Configuring Airspace Sectors with Approximate Dynamic Programming
Bloem, Michael; Gupta, Pramod
2010-01-01
In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.
Approximate Dynamic Programming for Self-Learning Control
Institute of Scientific and Technical Information of China (English)
Derong Liu
2005-01-01
This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.
Approximate Dynamic Programming Solving the Curses of Dimensionality
Powell, Warren B
2011-01-01
Praise for the First Edition "Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners."-Computing Reviews This new edition showcases a focus on modeling and computation for complex classes of approximate dynamic programming problems Understanding approximate dynamic programming (ADP) is vital in order to develop practical and high-quality solutions to complex industrial problems, particularly when those problems involve making decisions in the presence of unce
Chen, Wei; Huang, Dayu; Kulkarni, Ankur A.; Unnikrishnan, Jayakrishnan; Zhu, Quanyan; Mehta, Prashant; Meyn, Sean; Wierman, Adam
2013-01-01
Neuro-dynamic programming is a class of powerful techniques for approximating the solution to dynamic programming equations. In their most computationally attractive formulations, these techniques provide the approximate solution only within a prescribed finite-dimensional function class. Thus, the question that always arises is how should the function class be chosen? The goal of this paper is to propose an approach using the solutions to associated fluid and diffusion approximations. In ord...
An Approximate Dynamic Programming Approach to Multidimensional Knapsack Problems
Dimitris Bertsimas; Ramazan Demir
2002-01-01
We present an Approximate Dynamic Programming (ADP) approach for the multidimensional knapsack problem (MKP). We approximate the value function (a) using parametric and nonparametric methods and (b)using a base-heuristic. We propose a new heuristic which adaptively rounds the solution of the linear programming relaxation. Our computational study suggests: (a)the new heuristic produces high quality solutions fast and robustly, (b)state of the art commercial packages like CPLEX require signific...
Approximate dynamic programming solving the curses of dimensionality
Powell, Warren B
2007-01-01
Warren B. Powell, PhD, is Professor of Operations Research and Financial Engineering at Princeton University, where he is founder and Director of CASTLE Laboratory, a research unit that works with industrial partners to test new ideas found in operations research. The recipient of the 2004 INFORMS Fellow Award, Dr. Powell has authored over 100 refereed publications on stochastic optimization, approximate dynamic programming, and dynamic resource management.
Editorial Special issue on approximate dynamic programming and reinforcement learning
Institute of Scientific and Technical Information of China (English)
Silvia Ferrari; Jagannathan Sarangapani; Frank L. Lewis
2011-01-01
We are extremely pleased to present this special issue of the Journal of Control Theory and Applications.Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over time.ADP optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.
Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator
Directory of Open Access Journals (Sweden)
Marcin Szuster
2016-02-01
Full Text Available This article focuses on the implementation of an approximate dynamic programming algorithm in the discrete tracking control system of the three-degrees of freedom Scorbot-ER 4pc robotic manipulator. The controlled system is included in an articulated robots group which uses rotary joints to access their work space. The main part of the control system is a dual heuristic dynamic programming algorithm that consists of two structures designed in the form of neural networks: an actor and a critic. The actor generates the suboptimal control law while the critic approximates the difference of the value function from Bellman’s equation with respect to the state. The residual elements of the control system are the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis performed using the Lyapunov stability theorem. The control system works online, the neural networks’ weights-adaptation procedure is performed in every iteration step, and the neural networks’ preliminary learning process is not required. The performance of the control system was verified by a series of computer simulations and experiments performed using the Scorbot-ER 4pc robotic manipulator.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha
2013-02-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.
Jooyoung Park; Gyo-Bum Chung; Jungdong Lim; Dongsu Yang
2015-01-01
Recently, the optimization of power flows in portable hybrid power-supply systems (HPSSs) has become an important issue with the advent of a variety of mobile systems and hybrid energy technologies. In this paper, a control strategy is considered for dynamically managing power flows in portable HPSSs employing batteries and supercapacitors. Our dynamic power management strategy utilizes the concept of approximate dynamic programming (ADP). ADP methods are important tools in the fields of stoc...
Tuning approximate dynamic programming policies for ambulance redeployment via direct search
Directory of Open Access Journals (Sweden)
Matthew S. Maxwell
2014-01-01
Full Text Available In this paper we consider approximate dynamic programming methods for ambulance redeployment. We first demonstrate through simple examples how typical value function fitting techniques, such as approximate policy iteration and linear programming, may not be able to locate a high-quality policy even when the value function approximation architecture is rich enough to provide the optimal policy. To make up for this potential shortcoming, we show how to use direct search methods to tune the parameters in a value function approximation architecture so as to obtain high-quality policies. Direct search is computationally intensive. We therefore use a post-decision state dynamic programming formulation of ambulance redeployment that, together with direct search, requires far less computation with no noticeable performance loss. We provide further theoretical support for the post-decision state formulation of the ambulance-deployment problem by showing that this formulation can be obtained through a limiting argument on the original dynamic programming formulation.
Directory of Open Access Journals (Sweden)
Jooyoung Park
2015-05-01
Full Text Available Recently, the optimization of power flows in portable hybrid power-supply systems (HPSSs has become an important issue with the advent of a variety of mobile systems and hybrid energy technologies. In this paper, a control strategy is considered for dynamically managing power flows in portable HPSSs employing batteries and supercapacitors. Our dynamic power management strategy utilizes the concept of approximate dynamic programming (ADP. ADP methods are important tools in the fields of stochastic control and machine learning, and the utilization of these tools for practical engineering problems is now an active and promising research field. We propose an ADP-based procedure based on optimization under constraints including the iterated Bellman inequalities, which can be solved by convex optimization carried out offline, to find the optimal power management rules for portable HPSSs. The effectiveness of the proposed procedure is tested through dynamic simulations for smartphone workload scenarios, and simulation results show that the proposed strategy can successfully cope with uncertain workload demands.
