uncertain thermal characteristic of crude oil pipe is presented. • The mean temperature and standard deviation of foundation soils are obtained and analyzed. • Average standard deviation and maximum standard deviation of foundation soils increase with time. - Abstract: For foundation soils surrounding the crude oil pipeline in permafrost regions, the soil properties and the upper boundary conditions are stochastic because of complex geological processes and changeable atmospheric environment. The conventional finite element analysis of thermal characteristics for crude oil pipeline is always deterministic, rather than taking stochastic parameters and conditions into account. This study investigated the stochastic influence of an underground crude oil pipeline on the thermal stability of the permafrost foundation on the basis of a stochastic analysis model and the stochastic finite element method. A stochastic finite element program is compiled by Matrix Laboratory (MATLAB) software, and the random temperature fields of foundation soils surrounding a crude oil pipeline in a permafrost region are obtained and analyzed by Neumann stochastic finite element method (NSFEM). The results provide a new way to predict the thermal effects of the crude oil pipeline in permafrost regions, and it shows that the standard deviations in temperature increase with time when considering the stochastic effect of soil properties and boundary conditions, which imply that the results of conventional deterministic analysis may be far from the true value, even if in different seasons. It can improve our understanding of the random temperature field of foundation soils surrounding the crude oil pipeline and provide a theoretical basis for actual engineering design in permafrost regions.

Genetic Variation in the Nuclear and Organellar Genomes Modulates Stochastic Variation in the Metabolome, Growth, and Defense

Science.gov (United States)

Joseph, Bindu; Corwin, Jason A.; Kliebenstein, Daniel J.

2015-01-01

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype. PMID:25569687

Stochastic volatility of volatility in continuous time

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole; Veraart, Almut

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility...... of volatility can be defined both non-parametrically, where we link it to the quadratic variation of the stochastic variance process, and parametrically, where we propose two new SV models which allow for stochastic volatility of volatility. In addition, we show that volatility of volatility can be estimated...

Optimal harvesting policy of a stochastic two-species competitive model with Lévy noise in a polluted environment

Science.gov (United States)

Zhao, Yu; Yuan, Sanling

2017-07-01

As well known that the sudden environmental shocks and toxicant can affect the population dynamics of fish species, a mechanistic understanding of how sudden environmental change and toxicant influence the optimal harvesting policy requires development. This paper presents the optimal harvesting of a stochastic two-species competitive model with Lévy noise in a polluted environment, where the Lévy noise is used to describe the sudden climate change. Due to the discontinuity of the Lévy noise, the classical optimal harvesting methods based on the explicit solution of the corresponding Fokker-Planck equation are invalid. The object of this paper is to fill up this gap and establish the optimal harvesting policy. By using of aggregation and ergodic methods, the approximation of the optimal harvesting effort and maximum expectation of sustainable yields are obtained. Numerical simulations are carried out to support these theoretical results. Our analysis shows that the Lévy noise and the mean stress measure of toxicant in organism may affect the optimal harvesting policy significantly.

Quantum stochastic calculus associated with quadratic quantum noises

International Nuclear Information System (INIS)

Ji, Un Cig; Sinha, Kalyan B.

2016-01-01

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus

Quantum stochastic calculus associated with quadratic quantum noises

Energy Technology Data Exchange (ETDEWEB)

Ji, Un Cig, E-mail: uncigji@chungbuk.ac.kr [Department of Mathematics, Research Institute of Mathematical Finance, Chungbuk National University, Cheongju, Chungbuk 28644 (Korea, Republic of); Sinha, Kalyan B., E-mail: kbs-jaya@yahoo.co.in [Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore-64, India and Department of Mathematics, Indian Institute of Science, Bangalore-12 (India)

2016-02-15

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus.

Set-Valued Stochastic Lebesque Integral and Representation Theorems

Directory of Open Access Journals (Sweden)

Jungang Li

2008-06-01

Full Text Available In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of stochastic integral, we shall introduce a new definition of Lebesgue integral of a set-valued stochastic process with respect to the time t . Finally we shall prove the presentation theorem of set-valued stochastic integral and dis- cuss further properties that will be useful to study set-valued stochastic differential equations with their applications.

Instantaneous stochastic perturbation theory

International Nuclear Information System (INIS)

Lüscher, Martin

2015-01-01

A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.

A retrodictive stochastic simulation algorithm

International Nuclear Information System (INIS)

Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.

2010-01-01

In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.

Stochastic processes and quantum theory

International Nuclear Information System (INIS)

Klauder, J.R.

1975-01-01

The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)

Stochastic flows in the Brownian web and net

Czech Academy of Sciences Publication Activity Database

Schertzer, E.; Sun, R.; Swart, Jan M.

2014-01-01

Roč. 227, č. 1065 (2014), s. 1-160 ISSN 0065-9266 R&D Projects: GA ČR GA201/07/0237; GA ČR GA201/09/1931 Institutional support: RVO:67985556 Keywords : Brownian web * Brownian net * stochastic flow of kernels * measure-valued process * Howitt-Warren flow * linear system * random walk in random environment * finite graph representation Subject RIV: BA - General Mathematics Impact factor: 1.727, year: 2014 http://library.utia.cas.cz/separaty/2013/SI/swart-0396636.pdf

Optimal control strategy for an impulsive stochastic competition system with time delays and jumps

Science.gov (United States)

Liu, Lidan; Meng, Xinzhu; Zhang, Tonghua

2017-07-01

Driven by both white and jump noises, a stochastic delayed model with two competitive species in a polluted environment is proposed and investigated. By using the comparison theorem of stochastic differential equations and limit superior theory, sufficient conditions for persistence in mean and extinction of two species are established. In addition, we obtain that the system is asymptotically stable in distribution by using ergodic method. Furthermore, the optimal harvesting effort and the maximum of expectation of sustainable yield (ESY) are derived from Hessian matrix method and optimal harvesting theory of differential equations. Finally, some numerical simulations are provided to illustrate the theoretical results.

Stochastic Still Water Response Model

DEFF Research Database (Denmark)

Friis-Hansen, Peter; Ditlevsen, Ove Dalager

2002-01-01

In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...

Stochastic quantization and topological theories

International Nuclear Information System (INIS)

Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.

1992-01-01

In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones

Stochastic quantization of Einstein gravity

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''

Momentum Maps and Stochastic Clebsch Action Principles

Science.gov (United States)

Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.

2018-01-01

We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.

Partial observation control in an anticipating environment

International Nuclear Information System (INIS)

Oeksendal, B; Sulem, A

2004-01-01

A study is made of a controlled stochastic system whose state X(t) at time t is described by a stochastic differential equation driven by Levy processes with filtration {F t } telementof[0,T] . The system is assumed to be anticipating, in the sense that the coefficients are assumed to be adapted to a filtration {G t } t≥0 with F t subset of equal G t for all t element of [0,T]. The corresponding anticipating stochastic differential equation is interpreted in the sense of forward integrals, which naturally generalize semimartingale integrals. The admissible controls are assumed to be adapted to a filtration {E t } telementof[0,T] such that E t subset of equal F t for all t element of [0,T]. The general problem is to maximize a given performance functional of this system over all admissible controls. This is a partial observation stochastic control problem in an anticipating environment. Examples of applications include stochastic volatity models in finance, insider influenced financial markets, and stochastic control of systems with delayed noise effects. Some particular cases in finance, involving optimal portfolios with logarithmic utility, are solved explicitly

A stochastic approach for quantifying immigrant integration: the Spanish test case

Science.gov (United States)

Agliari, Elena; Barra, Adriano; Contucci, Pierluigi; Sandell, Richard; Vernia, Cecilia

2014-10-01

We apply stochastic process theory to the analysis of immigrant integration. Using a unique and detailed data set from Spain, we study the relationship between local immigrant density and two social and two economic immigration quantifiers for the period 1999-2010. As opposed to the classic time-series approach, by letting immigrant density play the role of ‘time’ and the quantifier the role of ‘space,’ it becomes possible to analyse the behavior of the quantifiers by means of continuous time random walks. Two classes of results are then obtained. First, we show that social integration quantifiers evolve following diffusion law, while the evolution of economic quantifiers exhibits ballistic dynamics. Second, we make predictions of best- and worst-case scenarios taking into account large local fluctuations. Our stochastic process approach to integration lends itself to interesting forecasting scenarios which, in the hands of policy makers, have the potential to improve political responses to integration problems. For instance, estimating the standard first-passage time and maximum-span walk reveals local differences in integration performance for different immigration scenarios. Thus, by recognizing the importance of local fluctuations around national means, this research constitutes an important tool to assess the impact of immigration phenomena on municipal budgets and to set up solid multi-ethnic plans at the municipal level as immigration pressures build.