Hamilton-Jacobi-Bellman equations and approximate dynamic programming on time scales.
Seiffertt, John; Sanyal, Suman; Wunsch, Donald C
2008-08-01
The time scales calculus is a key emerging area of mathematics due to its potential use in a wide variety of multidisciplinary applications. We extend this calculus to approximate dynamic programming (ADP). The core backward induction algorithm of dynamic programming is extended from its traditional discrete case to all isolated time scales. Hamilton-Jacobi-Bellman equations, the solution of which is the fundamental problem in the field of dynamic programming, are motivated and proven on time scales. By drawing together the calculus of time scales and the applied area of stochastic control via ADP, we have connected two major fields of research. PMID:18632378
Approximate group context tree: applications to dynamic programming and dynamic choice models
Belloni, Alexandre
2011-01-01
The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities. We propose a new model selection and estimation method, develop oracle inequalities and model selection properties for the estimator. These results also provide conditions under which the use of the group structure can lead to improvements in the overall estimation. Our work is also motivated by two methodological applications: discrete stochastic dynamic programming and dynamic discrete choice models. We analyze the uniform estimation of the value function for dynamic programming and the uniform estimation of average dynamic marginal effects for dynamic discrete choice models accounting for possible imperfect model selection. We also derive the typical behavior of our estimator when applied to polynomially $\\beta$-mixing stochastic processes. For parametric models, we derive uniform rate of convergence for the estimation...
A Case Study on Air Combat Decision Using Approximated Dynamic Programming
Directory of Open Access Journals (Sweden)
Yaofei Ma
2014-01-01
Full Text Available As a continuous state space problem, air combat is difficult to be resolved by traditional dynamic programming (DP with discretized state space. The approximated dynamic programming (ADP approach is studied in this paper to build a high performance decision model for air combat in 1 versus 1 scenario, in which the iterative process for policy improvement is replaced by mass sampling from history trajectories and utility function approximating, leading to high efficiency on policy improvement eventually. A continuous reward function is also constructed to better guide the plane to find its way to “winner” state from any initial situation. According to our experiments, the plane is more offensive when following policy derived from ADP approach other than the baseline Min-Max policy, in which the “time to win” is reduced greatly but the cumulated probability of being killed by enemy is higher. The reason is analyzed in this paper.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Dynamic Analyses of Result Quality in Energy-Aware Approximate Programs
RIngenburg, Michael F.
Energy efficiency is a key concern in the design of modern computer systems. One promising approach to energy-efficient computation, approximate computing, trades off output precision for energy efficiency. However, this tradeoff can have unexpected effects on computation quality. This thesis presents dynamic analysis tools to study, debug, and monitor the quality and energy efficiency of approximate computations. We propose three styles of tools: prototyping tools that allow developers to experiment with approximation in their applications, online tools that instrument code to determine the key sources of error, and online tools that monitor the quality of deployed applications in real time. Our prototyping tool is based on an extension to the functional language OCaml. We add approximation constructs to the language, an approximation simulator to the runtime, and profiling and auto-tuning tools for studying and experimenting with energy-quality tradeoffs. We also present two online debugging tools and three online monitoring tools. The first online tool identifies correlations between output quality and the total number of executions of, and errors in, individual approximate operations. The second tracks the number of approximate operations that flow into a particular value. Our online tools comprise three low-cost approaches to dynamic quality monitoring. They are designed to monitor quality in deployed applications without spending more energy than is saved by approximation. Online monitors can be used to perform real time adjustments to energy usage in order to meet specific quality goals. We present prototype implementations of all of these tools and describe their usage with several applications. Our prototyping, profiling, and autotuning tools allow us to experiment with approximation strategies and identify new strategies, our online tools succeed in providing new insights into the effects of approximation on output quality, and our monitors succeed in
Amin, Talha
2013-01-01
In the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.
Approximate Dynamic Programming for Fast Denoising of aCGH Data
Miller, Gary L; Schwartz, Russell; Tsourakakis, Charalampos E
2010-01-01
DNA sequence copy number is the number of copies of DNA at a region of a genome. Identifying genomic regions whose DNA copy number deviates from the normal is a crucial task in understanding cancer evolution. Array-based comparative genomic hybridization (aCGH) is a high-throughput technique for identifying DNA gain or loss. Due to the high level of noise in microarray data, however, interpretation of aCGH output is a difficult and error-prone task. In this paper, we adopt a recent formulation of the denoising aCGH data problem as a regularized least squares problem and propose an approximation algorithm within $\\epsilon$ additive error, where \\epsilon is an arbitrarily small positive constant. Specifically, we show that for n probes, we can approximate the optimal value of our function within additive \\epsilon with an algorithm that runs in $\\tilde{O}(n^{1.5} \\log{(\\frac{U}{\\epsilon}))}$ time, where U is the maximum value over the regularization term and the probes. The basis of our algorithm is the definiti...