A stochastic approach for quantifying immigrant integration: the Spanish test case

International Nuclear Information System (INIS)

Agliari, Elena; Barra, Adriano; Contucci, Pierluigi; Sandell, Richard; Vernia, Cecilia

2014-01-01

We apply stochastic process theory to the analysis of immigrant integration. Using a unique and detailed data set from Spain, we study the relationship between local immigrant density and two social and two economic immigration quantifiers for the period 1999–2010. As opposed to the classic time-series approach, by letting immigrant density play the role of ‘time’ and the quantifier the role of ‘space,’ it becomes possible to analyse the behavior of the quantifiers by means of continuous time random walks. Two classes of results are then obtained. First, we show that social integration quantifiers evolve following diffusion law, while the evolution of economic quantifiers exhibits ballistic dynamics. Second, we make predictions of best- and worst-case scenarios taking into account large local fluctuations. Our stochastic process approach to integration lends itself to interesting forecasting scenarios which, in the hands of policy makers, have the potential to improve political responses to integration problems. For instance, estimating the standard first-passage time and maximum-span walk reveals local differences in integration performance for different immigration scenarios. Thus, by recognizing the importance of local fluctuations around national means, this research constitutes an important tool to assess the impact of immigration phenomena on municipal budgets and to set up solid multi-ethnic plans at the municipal level as immigration pressures build. (paper)

Physical activity patterns of ethnic children from low socio-economic environments within the UK.

Science.gov (United States)

Eyre, Emma Lisa Jane; Duncan, Michael Joseph; Birch, Samantha Louise; Cox, Valerie; Blackett, Matthew

2015-01-01

Many children fail to meet physical activity (PA) guidelines for health benefits. PA behaviours are complex and depend on numerous interrelated factors. The study aims to develop current understanding of how children from low Socio-economic environments within the UK use their surrounding built environments for PA by using advanced technology. The environment was assessed in 96 school children (7-9 years) using global positioning system (GPS) monitoring (Garmin Forerunner, 305). In a subsample of 46 children, the environment and PA were assessed using an integrated GPS and heart rate monitor. The percentage of time spent indoor, outdoor, in green and non-green environments along with time spent in moderate-to-vigorous PA (MVPA) in indoor and outdoor environments were assessed. A 2-by-2 repeated measures analysis of covariance, controlling for body mass index, BF%, assessed the environmental differences. The findings show that 42% of children from deprived wards of Coventry fail to meet PA guidelines, of which 43% was accumulated during school. Children engaged in more MVPA outdoor than indoor environments (P outdoors was negatively associated with BF%. In conclusion, outdoor environments are important for health-enhancing PA and reducing fatness in deprived and ethnic children.

The association between neighborhood economic hardship, the retail food environment, fast food intake, and obesity: findings from the Survey of the Health of Wisconsin.

Science.gov (United States)

Laxy, Michael; Malecki, Kristen C; Givens, Marjory L; Walsh, Matthew C; Nieto, F Javier

2015-03-13

Neighborhood-level characteristics such as economic hardship and the retail food environment are assumed to be correlated and to influence consumers' dietary behavior and health status, but few studies have investigated these different relationships comprehensively in a single study. This work aims to investigate the association between neighborhood-level economic hardship, the retail food environment, fast food consumption, and obesity prevalence. Linking data from the population-based Survey of the Health of Wisconsin (SHOW, n = 1,570, 2008-10) and a commercially available business database, the Wisconsin Retail Food Environment Index (WRFEI) was defined as the mean distance from each participating household to the three closest supermarkets divided by the mean distance to the three closest convenience stores or fast food restaurants. Based on US census data, neighborhood-level economic hardship was defined by the Economic Hardship Index (EHI). Relationships were analyzed using multivariate linear and logistic regression models. SHOW residents living in neighborhoods with the highest economic hardship faced a less favorable retail food environment (WRFEI = 2.53) than residents from neighborhoods with the lowest economic hardship (WRFEI = 1.77; p-trend associations between the WRFEI and obesity and only a weak borderline-significant association between access to fast food restaurants and self-reported fast food consumption (≥ 2 times/week, OR = 0.59-0.62, p = 0.05-0.09) in urban residents. Participants reporting higher frequency of fast food consumption (≥ 2 times vs. obese (OR = 1.35, p = 0.06). This study indicates that neighborhood-level economic hardship is associated with an unfavorable retail food environment. However inconsistent or non-significant relationships between the retail food environment, fast food consumption, and obesity were observed. More research is needed to enhance methodological approaches to assess the retail food environment and

Stochastic biomathematical models with applications to neuronal modeling

CERN Document Server

Batzel, Jerry; Ditlevsen, Susanne

2013-01-01

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Introduction to stochastic dynamic programming

CERN Document Server

Ross, Sheldon M; Lukacs, E

1983-01-01

Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...

BRST stochastic quantization

International Nuclear Information System (INIS)

Hueffel, H.

1990-01-01

After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)

[Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy].

Science.gov (United States)

Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming

2018-04-01

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

Stochastic quantum gravity

International Nuclear Information System (INIS)

Rumpf, H.

1987-01-01

We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)

Stochastic models, estimation, and control

CERN Document Server

Maybeck, Peter S

1982-01-01

This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

The mean and variance of climate change in the oceans: hidden evolutionary potential under stochastic environmental variability in marine sticklebacks.

Science.gov (United States)

Shama, Lisa N S

2017-08-21

Increasing climate variability may pose an even greater risk to species than climate warming because temperature fluctuations can amplify adverse impacts of directional warming on fitness-related traits. Here, the influence of directional warming and increasing climate variability on marine stickleback fish (Gasterosteus aculeatus) offspring size variation was investigated by simulating changes to the mean and variance of ocean temperatures predicted under climate change. Reproductive traits of mothers and offspring size reaction norms across four climate scenarios were examined to assess the roles of standing genetic variation, transgenerational and within-generation plasticity in adaptive potential. Mothers acclimated to directional warming produced smaller eggs than mothers in constant, ambient temperatures, whereas mothers in a predictably variable environment (weekly change between temperatures) produced a range of egg sizes, possibly reflecting a diversified bet hedging strategy. Offspring size post-hatch was mostly influenced by genotype by environment interactions and not transgenerational effects. Offspring size reaction norms also differed depending on the type of environmental predictability (predictably variable vs. stochastic), with offspring reaching the largest sizes in the stochastic environment. Release of cryptic genetic variation for offspring size in the stochastic environment suggests hidden evolutionary potential in this wild population to respond to changes in environmental predictability.