Xiao, Jingjie
A key hurdle for implementing real-time pricing of electricity is a lack of consumers' responses. Solutions to overcome the hurdle include the energy management system that automatically optimizes household appliance usage such as plug-in hybrid electric vehicle charging (and discharging with vehicle-to-grid) via a two-way communication with the grid. Real-time pricing, combined with household automation devices, has a potential to accommodate an increasing penetration of plug-in hybrid electric vehicles. In addition, the intelligent energy controller on the consumer-side can help increase the utilization rate of the intermittent renewable resource, as the demand can be managed to match the output profile of renewables, thus making the intermittent resource such as wind and solar more economically competitive in the long run. One of the main goals of this dissertation is to present how real-time retail pricing, aided by control automation devices, can be integrated into the wholesale electricity market under various uncertainties through approximate dynamic programming. What distinguishes this study from the existing work in the literature is that whole- sale electricity prices are endogenously determined as we solve a system operator's economic dispatch problem on an hourly basis over the entire optimization horizon. This modeling and algorithm framework will allow a feedback loop between electricity prices and electricity consumption to be fully captured. While we are interested in a near-optimal solution using approximate dynamic programming; deterministic linear programming benchmarks are use to demonstrate the quality of our solutions. The other goal of the dissertation is to use this framework to provide numerical evidence to the debate on whether real-time pricing is superior than the current flat rate structure in terms of both economic and environmental impacts. For this purpose, the modeling and algorithm framework is tested on a large-scale test case
Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R
2016-06-01
Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem. PMID:26744898
Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R
2016-06-01
Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.
François-Lavet, Vincent; Fonteneau, Raphaël; Ernst, Damien
2014-01-01
This paper proposes a methodology to estimate the maximum revenue that can be generated by a company that operates a high-capacity storage device to buy or sell electricity on the day-ahead electricity market. The methodology exploits the Dynamic Programming (DP) principle and is specified for hydrogen-based storage devices that use electrolysis to produce hydrogen and fuel cells to generate electricity from hydrogen. Experimental results are generated using historical data of energy prices o...
Reduction of Linear Programming to Linear Approximation
Vaserstein, Leonid N.
2006-01-01
It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.
Moraes Rêgo, Patrícia Helena; Viana da Fonseca Neto, João; Ferreira, Ernesto M.
2015-08-01
The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor-critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.
Proving acceptability properties of relaxed nondeterministic approximate programs
Carbin, Michael James; Kim, Deokhwan; Misailovic, Sasa; Rinard, Martin C
2012-01-01
Approximate program transformations such as skipping tasks [29, 30], loop perforation [21, 22, 35], reduction sampling [38], multiple selectable implementations [3, 4, 16, 38], dynamic knobs [16], synchronization elimination [20, 32], approximate function memoization [11],and approximate data types [34] produce programs that can execute at a variety of points in an underlying performance versus accuracy tradeoff space. These transformed programs have the ability to trade accuracy of their res...
Nonlinear Programming Method for Dynamic Programming
Yongyang Cai; Judd, Kenneth L; Lontzek, Thomas S.; Valentina Michelangeli; Che-Lin Su
2013-01-01
A nonlinear programming formulation is introduced to solve infinite horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to avoid inefficient discretization. Our numerical results show that this nonlinear programming method is efficient and accurate.
Dynamic Approximate Vertex Cover and Maximum Matching
Onak, Krzysztof; Rubinfeld, Ronitt
2010-01-01
We consider the problem of maintaining a large matching or a small vertex cover in a dynamically changing graph. Each update to the graph is either an edge deletion or an edge insertion. We give the first randomized data structure that simultaneously achieves a constant approximation factor and handles a sequence of k updates in k. polylog(n) time. Previous data structures require a polynomial amount of computation per update. The starting point of our construction is a distributed algorit...
Dynamical Vertex Approximation for the Hubbard Model
Toschi, Alessandro
A full understanding of correlated electron systems in the physically relevant situations of three and two dimensions represents a challenge for the contemporary condensed matter theory. However, in the last years considerable progress has been achieved by means of increasingly more powerful quantum many-body algorithms, applied to the basic model for correlated electrons, the Hubbard Hamiltonian. Here, I will review the physics emerging from studies performed with the dynamical vertex approximation, which includes diagrammatic corrections to the local description of the dynamical mean field theory (DMFT). In particular, I will first discuss the phase diagram in three dimensions with a special focus on the commensurate and incommensurate magnetic phases, their (quantum) critical properties, and the impact of fluctuations on electronic lifetimes and spectral functions. In two dimensions, the effects of non-local fluctuations beyond DMFT grow enormously, determining the appearance of a low-temperature insulating behavior for all values of the interaction in the unfrustrated model: Here the prototypical features of the Mott-Hubbard metal-insulator transition, as well as the existence of magnetically ordered phases, are completely overwhelmed by antiferromagnetic fluctuations of exponentially large extension, in accordance with the Mermin-Wagner theorem. Eventually, by a fluctuation diagnostics analysis of cluster DMFT self-energies, the same magnetic fluctuations are identified as responsible for the pseudogap regime in the holed-doped frustrated case, with important implications for the theoretical modeling of the cuprate physics.
Truth Approximation, Social Epistemology, and Opinion Dynamics
Douven, Igor; Kelp, Christoph
2011-01-01
This paper highlights some connections between work on truth approximation and work in social epistemology, in particular work on peer disagreement. In some of the literature on truth approximation, questions have been addressed concerning the efficiency of research strategies for approximating the
Dynamic programming models and applications
Denardo, Eric V
2003-01-01
Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.