A condition-based maintenance policy for multi-component systems with Lévy copulas dependence

International Nuclear Information System (INIS)

Li, Heping; Deloux, Estelle; Dieulle, Laurence

2016-01-01

In this paper, we propose a new condition-based maintenance policy for multi-component systems taking into account stochastic and economic dependences. The stochastic dependence between components due to common environment is modelled by Lévy copulas. Its influence on the maintenance optimization is investigated with different dependence degrees. On the issue of economic dependence providing opportunities to group maintenance activities, a new maintenance decision rule is proposed which permits maintenance grouping. In order to evaluate the performance of the proposed maintenance policy, we compare it to the classical maintenance policies. - Highlights: • A new adaptive maintenance policy for grouping maintenance actions is proposed. • The impacts of both economic and stochastic dependences are investigated. • The performance of the proposed maintenance policy is evaluated under different system configurations. • The stochastic dependence is modelled by Lévy copulas. • The proposed maintenance decision rule can take full advantage of economic and stochastic dependences.

Stochastic theories of quantum mechanics

International Nuclear Information System (INIS)

De la Pena, L.; Cetto, A.M.

1991-01-01

The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)

Health, "illth," and economic growth: medicine, environment, and economics at the crossroads.

Science.gov (United States)

Egger, Garry

2009-07-01

Economic growth has been the single biggest contributor to population health since the Industrial Revolution. The growth paradigm, by definition, is dynamic, implying similar diminishing returns on investment at both the macro- and the micro-economic levels. Changes in patterns of health in developing countries, from predominantly microbial-related infectious diseases to lifestyle-related chronic diseases (e.g., obesity, type 2 diabetes) beyond a point of economic growth described as the epidemiologic transition, suggest the start of certain declining benefits from further investment in the growth model. These changes are reflected in slowing improvements in some health indices (e.g., mortality, infant mortality) and deterioration in others (e.g., disability-associated life years, obesity, chronic diseases). Adverse environmental consequences, such as climate change from economic development, are also related to disease outcomes through the development of inflammatory processes due to an immune reaction to new environmental and lifestyle-related inducers. Both increases in chronic disease and climate change can be seen as growth problems with a similar economic cause and potential economic and public health-rather than personal health-solutions. Some common approaches for dealing with both are discussed, with a plea for greater involvement by health scientists in the economic and environmental debates in order to deal effectively with issues like obesity and chronic disease.

Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

Science.gov (United States)

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2015-09-01

Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

Essays on variational approximation techniques for stochastic optimization problems

Science.gov (United States)

Deride Silva, Julio A.

This dissertation presents five essays on approximation and modeling techniques, based on variational analysis, applied to stochastic optimization problems. It is divided into two parts, where the first is devoted to equilibrium problems and maxinf optimization, and the second corresponds to two essays in statistics and uncertainty modeling. Stochastic optimization lies at the core of this research as we were interested in relevant equilibrium applications that contain an uncertain component, and the design of a solution strategy. In addition, every stochastic optimization problem relies heavily on the underlying probability distribution that models the uncertainty. We studied these distributions, in particular, their design process and theoretical properties such as their convergence. Finally, the last aspect of stochastic optimization that we covered is the scenario creation problem, in which we described a procedure based on a probabilistic model to create scenarios for the applied problem of power estimation of renewable energies. In the first part, Equilibrium problems and maxinf optimization, we considered three Walrasian equilibrium problems: from economics, we studied a stochastic general equilibrium problem in a pure exchange economy, described in Chapter 3, and a stochastic general equilibrium with financial contracts, in Chapter 4; finally from engineering, we studied an infrastructure planning problem in Chapter 5. We stated these problems as belonging to the maxinf optimization class and, in each instance, we provided an approximation scheme based on the notion of lopsided convergence and non-concave duality. This strategy is the foundation of the augmented Walrasian algorithm, whose convergence is guaranteed by lopsided convergence, that was implemented computationally, obtaining numerical results for relevant examples. The second part, Essays about statistics and uncertainty modeling, contains two essays covering a convergence problem for a sequence

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

International Nuclear Information System (INIS)

Sutrisno; Widowati; Solikhin

2016-01-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well. (paper)

Expected utility and catastrophic risk in a stochastic economy-climate model

Energy Technology Data Exchange (ETDEWEB)

Ikefuji, M. [Institute of Social and Economic Research, Osaka University, Osaka (Japan); Laeven, R.J.A.; Magnus, J.R. [Department of Econometrics and Operations Research, Tilburg University, Tilburg (Netherlands); Muris, C. [CentER, Tilburg University, Tilburg (Netherlands)

2010-11-15

In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economy-climate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.

A dual theory of price and value in a meso-scale economic model with stochastic profit rate

Science.gov (United States)

Greenblatt, R. E.

2014-12-01

The problem of commodity price determination in a market-based, capitalist economy has a long and contentious history. Neoclassical microeconomic theories are based typically on marginal utility assumptions, while classical macroeconomic theories tend to be value-based. In the current work, I study a simplified meso-scale model of a commodity capitalist economy. The production/exchange model is represented by a network whose nodes are firms, workers, capitalists, and markets, and whose directed edges represent physical or monetary flows. A pair of multivariate linear equations with stochastic input parameters represent physical (supply/demand) and monetary (income/expense) balance. The input parameters yield a non-degenerate profit rate distribution across firms. Labor time and price are found to be eigenvector solutions to the respective balance equations. A simple relation is derived relating the expected value of commodity price to commodity labor content. Results of Monte Carlo simulations are consistent with the stochastic price/labor content relation.

A heterogeneous stochastic FEM framework for elliptic PDEs

International Nuclear Information System (INIS)

Hou, Thomas Y.; Liu, Pengfei

2015-01-01

We introduce a new concept of sparsity for the stochastic elliptic operator −div(a(x,ω)∇(⋅)), which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially heterogeneous stochastic structure. This new concept of sparsity motivates a heterogeneous stochastic finite element method (HSFEM) framework for linear elliptic equations, which discretizes the equations using the heterogeneous coupling of spatial basis with local stochastic basis to exploit the local stochastic structure of the solution space. We also provide a sampling method to construct the local stochastic basis for this framework using the randomized range finding techniques. The resulting HSFEM involves two stages and suits the multi-query setting: in the offline stage, the local stochastic structure of the solution space is identified; in the online stage, the equation can be efficiently solved for multiple forcing functions. An online error estimation and correction procedure through Monte Carlo sampling is given. Numerical results for several problems with high dimensional stochastic input are presented to demonstrate the efficiency of the HSFEM in the online stage

FERN - a Java framework for stochastic simulation and evaluation of reaction networks.

Science.gov (United States)

Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf

2008-08-29

Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand-alone program and within new

Separable quadratic stochastic operators

International Nuclear Information System (INIS)

Rozikov, U.A.; Nazir, S.

2009-04-01

We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-01-01

to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic

Dynamical and hamiltonian dilations of stochastic processes

International Nuclear Information System (INIS)

Baumgartner, B.; Gruemm, H.-R.

1982-01-01

This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

Modeling pitting corrosion damage of high-level radioactive-waste containers, with emphasis on the stochastic approach

Energy Technology Data Exchange (ETDEWEB)

Henshall, G.A.; Halsey, W.G.; Clarke, W.L.; McCright, R.D.

1993-01-01

Recent efforts to identify methods of modeling pitting corrosion damage of high-level radioactive-waste containers are described. The need to develop models that can provide information useful to higher level system performance assessment models is emphasized, and examples of how this could be accomplished are described. Work to date has focused upon physically-based phenomenological stochastic models of pit initiation and growth. These models may provide a way to distill information from mechanistic theories in a way that provides the necessary information to the less detailed performance assessment models. Monte Carlo implementations of the stochastic theory have resulted in simulations that are, at least qualitatively, consistent with a wide variety of experimental data. The effects of environment on pitting corrosion have been included in the model using a set of simple phenomenological equations relating the parameters of the stochastic model to key environmental variables. The results suggest that stochastic models might be useful for extrapolating accelerated test data and for predicting the effects of changes in the environment on pit initiation and growth. Preliminary ideas for integrating pitting models with performance assessment models are discussed. These ideas include improving the concept of container ``failure``, and the use of ``rules-of-thumb`` to take information from the detailed process models and provide it to the higher level system and subsystem models. Finally, directions for future work are described, with emphasis on additional experimental work since it is an integral part of the modeling process.

Modeling pitting corrosion damage of high-level radioactive-waste containers, with emphasis on the stochastic approach

International Nuclear Information System (INIS)

Henshall, G.A.; Halsey, W.G.; Clarke, W.L.; McCright, R.D.

1993-01-01

Recent efforts to identify methods of modeling pitting corrosion damage of high-level radioactive-waste containers are described. The need to develop models that can provide information useful to higher level system performance assessment models is emphasized, and examples of how this could be accomplished are described. Work to date has focused upon physically-based phenomenological stochastic models of pit initiation and growth. These models may provide a way to distill information from mechanistic theories in a way that provides the necessary information to the less detailed performance assessment models. Monte Carlo implementations of the stochastic theory have resulted in simulations that are, at least qualitatively, consistent with a wide variety of experimental data. The effects of environment on pitting corrosion have been included in the model using a set of simple phenomenological equations relating the parameters of the stochastic model to key environmental variables. The results suggest that stochastic models might be useful for extrapolating accelerated test data and for predicting the effects of changes in the environment on pit initiation and growth. Preliminary ideas for integrating pitting models with performance assessment models are discussed. These ideas include improving the concept of container ''failure'', and the use of ''rules-of-thumb'' to take information from the detailed process models and provide it to the higher level system and subsystem models. Finally, directions for future work are described, with emphasis on additional experimental work since it is an integral part of the modeling process

Transport in Stochastic Media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.; Thieberger, R.

1998-01-01

Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption

Modeling and forecasting mortality with economic growth : a multipopulation approach

NARCIS (Netherlands)

Boonen, T.J.; Li, H.

2017-01-01

Research on mortality modeling of multiple populations focuses mainly on extrapolating past mortality trends and summarizing these trends by one or more common latent factors. This article proposes a multipopulation stochastic mortality model that uses the explanatory power of economic growth. In

Stochastic Stability of Endogenous Growth: Theory and Applications

OpenAIRE

Boucekkine, Raouf; Pintus, Patrick; Zou, Benteng

2015-01-01

We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differen- tial equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncerta...

Optimal sensor locations for the backward Lagrangian stochastic technique in measuring lagoon gas emission

Science.gov (United States)

This study evaluated the impact of gas concentration and wind sensor locations on the accuracy of the backward Lagrangian stochastic inverse-dispersion technique (bLS) for measuring gas emission rates from a typical lagoon environment. Path-integrated concentrations (PICs) and 3-dimensional (3D) wi...

Adaptive economic and ecological forest management under risk

Science.gov (United States)

Joseph Buongiorno; Mo Zhou

2015-01-01

Background: Forest managers must deal with inherently stochastic ecological and economic processes. The future growth of trees is uncertain, and so is their value. The randomness of low-impact, high frequency or rare catastrophic shocks in forest growth has significant implications in shaping the mix of tree species and the forest landscape...

Stochastic models: theory and simulation.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2008-03-01

Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.

Stochastic PSO-based heat and power dispatch under environmental constraints incorporating CHP and wind power units

Energy Technology Data Exchange (ETDEWEB)

Piperagkas, G.S.; Anastasiadis, A.G.; Hatziargyriou, N.D. [National Technical University of Athens, School of Electrical and Computer Engineering, Electric Power Division, 9, Iroon Polytechneiou Str., GR-15773 Zografou, Athens (Greece)

2011-01-15

In this paper an extended stochastic multi-objective model for economic dispatch (ED) is proposed, that incorporates in the optimization process heat and power from CHP units and expected wind power. Stochastic restrictions for the CO{sub 2}, SO{sub 2} and NO{sub x} emissions are used as inequality constraints. The ED problem is solved using a multi-objective particle swarm optimization technique. The available wind power is estimated from a transformation of the wind speed considered as a random variable to wind power. Simulations are performed on the modified IEEE 30 bus network with 2 cogeneration units and actual wind data. Results concerning minimum cost and emissions reduction options are finally drawn. (author)

Creating the Environment for Entrepreneurship through Economic Freedom

OpenAIRE

Joshua C. Hall; Robert A. Lawson; Saurav Roychoudhury

2015-01-01

In this paper we argue that the ability of people to freely trade, enter into contracts, and start businesses in a system of private property and the rule of law is crucial for productive entrepreneurship. One measure of how freely individuals can engage in economic activity is the Economic Freedom of the World (EFW) index. After examining the economic policies that harm economic freedom and possibly entrepreneurship, we highlight the correspondence between economic freedom and a number of me...

Environment and Economic Growth. Is Technical Change the Key to Decoupling?

Energy Technology Data Exchange (ETDEWEB)

Galeotti, M. [Universita di Milano, Milan (Italy)

2003-09-01

The relationship between economic growth and pollution is very complex, depending upon a host of different factors. Thus the study of this phenomenon represents a challenging endeavor. While most economics papers begin with theory and support that theory with econometric evidence, the literature on Environmental Kuznets Curves has proceeded in the opposite direction: first developing an empirical observation about the world, and then attempting to supply appropriate theories. A number of papers have aimed at providing the theoretical underpinnings to the Environmental Kuznets Curve. Prominent here is the class of optimal growth models. These are usually studied from the point of view of the analytical conditions that must hold in order to obtain an inverted-U functional relationship between pollution and growth. These models are however seldom confronted with the data. In this paper we take one popular optimal growth model designed for climate change policy analysis and carry out a few simulation exercises with the purpose of characterizing the relationship between economic growth and emissions. In particular, we try to assess the relative contribution of the ingredients of the well-known decomposition of the environment-growth relationship put forth by Grossman (1995): according to it, the presumed inverted-U pattern results from the joint effect of scale, composition, and technology components. We do this focusing on the developed regions of the world and on a global pollutant, CO2 emissions.

Option Pricing with Stochastic Volatility and Jump Diffusion Processes

Directory of Open Access Journals (Sweden)

Radu Lupu

2006-03-01

Full Text Available Option pricing by the use of Black Scholes Merton (BSM model is based on the assumption that asset prices have a lognormal distribution. In spite of the use of these models on a large scale, both by practioners and academics, the assumption of lognormality is rejected by the history of returns. The objective of this article is to present the methods that developed after the Black Scholes Merton environment and deals with the option pricing model adjustment to the empirical properties of asset returns. The main models that appeared after BSM allowed for special changes of the returns that materialized in jump-diffusion and stochastic volatility processes. The article presents the foundations of risk neutral options evaluation and the empirical evidence that fed the amendment of the lognormal assumption in the first part and shows the evaluation procedure under the assumption of stock prices following the jump-diffusion process and the stochastic volatility process.

Intimate Partner Violence: A Stochastic Model.