Institute of Scientific and Technical Information of China (English)
李雪; 聂兰顺; 齐文艳; 战德臣
2015-01-01
针对物流配送服务业中，车辆调度问题日渐呈现任务规模大，车辆类型多、属性多，调度实时性要求越来越高等特点，提出了基于近似动态规划的动态车辆调度算法。根据当前的任务需求与车辆状态以及相应的约束条件作出相应的调度，并且对一些样本进行训练，得到了一个近似价值函数。通过该价值函数，即可对任务迅速作出相应的决策。仿真模拟实验证明了该算法的有效性和优越性。%Vehicle scheduling in service industry of logistics distribution was presenting features including the tasks tended to be of large scale,vehicles were multi-type and had multiple attributes as well as high demands for real-time scheduling.To solve these problems,this paper proposed a dy-namic vehicle scheduling algorithm based on the approximate dynamic programming.An approximate value function was obtained through training of some samples,and according to mission require-ments,vehicle state and conditions,and quick scheduling decisions could be made with the value func-tion.The simulation test has proved the correctness and effectiveness of the algorithm.
Approximated solutions to Born-Infeld dynamics
Ferraro, Rafael; Nigro, Mauro
2016-02-01
The Born-Infeld equation in the plane is usefully captured in complex language. The general exact solution can be written as a combination of holomorphic and anti-holomorphic functions. However, this solution only expresses the potential in an implicit way. We rework the formulation to obtain the complex potential in an explicit way, by means of a perturbative procedure. We take care of the secular behavior common to this kind of approach, by resorting to a symmetry the equation has at the considered order of approximation. We apply the method to build approximated solutions to Born-Infeld electrodynamics. We solve for BI electromagnetic waves traveling in opposite directions. We study the propagation at interfaces, with the aim of searching for effects susceptible to experimental detection. In particular, we show that a reflected wave is produced when a wave is incident on a semi-space containing a magnetostatic field.
STOVL propulsion system volume dynamics approximations
Drummond, Colin K.
1989-01-01
Two approaches to modeling turbofan engine component volume dynamics are explored and compared with a view toward application to real-time simulation of short take-off vertical landing (STOVL) aircraft propulsion systems. The first (and most popular) approach considers only heat and mass balances; the second approach includes a momentum balance and substitutes the heat equation with a complete energy balance. Results for a practical test case are presented and discussed.
Approximating Sparse Covering Integer Programs Online
Gupta, Anupam
2012-01-01
A covering integer program (CIP) is a mathematical program of the form: min {c^T x : Ax >= 1, 0 <= x <= u, x integer}, where A is an m x n matrix, and c and u are n-dimensional vectors, all having non-negative entries. In the online setting, the constraints (i.e., the rows of the constraint matrix A) arrive over time, and the algorithm can only increase the coordinates of vector x to maintain feasibility. As an intermediate step, we consider solving the covering linear program (CLP) online, where the integrality requirement on x is dropped. Our main results are (a) an O(log k)-competitive online algorithm for solving the CLP, and (b) an O(log k log L)-competitive randomized online algorithm for solving the CIP. Here k<=n and L<=m respectively denote the maximum number of non-zero entries in any row and column of the constraint matrix A. By a result of Feige and Korman, this is the best possible for polynomial-time online algorithms, even in the special case of set cover.
Approximate Augmented Lagrangian Functions and Nonlinear Semidefinite Programs
Institute of Scientific and Technical Information of China (English)
X. X. HUANG; K. L. TEO; X. Q. YANG
2006-01-01
In this paper, an approximate augmented Lagrangian function for nonlinear semidefinite programs is introduced. Some basic properties of the approximate augmented Lagrange function such as monotonicity and convexity are discussed. Necessary and sufficient conditions for approximate strong duality results are derived. Conditions for an approximate exact penalty representation in the framework of augmented Lagrangian are given. Under certain conditions, it is shown that any limit point of a sequence of stationary points of approximate augmented Lagrangian problems is a KKT point of the original semidefinite program and that a sequence of optimal solutions to augmented Lagrangian problems converges to a solution of the original semidefinite program.
Real space Dynamical Super Cell Approximation for interacting disordered systems
Moradian, Rostam
2004-01-01
Effective medium super-cell approximation method which is introduced for disordered systems is extended to a general case of interacting disordered systems. We found that the dynamical cluster approximation (DCA) and also the non local coherent potential approximation (NLCPA) are two simple case of this technique. Whole equations of this formalism derived by using the effective medium theory in real space.
Introduction to dynamic programming
Cooper, Leon; Rodin, E Y
1981-01-01
Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Mark
A Linear-Programming Approximation of AC Power Flows
Coffrin, Carleton; Van Hentenryck, Pascal
2012-01-01
Linear active-power-only DC power flow approximations are pervasive in the planning and control of power systems. However, these approximations fail to capture reactive power and voltage magnitudes, both of which are necessary in many applications to ensure voltage stability and AC power flow feasibility. This paper proposes linear-programming models (the LPAC models) that incorporate reactive power and voltage magnitudes in a linear power flow approximation. The LPAC models are built on a co...
Optimal Piecewise-Linear Approximation of the Quadratic Chaotic Dynamics
Directory of Open Access Journals (Sweden)
J. Petrzela
2012-04-01
Full Text Available This paper shows the influence of piecewise-linear approximation on the global dynamics associated with autonomous third-order dynamical systems with the quadratic vector fields. The novel method for optimal nonlinear function approximation preserving the system behavior is proposed and experimentally verified. This approach is based on the calculation of the state attractor metric dimension inside a stochastic optimization routine. The approximated systems are compared to the original by means of the numerical integration. Real electronic circuits representing individual dynamical systems are derived using classical as well as integrator-based synthesis and verified by time-domain analysis in Orcad Pspice simulator. The universality of the proposed method is briefly discussed, especially from the viewpoint of the higher-order dynamical systems. Future topics and perspectives are also provided
Approximate dynamic programming and aerial refueling
Panos, Dennis C.