Science.gov (United States)

Guidi, Elisa; Meringolo, Patrizia; Guazzini, Andrea; Bagnoli, Franco

2017-01-01

Intimate partner violence (IPV) has been a well-studied problem in the past psychological literature, especially through its classical methodology such as qualitative, quantitative and mixed methods. This article introduces two basic stochastic models as an alternative approach to simulate the short and long-term dynamics of a couple at risk of IPV. In both models, the members of the couple may assume a finite number of states, updating them in a probabilistic way at discrete time steps. After defining the transition probabilities, we first analyze the evolution of the couple in isolation and then we consider the case in which the individuals modify their behavior depending on the perceived violence from other couples in their environment or based on the perceived informal social support. While high perceived violence in other couples may converge toward the own presence of IPV by means a gender-specific transmission, the gender differences fade-out in the case of received informal social support. Despite the simplicity of the two stochastic models, they generate results which compare well with past experimental studies about IPV and they give important practical implications for prevention intervention in this field. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

Nuclear power economic database

International Nuclear Information System (INIS)

Ding Xiaoming; Li Lin; Zhao Shiping

1996-01-01

Nuclear power economic database (NPEDB), based on ORACLE V6.0, consists of three parts, i.e., economic data base of nuclear power station, economic data base of nuclear fuel cycle and economic database of nuclear power planning and nuclear environment. Economic database of nuclear power station includes data of general economics, technique, capital cost and benefit, etc. Economic database of nuclear fuel cycle includes data of technique and nuclear fuel price. Economic database of nuclear power planning and nuclear environment includes data of energy history, forecast, energy balance, electric power and energy facilities

Stochastic diffusion models for substitutable technological innovations

NARCIS (Netherlands)

Wang, L.; Hu, B.; Yu, X.

2004-01-01

Based on the analysis of firms' stochastic adoption behaviour, this paper first points out the necessity to build more practical stochastic models. And then, stochastic evolutionary models are built for substitutable innovation diffusion system. Finally, through the computer simulation of the

Stochasticity in the Josephson map

International Nuclear Information System (INIS)

Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

1996-04-01

The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

STOCHASTIC MODEL OF THE SPIN DISTRIBUTION OF DARK MATTER HALOS

Energy Technology Data Exchange (ETDEWEB)

Kim, Juhan [Center for Advanced Computation, Korea Institute for Advanced Study, Heogiro 85, Seoul 130-722 (Korea, Republic of); Choi, Yun-Young [Department of Astronomy and Space Science, Kyung Hee University, Gyeonggi 446-701 (Korea, Republic of); Kim, Sungsoo S.; Lee, Jeong-Eun [School of Space Research, Kyung Hee University, Gyeonggi 446-701 (Korea, Republic of)

2015-09-15

We employ a stochastic approach to probing the origin of the log-normal distributions of halo spin in N-body simulations. After analyzing spin evolution in halo merging trees, it was found that a spin change can be characterized by a stochastic random walk of angular momentum. Also, spin distributions generated by random walks are fairly consistent with those directly obtained from N-body simulations. We derived a stochastic differential equation from a widely used spin definition and measured the probability distributions of the derived angular momentum change from a massive set of halo merging trees. The roles of major merging and accretion are also statistically analyzed in evolving spin distributions. Several factors (local environment, halo mass, merging mass ratio, and redshift) are found to influence the angular momentum change. The spin distributions generated in the mean-field or void regions tend to shift slightly to a higher spin value compared with simulated spin distributions, which seems to be caused by the correlated random walks. We verified the assumption of randomness in the angular momentum change observed in the N-body simulation and detected several degrees of correlation between walks, which may provide a clue for the discrepancies between the simulated and generated spin distributions in the voids. However, the generated spin distributions in the group and cluster regions successfully match the simulated spin distribution. We also demonstrated that the log-normality of the spin distribution is a natural consequence of the stochastic differential equation of the halo spin, which is well described by the Geometric Brownian Motion model.

Numerical Simulation of the Heston Model under Stochastic Correlation

Directory of Open Access Journals (Sweden)

Long Teng

2017-12-01

Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

1995-01-01

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...... to optimization variables can be performed. A computer implementation is described and an illustrative example is given....

Economic measurement of environment damages

Energy Technology Data Exchange (ETDEWEB)

Krawiec, F.

1980-05-01

The densities, energy consumption, and economic development of the increasing population exacerbate environmental degradation. Air and water pollution is a major environmental problem affecting life and health, outdoor recreation, household soiling, vegetation, materials, and production. The literature review indicated that numerous studies have assessed the physical and monetary damage to populations at risk from excessive concentrations of major air and water pollutants-sulfur dioxide, total suspended particulate matter, oxidants, and carbon monoxide in air; and nutrients, oil, pesticides, and toxic metals and others in water. The measurement of the damages was one of the most controversial issues in pollution abatement. The methods that have been used to estimate the societal value of pollution abatement are: (1) chain of effects, (2) market approaches, and (3) surveys. National gross damages of air pollution of $20.2 billion and of water pollution of $11.1 billion for 1973 are substantial. These best estimates, updated for the economic and demographic conditions, could provide acceptable control totals for estimating and predicting benefits and costs of abating air and water pollution emissions. The major issues to be resolved are: (1) lack of available noneconomic data, (2) theoretical and empirical difficulties of placing a value on human life and health and on benefits such as aesthetics, and (3) lack of available demographic and economic data.

Social, economic, and political processes that create built environment inequities: perspectives from urban African Americans in Atlanta.

Science.gov (United States)

Redwood, Yanique; Schulz, Amy J; Israel, Barbara A; Yoshihama, Mieko; Wang, Caroline C; Kreuter, Marshall

2010-01-01

Growing evidence suggests that the built environment features found in many high-poverty urban areas contribute to negative health outcomes. Both built environment hazards and negative health outcomes disproportionately affect poor people of color. We used community-based participatory research and Photovoice in inner-city Atlanta to elicit African Americans' perspectives on their health priorities. The built environment emerged as a critical factor, impacting physical and mental health outcomes. We offer a conceptual model, informed by residents' perspectives, linking social, economic, and political processes to built environment and health inequities. Research, practice, and policy implications are discussed within an environmental justice framework.

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

Science.gov (United States)

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

Economic Instruments and the Environment: Can Natural Resources be Maneged Exclusively by the Market?

Directory of Open Access Journals (Sweden)

João Júlio Vitral Amaro

2012-06-01

Full Text Available The advent of industrial economies coincides with the emergence of the economy as an autonomous discipline and with the question, not hitherto placed on the “value of nature”. As the basis of any theory of the first economists was the statement that every "value" is the work of man, was a fragile theoretical nature of the classics, since this is not the result of human labor. So, to circumvent the problem of fixing the "values​​" intrinsic to nature, environmental economics, in its most widespread version, part of the statement that assigns what is "value" is not exactly the environment or environmental resources but people's preferences in relation to changes in quality or quantity supplied of natural resource. The idea of ​​transaction rights on the environment (in fact, the right to pollute found resonance in the United States with "certified environmental" measures to better control pollution. They are traded for several polluting companies that can, in turn, trade them in the market for environmental permits. Remember that in any arrangement in which disputing parties settle in reaction conditions supposedly equal, makes a big difference the presence of those more able to lobby and power to influence public opinion. It is seen, even with the refinement that achieves economic analysis by incorporating as legitimate rights of non pollution, yet there is no guarantee the order of environmental damage if the whole issue be restricted to the context of the economic approach simply.

Environmental vs Demographic Stochasticity in Population Growth

OpenAIRE

Braumann, C. A.

2010-01-01

Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.

Stochastic Real-World Drive Cycle Generation Based on a Two Stage Markov Chain Approach

NARCIS (Netherlands)

Balau, A.E.; Kooijman, D.; Vazquez Rodarte, I.; Ligterink, N.

2015-01-01

This paper presents a methodology and tool that stochastically generates drive cycles based on measured data, with the purpose of testing and benchmarking light duty vehicles in a simulation environment or on a test-bench. The WLTP database, containing real world driving measurements, was used as

Alternative Asymmetric Stochastic Volatility Models

NARCIS (Netherlands)

M. Asai (Manabu); M.J. McAleer (Michael)

2010-01-01

textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is

Economic efficiency among small scale poultry farmers in Imo State ...

African Journals Online (AJOL)

... household size and extension, were found to be the significant factors that account for the observed variation in efficiency among the small scale poultry farmers. Keywords: economic efficiency, small scale poultry farmers, stochastic frontier production model. International Journal of Agriculture and Rural Development Vol.

Transport stochastic multi-dimensional media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.

1996-01-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors)

Transport stochastic multi-dimensional media

Energy Technology Data Exchange (ETDEWEB)

Haran, O; Shvarts, D [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev; Thiberger, R [Ben-Gurion Univ. of the Negev, Beersheba (Israel)

1996-12-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors).

A stochastic simulator of a blood product donation environment with demand spikes and supply shocks.

Science.gov (United States)

An, Ming-Wen; Reich, Nicholas G; Crawford, Stephen O; Brookmeyer, Ron; Louis, Thomas A; Nelson, Kenrad E

2011-01-01

The availability of an adequate blood supply is a critical public health need. An influenza epidemic or another crisis affecting population mobility could create a critical donor shortage, which could profoundly impact blood availability. We developed a simulation model for the blood supply environment in the United States to assess the likely impact on blood availability of factors such as an epidemic. We developed a simulator of a multi-state model with transitions among states. Weekly numbers of blood units donated and needed were generated by negative binomial stochastic processes. The simulator allows exploration of the blood system under certain conditions of supply and demand rates, and can be used for planning purposes to prepare for sudden changes in the public's health. The simulator incorporates three donor groups (first-time, sporadic, and regular), immigration and emigration, deferral period, and adjustment factors for recruitment. We illustrate possible uses of the simulator by specifying input values for an 8-week flu epidemic, resulting in a moderate supply shock and demand spike (for example, from postponed elective surgeries), and different recruitment strategies. The input values are based in part on data from a regional blood center of the American Red Cross during 1996-2005. Our results from these scenarios suggest that the key to alleviating deficit effects of a system shock may be appropriate timing and duration of recruitment efforts, in turn depending critically on anticipating shocks and rapidly implementing recruitment efforts.

Modelling and application of stochastic processes

CERN Document Server

1986-01-01

The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza­ tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef­ ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...

Turbulent response in a stochastic regime

International Nuclear Information System (INIS)

Molvig, K.; Freidberg, J.P.; Potok, R.; Hirshman, S.P.; Whitson, J.C.; Tajima, T.

1981-06-01

The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations

Unpacking socio-economic risks for reading and academic self-concept in primary school: Differential effects and the role of the preschool home learning environment.

Science.gov (United States)

Crampton, Alexandria; Hall, James

2017-09-01

Uncertainty remains concerning how children's reading and academic self-concept are related and how these are differentially affected by social disadvantage and home learning environments. To contrast the impacts of early socio-economic risks and preschool home learning environments upon British children's reading abilities and academic self-concept between 7 and 10 years. n = 3,172 British children aged 3-10 years and their families. A secondary analysis of the nationally representative UK EPPE database. Multilevel structural equation modelling calculated the direct, indirect, and total impacts of early socio-economic risks (0-3 years) and preschool home learning environments (3-5 years) upon children's reading ability and academic self-concept between 7 and 10 years. Early socio-economic risk had different effects upon children's reading ability and academic self-concept. Early socio-economic risks affected children's reading at ages 7 and 10 both directly and indirectly via effects upon preschool home learning environments. By contrast, early socio-economic risks had only indirect effects upon children's academic self-concept via less stimulating home learning environments in the preschool period and by limiting reading abilities early on in primary school. Although the impacts of early socio-economic risks are larger and more easily observed upon reading than upon academic self-concept, they can impact both by making it less likely that children will experience enriching home learning environments during the preschool period. This has implications for social policymakers, early educators, and interventionists. Intervening early and improving preschool home learning environments can do more than raise children's reading abilities; secondary benefits may also be achievable upon children's self-concept. © 2017 The British Psychological Society.

Stochastic modeling and analysis of telecoms networks

CERN Document Server

Decreusefond, Laurent

2012-01-01

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

Intellectual capital: approaches to analysis as an object of the internal environment of an economic entity

Directory of Open Access Journals (Sweden)

O. E. Ustinova

2017-01-01

Full Text Available Intellectual capital is of strategic importance for a modern company. At the same time, its effective management, including a stimulating and creative approach to solving problems, will help to increase the competitiveness and development of economic entities. The article considers intellectual capital as an object of analysis of the internal environment. In the context of the proposed approaches to its study, its impact on the development of the company is also considered. The intellectual capital has a special significance and influence on internal processes, since on each of them the intellectual component allows to achieve a positive synergetic effect from the interaction of different objects. In more detail, it is proposed to consider it in terms of the position of the company it occupies on the market, the principles of its activities, the formation of marketing policies, the use of resources, methods and means of making managerial decisions, and the organizational culture formed. For the analysis of the state of the internal environment, the main approaches are proposed, in which the intellectual capital is considered, among them: methods for analyzing cash flows, economic efficiency and financial feasibility of the project, analysis of the consolidated financial flow by group of objects, assessment of the potential of the business entity, technology of choice of investment policy, technology Selection of incentive mechanisms. In this regard, it is advisable to analyze the company's internal environment from the position of influencing its state of intellectual capital. The scheme of interaction of intellectual capital and objects of an estimation of an internal environment of the managing subject is offered. The results of this study should be considered as initial data for the further development of the economic evaluation of the influence of intellectual capital on the competitiveness of companies.

Non-Markovian dissipative quantum mechanics with stochastic trajectories

Energy Technology Data Exchange (ETDEWEB)

Koch, Werner

2010-09-09

All fields of physics - be it nuclear, atomic and molecular, solid state, or optical - offer examples of systems which are strongly influenced by the environment of the actual system under investigation. The scope of what is called ''the environment'' may vary, i.e., how far from the system of interest an interaction between the two does persist. Typically, however, it is much larger than the open system itself. Hence, a fully quantum mechanical treatment of the combined system without approximations and without limitations of the type of system is currently out of reach. With the single assumption of the environment to consist of an internally thermalized set of infinitely many harmonic oscillators, the seminal work of Stockburger and Grabert [Chem. Phys., 268:249-256, 2001] introduced an open system description that captures the environmental influence by means of a stochastic driving of the reduced system. The resulting stochastic Liouville-von Neumann equation describes the full non-Markovian dynamics without explicit memory but instead accounts for it implicitly through the correlations of the complex-valued noise forces. The present thesis provides a first application of the Stockburger-Grabert stochastic Liouville-von Neumann equation to the computation of the dynamics of anharmonic, continuous open systems. In particular, it is demonstrated that trajectory based propagators allow for the construction of a numerically stable propagation scheme. With this approach it becomes possible to achieve the tremendous increase of the noise sample count necessary to stochastically converge the results when investigating such systems with continuous variables. After a test against available analytic results for the dissipative harmonic oscillator, the approach is subsequently applied to the analysis of two different realistic, physical systems. As a first example, the dynamics of a dissipative molecular oscillator is investigated. Long time

Stochastic resonance in a generalized Von Foerster population growth model

Energy Technology Data Exchange (ETDEWEB)

Lumi, N.; Mankin, R. [Institute of Mathematics and Natural Sciences, Tallinn University, 25 Narva Road, 10120 Tallinn (Estonia)

2014-11-12

The stochastic dynamics of a population growth model, similar to the Von Foerster model for human population, is studied. The influence of fluctuating environment on the carrying capacity is modeled as a multiplicative dichotomous noise. It is established that an interplay between nonlinearity and environmental fluctuations can cause single unidirectional discontinuous transitions of the mean population size versus the noise amplitude, i.e., an increase of noise amplitude can induce a jump from a state with a moderate number of individuals to that with a very large number, while by decreasing the noise amplitude an opposite transition cannot be effected. An analytical expression of the mean escape time for such transitions is found. Particularly, it is shown that the mean transition time exhibits a strong minimum at intermediate values of noise correlation time, i.e., the phenomenon of stochastic resonance occurs. Applications of the results in ecology are also discussed.