2007-01-01
Aerial refueling is an integral part of the United States military's ability to strike targets around the world with an overwhelming and continuous projection of force. However, with an aging fleet of refueling tankers and an indefinite replacement schedule the optimization of tanker usage is vital to national security. Optimizing tanker and receiver refueling operations is a complicated endeavor as it can involve over a thousand of missions during a 24 hour period, as in Operation Iraqi Free...
Approximating the maximum weight clique using replicator dynamics.
Bomze, I R; Pelillo, M; Stix, V
2000-01-01
Given an undirected graph with weights on the vertices, the maximum weight clique problem (MWCP) is to find a subset of mutually adjacent vertices (i.e., a clique) having the largest total weight. This is a generalization of the classical problem of finding the maximum cardinality clique of an unweighted graph, which arises as a special case of the MWCP when all the weights associated to the vertices are equal. The problem is known to be NP-hard for arbitrary graphs and, according to recent theoretical results, so is the problem of approximating it within a constant factor. Although there has recently been much interest around neural-network algorithms for the unweighted maximum clique problem, no effort has been directed so far toward its weighted counterpart. In this paper, we present a parallel, distributed heuristic for approximating the MWCP based on dynamics principles developed and studied in various branches of mathematical biology. The proposed framework centers around a recently introduced continuous characterization of the MWCP which generalizes an earlier remarkable result by Motzkin and Straus. This allows us to formulate the MWCP (a purely combinatorial problem) in terms of a continuous quadratic programming problem. One drawback associated with this formulation, however, is the presence of "spurious" solutions, and we present characterizations of these solutions. To avoid them we introduce a new regularized continuous formulation of the MWCP inspired by previous works on the unweighted problem, and show how this approach completely solves the problem. The continuous formulation of the MWCP naturally maps onto a parallel, distributed computational network whose dynamical behavior is governed by the so-called replicator equations. These are dynamical systems introduced in evolutionary game theory and population genetics to model evolutionary processes on a macroscopic scale.We present theoretical results which guarantee that the solutions provided by
Some approximations in the linear dynamic equations of thin cylinders
El-Raheb, M.; Babcock, C. D., Jr.
1981-01-01
Theoretical analysis is performed on the linear dynamic equations of thin cylindrical shells to find the error committed by making the Donnell assumption and the neglect of in-plane inertia. At first, the effect of these approximations is studied on a shell with classical simply supported boundary condition. The same approximations are then investigated for other boundary conditions from a consistent approximate solution of the eigenvalue problem. The Donnell assumption is valid at frequencies high compared with the ring frequencies, for finite length thin shells. The error in the eigenfrequencies from omitting tangential inertia is appreciable for modes with large circumferential and axial wavelengths, independent of shell thickness and boundary conditions.
Global Stochastic Properties of Dynamic Models and their Linear Approximations
A.M. Babus (Ana Maria); C.G. de Vries (Casper)
2010-01-01
textabstractThe dynamic properties of micro based stochastic macro models are often analyzed through a linearization around the associated deterministic steady state. Recent literature has investigated the error made by such a deterministic approximation. Complementary to this literature we investig
Approximate bayesian parameter inference for dynamical systems in systems biology
International Nuclear Information System (INIS)
This paper proposes to use approximate instead of exact stochastic simulation algorithms for approximate Bayesian parameter inference of dynamical systems in systems biology. It first presents the mathematical framework for the description of systems biology models, especially from the aspect of a stochastic formulation as opposed to deterministic model formulations based on the law of mass action. In contrast to maximum likelihood methods for parameter inference, approximate inference method- share presented which are based on sampling parameters from a known prior probability distribution, which gradually evolves toward a posterior distribution, through the comparison of simulated data from the model to a given data set of measurements. The paper then discusses the simulation process, where an over- view is given of the different exact and approximate methods for stochastic simulation and their improvements that we propose. The exact and approximate simulators are implemented and used within approximate Bayesian parameter inference methods. Our evaluation of these methods on two tasks of parameter estimation in two different models shows that equally good results are obtained much faster when using approximate simulation as compared to using exact simulation. (Author)
Efficient Optimization of Dynamic Systems Using Pade Approximants
DEFF Research Database (Denmark)
Jensen, Jakob Søndergaard
2006-01-01
A numerical procedure is suggested for efficient optimization of large dynamic systems. The method is based on Pad´e approximants that give a remarkably accurate approximation of the vibration response for large ranges of frequencies at low computational cost. Analytical expressions for the design...... sensitivities are derived by an adjoint method making the method well suited for large number of design variables. The method is illustrated by a topology optimization example for an elastic body subjected to a time-harmonic load. The distribution of two material phases is optimized in order to reduce the...
Application of saddlepoint approximation in reliability analysis of dynamic systems
Institute of Scientific and Technical Information of China (English)
Ka-Veng Yuen; Jia Wang; Siu-Kui Au
2007-01-01
The application of the saddlepoint approximation to reliability analysis of dynamic systems iS investigated.The failure event in reliability problems is formulated as the exceedance of a single performance variable over a prescribed threshold level.The saddlepoint approximation technique provides a choice to estimate the cumulative distribution function (CDF) of the performance varilable.The failure probability is obtained as the value of the complement CDF at a specified threshold.The method requires computing the saddlepoint from a simple algebraic equation that depends on the cumulant generating function(CGF) of the performance variable.A method for calculating the saddlepoint using random samples of the performance variable is presented.The applicable region of the saddlepoint approximation is discussed in detail.A 10-story shear building model with white noise excitation illustrates the accuracy and efficiency of the proposed methodology.
Wave packet dynamics in the optimal superadiabatic approximation
Betz, Volker; Manthe, Uwe
2016-01-01
We explain the concept of superadiabatic approximations and show how in the context of the Born- Oppenheimer approximation they lead to an explicit formula that can be used to predict transitions at avoided crossings. Based on this formula, we present a simple method for computing wave packet dynamics across avoided crossings. Only knowledge of the adiabatic electronic energy levels near the avoided crossing is required for the computation. In particular, this means that no diabatization procedure is necessary, the adiabatic energy levels can be computed on the fly, and they only need to be computed to higher accuracy when an avoided crossing is detected. We test the quality of our method on the paradigmatic example of photo-dissociation of NaI, finding very good agreement with results of exact wave packet calculations.
Dynamic programming using radial basis functions
Junge, Oliver; Schreiber, Alex
2014-01-01
We propose a discretization of the optimality principle in dynamic programming based on radial basis functions and Shepard's moving least squares approximation method. We prove convergence of the approximate optimal value function to the true one and present several numerical experiments.
Dynamic Programming Strikes Back
Moerkotte, Guido; Neumann, Thomas
2008-01-01
Two highly efficient algorithms are known for optimally ordering joins while avoiding cross products: DPccp, which is based on dynamic programming, and Top-Down Partition Search, based on memoization. Both have two severe limitations: They handle only (1) simple (binary) join predicates and (2) inner joins. However, real queries may contain complex join predicates, involving more than two relations, and outer joins as well as other non-inner joins. Taking the mos...
Exact and approximate probabilistic symbolic execution for nondeterministic programs
DEFF Research Database (Denmark)
Luckow, Kasper Søe; Păsăreanu, Corina S.; Dwyer, Matthew B.;
2014-01-01
introduce approximate algorithms to search for good schedulers, speeding up established random sampling and reinforcement learning results through the quantification of path probabilities based on symbolic execution. We implemented the techniques in Symbolic PathFinder and evaluated them on nondeterministic......Probabilistic software analysis seeks to quantify the likelihood of reaching a target event under uncertain environments. Recent approaches compute probabilities of execution paths using symbolic execution, but do not support nondeterminism. Nondeterminism arises naturally when no suitable...... probabilistic model can capture a program behavior, e.g., for multithreading or distributed systems. In this work, we propose a technique, based on symbolic execution, to synthesize schedulers that resolve nondeterminism to maximize the probability of reaching a target event. To scale to large systems, we also...
Approximations for inclusion of rotor lag dynamics in helicopter flight dynamics models
Mckillip, Robert, Jr.; Curtiss, Howard C., Jr.
1991-01-01
Approximate forms are suggested for augmenting linear rotor/body response models to include rotor lag dynamics. Use of an analytically linearized rotor/body model has shown that the primary effect comes from the additional angular rate contributions of the lag inertial response. Addition of lag dynamics may be made assuming these dynamics are represented by an isolated rotor with no shaft motion. Implications of such an approximation are indicated through comparison with flight test data and sensitivity of stability levels with body rate feedback.
A HYBRID DYNAMIC PROGRAM SLICING
Institute of Scientific and Technical Information of China (English)
Yi Tong; Wu Fangjun
2005-01-01
This letter proposes a hybrid method for computing dynamic program slicing. The key element is to construct a Coverage-Testing-based Dynamic Dependence Graph (CTDDG),which makes use of both dynamic and static information to get execution status. The approach overcomes the limitations of previous dynamic slicing methods, which have to redo slicing if slice criterion changes.
Approximate supernova remnant dynamics with cosmic ray production
International Nuclear Information System (INIS)
Supernova explosions are the most violent and energetic events in the galaxy and have long been considered probable sources of cosmic rays. Recent shock acceleration models treating the cosmic rays (CR's) as test particles nb a prescribed supernova remnant (SNR) evolution, indeed indicate an approximate power law momentum distribution f sub source (p) approximation p(-a) for the particles ultimately injected into the interstellar medium (ISM). This spectrum extends almost to the momentum p = 1 million GeV/c, where the break in the observed spectrum occurs. The calculated power law index approximately less than 4.2 agrees with that inferred for the galactic CR sources. The absolute CR intensity can however not be well determined in such a test particle approximation
Envelope induced ionization dynamics beyond the dipole approximation
Simonsen, Aleksander Skjerlie; Førre, Morten; Lindroth, Eva; Selstø, Sølve
2015-01-01
When atoms and molecules are ionized by laser pulses of finite duration and increasingly high intensities, the validity of the much used dipole approximation, in which the spatial dependence and magnetic component of the external field are neglected, eventually breaks down. We report that when going beyond the dipole approximation for the description of atoms exposed to ultraviolet light, the spatial dependence of the pulse shape, the envelope, provides the dominant correction, while the spatial dependence of the carrier may safely be neglected in the general case. We present a first order beyond-dipole correction to the Hamiltonian which accounts exclusively for effects stemming from the carrier-envelope of the pulse. This much simpler form of the correction is further discussed in connection with various descriptions of the light-matter interaction. We demonstrate by ab initio calculations that this approximation, which we will refer to as the envelope approximation, reproduces the full interaction beyond t...
Taylor Series Approximation to Solve Neutrosophic Multiobjective Programming Problem
Directory of Open Access Journals (Sweden)
Ibrahim M. Hezam
2015-12-01
Full Text Available In this paper, Taylor series is used to solve neutrosophic multi-objective programming problem (NMOPP. In the proposed approach, the truth membership, Indeterminacy membership, falsity membership functions associated with each objective of multi-objective programming problems are transformed into a single objective linear programming problem by using a first order Taylor polynomial series. Finally, to illustrate the efficiency of the proposed method, a numerical experiment for supplier selection is given as an application of Taylor series method for solving neutrosophic multi-objective programming problem at end of this paper.