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-10-01

The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400-407]. After five decades of continual development, it has developed into an important area in systems control and optimization, and it has also served as a prototype for the development of adaptive algorithms for on-line estimation and control of stochastic systems. Recently, it has been used in statistics with Markov chain Monte Carlo for solving maximum likelihood estimation problems and for general simulation and optimizations. In this paper, we first show that the trajectory averaging estimator is asymptotically efficient for the stochastic approximation MCMC (SAMCMC) algorithm under mild conditions, and then apply this result to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic approximation MLE algorithm for missing data problems, is also considered in the paper. © Institute of Mathematical Statistics, 2010.

Stochastic resonance during a polymer translocation process

International Nuclear Information System (INIS)

Mondal, Debasish; Muthukumar, M.

2016-01-01

We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.

Economic and agricultural transformation through large-scale farming : impacts of large-scale farming on local economic development, household food security and the environment in Ethiopia

NARCIS (Netherlands)

Bekele, M.S.

2016-01-01

This study examined impacts of large-scale farming in Ethiopia on local economic development, household food security, incomes, employment, and the environment. The study adopted a mixed research approach in which both qualitative and quantitative data were generated from secondary and primary

Is human failure a stochastic process?

International Nuclear Information System (INIS)

Dougherty, Ed M.

1997-01-01

Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance

Perturbative approach to non-Markovian stochastic Schroedinger equations

International Nuclear Information System (INIS)

Gambetta, Jay; Wiseman, H.M.

2002-01-01

In this paper we present a perturbative procedure that allows one to numerically solve diffusive non-Markovian stochastic Schroedinger equations, for a wide range of memory functions. To illustrate this procedure numerical results are presented for a classically driven two-level atom immersed in an environment with a simple memory function. It is observed that as the order of the perturbation is increased the numerical results for the ensemble average state ρ red (t) approach the exact reduced state found via Imamog-barlu ' s enlarged system method [Phys. Rev. A 50, 3650 (1994)

Stochastic Switching Dynamics

DEFF Research Database (Denmark)

Simonsen, Maria

This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...

Stochastic singular optics

CSIR Research Space (South Africa)

Roux, FS

2013-09-01

Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...

Dynamics of non-holonomic systems with stochastic transport

Science.gov (United States)

Holm, D. D.; Putkaradze, V.

2018-01-01

This paper formulates a variational approach for treating observational uncertainty and/or computational model errors as stochastic transport in dynamical systems governed by action principles under non-holonomic constraints. For this purpose, we derive, analyse and numerically study the example of an unbalanced spherical ball rolling under gravity along a stochastic path. Our approach uses the Hamilton-Pontryagin variational principle, constrained by a stochastic rolling condition, which we show is equivalent to the corresponding stochastic Lagrange-d'Alembert principle. In the example of the rolling ball, the stochasticity represents uncertainty in the observation and/or error in the computational simulation of the angular velocity of rolling. The influence of the stochasticity on the deterministically conserved quantities is investigated both analytically and numerically. Our approach applies to a wide variety of stochastic, non-holonomically constrained systems, because it preserves the mathematical properties inherited from the variational principle.

Optimal management strategies in variable environments: Stochastic optimal control methods

Science.gov (United States)

Williams, B.K.

1985-01-01

Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both

Chlorofluorocarbons and the environment: scientific, economic, social and political issues

Energy Technology Data Exchange (ETDEWEB)

Badr, O; Probert, S D; O' Callaghan, P W [Cranfield Inst. of Technology, Bedford (GB). Dept. of Applied Energy

1990-01-01

Chlorofluorocarbons have been among the most useful chemical compounds ever developed. However, after more than forty years of a continuously increasing rate of worldwide use in the industrial and domestic sectors, unequivocal evidence has indicated that, if released into Earth's atmosphere, they are amongst the most devastating of pollutants that could threaten the quality of life for future generations. Thus it is not surprising that, for nearly two decades, this dichotomy of interests has been a prominent issue. This report presents the scientific evidence available concerning the impacts of chlorofluorocarbons on the ambient environment. Regional, national and international policies adopted to try to curb their emissions into the atmosphere are summarised. Economic and social consequences of these policies are discussed, together with some of the available and recommended technological solutions to the environmental problem. It is believed that agreements reached internationally to date are insufficient to ensure the adequate protection of the environment. Even an immediate total ban on the production and use of such chemical compounds would not lead to a reversal of the environmental degradation for at least a century, due to the chlorofluorocarbons already in the atmosphere. (author).

Stochastic cooling at Fermilab

International Nuclear Information System (INIS)

Marriner, J.

1986-08-01

The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system

Stochastic inflation in phase space: is slow roll a stochastic attractor?

Energy Technology Data Exchange (ETDEWEB)

Grain, Julien [Institut d' Astrophysique Spatiale, UMR8617, CNRS, Univ. Paris Sud, Université Paris-Saclay, Bt. 121, Orsay, F-91405 (France); Vennin, Vincent, E-mail: julien.grain@ias.u-psud.fr, E-mail: vincent.vennin@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO13FX (United Kingdom)

2017-05-01

An appealing feature of inflationary cosmology is the presence of a phase-space attractor, ''slow roll'', which washes out the dependence on initial field velocities. We investigate the robustness of this property under backreaction from quantum fluctuations using the stochastic inflation formalism in the phase-space approach. A Hamiltonian formulation of stochastic inflation is presented, where it is shown that the coarse-graining procedure—where wavelengths smaller than the Hubble radius are integrated out—preserves the canonical structure of free fields. This means that different sets of canonical variables give rise to the same probability distribution which clarifies the literature with respect to this issue. The role played by the quantum-to-classical transition is also analysed and is shown to constrain the coarse-graining scale. In the case of free fields, we find that quantum diffusion is aligned in phase space with the slow-roll direction. This implies that the classical slow-roll attractor is immune to stochastic effects and thus generalises to a stochastic attractor regardless of initial conditions, with a relaxation time at least as short as in the classical system. For non-test fields or for test fields with non-linear self interactions however, quantum diffusion and the classical slow-roll flow are misaligned. We derive a condition on the coarse-graining scale so that observational corrections from this misalignment are negligible at leading order in slow roll.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter; Taká č, Martin

2017-01-01

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter

2017-06-04

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Quantization of dynamical systems and stochastic control theory

International Nuclear Information System (INIS)

Guerra, F.; Morato, L.M.