Strong semiclassical approximation of Wigner functions for the Hartree dynamics
Athanassoulis, Agissilaos
2011-01-01
We consider the Wigner equation corresponding to a nonlinear Schrödinger evolution of the Hartree type in the semiclassical limit h → 0. Under appropriate assumptions on the initial data and the interaction potential, we show that the Wigner function is close in L 2 to its weak limit, the solution of the corresponding Vlasov equation. The strong approximation allows the construction of semiclassical operator-valued observables, approximating their quantum counterparts in Hilbert-Schmidt topology. The proof makes use of a pointwise-positivity manipulation, which seems necessary in working with the L 2 norm and the precise form of the nonlinearity. We employ the Husimi function as a pivot between the classical probability density and the Wigner function, which - as it is well known - is not pointwise positive in general.
Approximate analysis of dynamic soil-structure interaction
Lanzi, Armando
2011-01-01
This study focuses on the approximate analysis of soil- structure interaction problems, specifically on the application of classical modal analysis for coupled horizontal-rocking vibrations of plane structures resting on a linear elastic soil. Although the classical modal approach provides a non-rigorous solution, it is particularly meaningful as it offers physical insight into the nature of soil-structure interaction effects. After validating the numerical algorithm by comparison with earlie...
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
Mansinghka, Vikash K.; Kulkarni, Tejas D.; Perov, Yura N.; Tenenbaum, Joshua B.
2013-01-01
The idea of computer vision as the Bayesian inverse problem to computer graphics has a long history and an appealing elegance, but it has proved difficult to directly implement. Instead, most vision tasks are approached via complex bottom-up processing pipelines. Here we show that it is possible to write short, simple probabilistic graphics programs that define flexible generative models and to automatically invert them to interpret real-world images. Generative probabilistic graphics program...
Approximate Solutions of Interactive Dynamic Influence Diagrams Using Model Clustering
DEFF Research Database (Denmark)
Zeng, Yifeng; Doshi, Prashant; Qiongyu, Cheng
2007-01-01
Interactive dynamic influence diagrams (I-DIDs) offer a transparent and semantically clear representation for the sequential decision-making problem over multiple time steps in the presence of other interacting agents. Solving I-DIDs exactly involves knowing the solutions of possible models of th...
Introduction to stochastic dynamic programming
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
Dynamic Programming Foundations and Principles
Sniedovich, Moshe
2010-01-01
Focusing on the modeling and solution of deterministic multistage decision problems, this book looks at dynamic programming as a problem-solving optimization method. With over 400 useful references, this edition discusses the dynamic programming analysis of a problem, illustrates the rationale behind this analysis, and clarifies the theoretical grounds that justify the rationale. It also explains the meaning and role of the concept of state in dynamic programming, examines the purpose and function of the principle of optimality, and outlines solution strategies for problems defiant of conventi
Lattice dynamics of rhenium trioxide from the quasiharmonic approximation
Wdowik, U.D.; Parlinski, K.; Chatterji, T.; Rols, S.; Schober, H.
2010-01-01
The quasiharmonic theory is applied to study the lattice dynamics and thermal properties of rhenium trioxide, a material exhibiting the negative thermal-expansion phenomenon. Phonons are calculated at several external pressures. The pressure dependence of the M, R, and zone-center phonon modes is analyzed. Relying on the Gruneisen formalism an influence of temperature on the M phonon mode is investigated. The calculated free energy of the system provides predictions for the temperature depend...
Secure Dynamic Program Repartitioning
DEFF Research Database (Denmark)
Hansen, Rene Rydhoff; Probst, Christian
2005-01-01
Secure program partitioning has been introduced as a language-based technique to allow the distribution of data and computation across mutualy untrusted hosts, while at the same time guaranteeing the protection of confidential data. Programs that have been annotated with security types...
On the point-source approximation of earthquake dynamics
Directory of Open Access Journals (Sweden)
Andrea Bizzarri
2014-06-01
Full Text Available The focus on the present study is on the point-source approximation of a seismic source. First, we compare the synthetic motions on the free surface resulting from different analytical evolutions of the seismic source (the Gabor signal (G, the Bouchon ramp (B, the Cotton and Campillo ramp (CC, the Yoffe function (Y and the Liu and Archuleta function (LA. Our numerical experiments indicate that the CC and the Y functions produce synthetics with larger oscillations and correspondingly they have a higher frequency content. Moreover, the CC and the Y functions tend to produce higher peaks in the ground velocity (roughly of a factor of two. We have also found that the falloff at high frequencies is quite different: it roughly follows ω−2 in the case of G and LA functions, it decays more faster than ω−2 for the B function, while it is slow than ω−1 for both the CC and the Y solutions. Then we perform a comparison of seismic waves resulting from 3-D extended ruptures (both supershear and subshear obeying to different governing laws against those from a single point-source having the same features. It is shown that the point-source models tend to overestimate the ground motions and that they completely miss the Mach fronts emerging from the supershear transition process. When we compare the extended fault solutions against a multiple point-sources model the agreement becomes more significant, although relevant discrepancies still persist. Our results confirm that, and more importantly quantify how, the point-source approximation is unable to adequately describe the radiation emitted during a real world earthquake, even in the most idealized case of planar fault with homogeneous properties and embedded in a homogeneous, perfectly elastic medium.