1982-09-01

In the general framework of stochastic control theory we introduce a suitable form of stochastic action associated to the controlled process. Then a variational principle gives all main features of Nelson's stochastic mechanics. In particular we derive the expression of the current velocity field as the gradient of the phase action. Moreover the stochastic corrections to the Hamilton-Jacobi equation are in agreement with the quantum mechanical form of the Madelung fluid (equivalent to the Schroedinger equation). Therefore stochastic control theory can provide a very simple model simulating quantum mechanical behavior

Stochastic Drought Risk Analysis and Projection Methods For Thermoelectric Power Systems

Science.gov (United States)

Bekera, Behailu Belamo

Combined effects of socio-economic, environmental, technological and political factors impact fresh cooling water availability, which is among the most important elements of thermoelectric power plant site selection and evaluation criteria. With increased variability and changes in hydrologic statistical stationarity, one concern is the increased occurrence of extreme drought events that may be attributable to climatic changes. As hydrological systems are altered, operators of thermoelectric power plants need to ensure a reliable supply of water for cooling and generation requirements. The effects of climate change are expected to influence hydrological systems at multiple scales, possibly leading to reduced efficiency of thermoelectric power plants. This study models and analyzes drought characteristics from a thermoelectric systems operational and regulation perspective. A systematic approach to characterize a stream environment in relation to extreme drought occurrence, duration and deficit-volume is proposed and demonstrated. More specifically, the objective of this research is to propose a stochastic water supply risk analysis and projection methods from thermoelectric power systems operation and management perspectives. The study defines thermoelectric drought as a shortage of cooling water due to stressed supply or beyond operable water temperature limits for an extended period of time requiring power plants to reduce production or completely shut down. It presents a thermoelectric drought risk characterization framework that considers heat content and water quantity facets of adequate water availability for uninterrupted operation of such plants and safety of its surroundings. In addition, it outlines mechanisms to identify rate of occurrences of the said droughts and stochastically quantify subsequent potential losses to the sector. This mechanism is enabled through a model based on compound Nonhomogeneous Poisson Process. This study also demonstrates how

On Lipschitzian quantum stochastic differential inclusions

International Nuclear Information System (INIS)

Ekhaguere, G.O.S.

1990-12-01

Quantum stochastic differential inclusions are introduced and studied within the framework of the Hudson-Parthasarathy formulation of quantum stochastic calculus. Results concerning the existence of solutions of a Lipschitzian quantum stochastic differential inclusion and the relationship between the solutions of such an inclusion and those of its convexification are presented. These generalize the Filippov existence theorem and the Filippov-Wazewski Relaxation Theorem for classical differential inclusions to the present noncommutative setting. (author). 9 refs

Stochastic temperature and the Nicolai map

International Nuclear Information System (INIS)

Hueffel, H.

1989-01-01

Just as standard temperature can be related to the time coordinate of Euclidean space, a new concept of 'stochastic temperature' may be introduced by associating it to the Parisi-Wu time of stochastic quantization. The perturbative equilibrium limit for a self-interacting scalar field is studied, and a 'thermal' mass shift to one loop is shown. In addition one may interpret the underlying stochastic process as a Nicolai map at nonzero 'temperature'. 22 refs. (Author)

Stochastic Linear Quadratic Optimal Control Problems

International Nuclear Information System (INIS)

Chen, S.; Yong, J.

2001-01-01

This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward-backward stochastic differential equations are established. Some results involving Riccati equation are discussed as well

Stochastic programming with integer recourse

NARCIS (Netherlands)

van der Vlerk, Maarten Hendrikus

1995-01-01

In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic

Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid

Directory of Open Access Journals (Sweden)

Xiaogang Guo

2018-01-01

Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.

Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

Czech Academy of Sciences Publication Activity Database

Baruník, Jozef; Kukačka, Jiří

2015-01-01

Roč. 15, č. 6 (2015), s. 959-973 ISSN 1469-7688 R&D Projects: GA ČR GA402/09/0965; GA ČR GA13-32263S EU Projects: European Commission 612955 - FINMAP Institutional support: RVO:67985556 Keywords : Stochastic cusp catastrophe model * Realized volatility * Bifurcations * Stock market crash Subject RIV: AH - Economics Impact factor: 0.794, year: 2015 http://library.utia.cas.cz/separaty/2014/E/barunik-0434202.pdf

Public economics and the environment in an imperfect world. An introductory summary

International Nuclear Information System (INIS)

Bovenberg, L.; Cnossen, S.

1995-01-01

Growing populations and economies have increased the public's awareness that the world's environment resources are finite. The issues of global warming and depletion of the ozone layer have given universal significance to what were once local and regional pollution problems. In this book the interface between public economics and environmental economics is examined. It is evident that Coasian negotiations fail to internalize the costs of environmental degradation often calling for public intervention through the market mechanism. In this book those issues are considered and contributions on assessment problems, institutional aspects, the need for coordination and efficiency and distribution issues are included. The papers in this volume were selected from 64 papers, presented at the 50th IIPF (International Institute of Public Finance) congress. In this chapter 15 contributions are summarized, grouped under the headings Introduction (Part 1), An Imperfect World (Part 2), Assessment Problems (Part 3), Institutional Aspects (Part 4), The Need for Coordination (Part 5), and Efficiency and Distribution Issues (Part 6). 9 refs

Stochastic quantization of gravity and string fields

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

The stochastic quantization method of Parisi and Wu is generalized so as to make it applicable to Einstein's theory of gravitation. The generalization is based on the existence of a preferred metric in field configuration space, involves Ito's calculus, and introduces a complex stochastic process adapted to Lorentzian spacetime. It implies formally the path integral measure of DeWitt, a causual Feynman propagator, and a consistent stochastic perturbation theory. The lineraized version of the theory is also obtained from the stochastic quantization of the free string field theory of Siegel and Zwiebach. (Author)

Economic feasibility of animal welfare improvements in Dutch intensive livestock production: A comparison between broiler, laying hen, and fattening pig farms

NARCIS (Netherlands)

Gocsik, E.; Oude Lansink, A.G.J.M.; Voermans, G.; Saatkamp, H.W.

2015-01-01

This study compared the economic feasibility of production systems with different levels of animal welfare (AW) in the broiler, laying hen, and fattening pig sectors. Economic feasibility over a five-year time horizon was assessed using stochastic bio-economic simulation models. The results suggest

Static economic dispatch incorporating wind farm using Flower pollination algorithm

Directory of Open Access Journals (Sweden)

Suresh Velamuri

2016-09-01

Full Text Available Renewable energy is one of the clean and cheapest forms of energy which helps in minimizing the carbon foot print. Due to the less environmental impact and economic issues integration of renewable energy sources with the existing network gained attention. In this paper, the impact of wind energy is analysed in a power system network using static economic dispatch (SED. The wind energy is integrated with the existing thermal systems. Here, the generation scheduling is optimized using Flower pollination algorithm (FPA due to its robustness in solving nonlinear problems. Integration of wind power in the existing system increases the complexity due to its stochastic nature. Weibull distribution function is used for solving the stochastic nature of wind. Scenarios without and with wind power penetration are discussed in detail. The analysis is carried out by considering the losses and installing the wind farm at different locations in the system. The proposed methodology is tested and validated on a standard IEEE 30 bus system.

The Dynamic Programming Method of Stochastic Differential Game for Functional Forward-Backward Stochastic System

Directory of Open Access Journals (Sweden)

Shaolin Ji

2013-01-01

Full Text Available This paper is devoted to a stochastic differential game (SDG of decoupled functional forward-backward stochastic differential equation (FBSDE. For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs. Applying the Girsanov transformation method introduced by Buckdahn and Li (2008, the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI equations to the path-dependent ones. By establishing the dynamic programming principal (DPP, we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.

Thermal mixtures in stochastic mechanics