Modelling Opinion Dynamics: Theoretical analysis and continuous approximation
Pinasco, Juan Pablo; Balenzuela, Pablo
2016-01-01
Frequently we revise our first opinions after talking over with other individuals because we get convinced. Argumentation is a verbal and social process aimed at convincing. It includes conversation and persuasion. In this case, the agreement is reached because the new arguments are incorporated. In this paper we deal with a simple model of opinion formation with such persuasion dynamics, and we find the exact analytical solutions for both, long and short range interactions. A novel theoretical approach has been used in order to solve the master equations of the model with non-local kernels. Simulation results demonstrate an excellent agreement with results obtained by the theoretical estimation.
Institute of Scientific and Technical Information of China (English)
侯进军
2007-01-01
@@ 1 Seed Selection Genetic Programming In Genetic Programming, each tree in population shows an algebraic or surmounting expression, and each algebraic or surmounting expression shows an approximate analytic solution to differential equations.
Approximate but accurate quantum dynamics from the Mori formalism: I. Nonequilibrium dynamics
Montoya-Castillo, Andrés; Reichman, David R.
2016-05-01
We present a formalism that explicitly unifies the commonly used Nakajima-Zwanzig approach for reduced density matrix dynamics with the more versatile Mori theory in the context of nonequilibrium dynamics. Employing a Dyson-type expansion to circumvent the difficulty of projected dynamics, we obtain a self-consistent equation for the memory kernel which requires only knowledge of normally evolved auxiliary kernels. To illustrate the properties of the current approach, we focus on the spin-boson model and limit our attention to the use of a simple and inexpensive quasi-classical dynamics, given by the Ehrenfest method, for the calculation of the auxiliary kernels. For the first time, we provide a detailed analysis of the dependence of the properties of the memory kernels obtained via different projection operators, namely, the thermal (Redfield-type) and population based (NIBA-type) projection operators. We further elucidate the conditions that lead to short-lived memory kernels and the regions of parameter space to which this program is best suited. Via a thorough analysis of the different closures available for the auxiliary kernels and the convergence properties of the self-consistently extracted memory kernel, we identify the mechanisms whereby the current approach leads to a significant improvement over the direct usage of standard semi- and quasi-classical dynamics.
Institute of Scientific and Technical Information of China (English)
Fan Shang-Chun; Li Yan; Guo Zhan-She; Li Jing; Zhuang Hai-Han
2012-01-01
Dynamic characteristics of the resonant gyroscope are studied based on the Mathieu equation approximate solution in this paper.The Mathieu equation is used to analyze the parametric resonant characteristics and the approximate output of the resonant gyroscope.The method of small parameter perturbation is used to analyze the approximate solution of the Mathieu equation.The theoretical analysis and the numerical simulations show that the approximate solution of the Mathieu equation is close to the dynamic output characteristics of the resonant gyroscope.The experimental analysis shows that the theoretical curve and the experimental data processing results coincide perfectly,which means that the approximate solution of the Mathieu equation can present the dynamic output characteristic of the resonant gyroscope.The theoretical approach and the experimental results of the Mathieu equation approximate solution are obtained,which provides a reference for the robust design of the resonant gyroscope.
Miura, H.; Schmit, L. A., Jr.
1976-01-01
The program documentation and user's guide for the ACCESS-1 computer program is presented. ACCESS-1 is a research oriented program which implements a collection of approximation concepts to achieve excellent efficiency in structural synthesis. The finite element method is used for structural analysis and general mathematical programming algorithms are applied in the design optimization procedure. Implementation of the computer program, preparation of input data and basic program structure are described, and three illustrative examples are given.
Directory of Open Access Journals (Sweden)
D. Bahuguna
2005-01-01
Full Text Available We consider a retarded differential equation with applications to population dynamics. We establish the convergence of a finite-dimensional approximations of a unique solution, the existence and uniqueness of which are also proved in the process.
Institute of Scientific and Technical Information of China (English)
范洪义
2002-01-01
We study the Wentzel-Kramers-Brillouin (WKB) approximation for dynamic systems with kinetic couplings inentangled state representations. The result shows that the kinetic coupling will affect the position of classicalturning points where the condition of using the WKB approximation breaks down. The modified WKB approx-imation formula is derived in the entangled state representation, for example, the common eigenvector of therelative coordinate and the total momentum of two particles. The corresponding Bohr-Sommerfeld quantizationrule is also derived.
Programming an Interpreter Using Molecular Dynamics
Directory of Open Access Journals (Sweden)
C.A. Middelburg
2007-01-01
Full Text Available PGA (ProGram Algebra is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of PGA, which bears on the use of dynamic data structures in programming.We consider the programming of an interpreter for a program notation that is close to existing assembly languages using PGA with the primitives of molecular dynamics as basic instructions. It happens that, although primarily meant for explaining programming language features relating to the use of dynamic data structures, the collection of primitives of molecular dynamics in itself is suited to our programming wants.
THE CONVERGENCE OF APPROACH PENALTY FUNCTION METHOD FOR APPROXIMATE BILEVEL PROGRAMMING PROBLEM
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, a new algorithm-approximate penalty function method is designed, which can be used to solve a bilevel optimization problem with linear constrained function. In this kind of bilevel optimization problem, the evaluation of the objective function is very difficult, so that only their approximate values can be obtained. This algorithm is obtained by combining penalty function method and approximation in bilevel programming. The presented algorithm is completely different from existing methods. That convergence for this algorithm is proved.
A dynamic inequality generation scheme for polynomial programming
Ghaddar, B.; Vera Lizcano, J.C.; Anjos, M.F.
2016-01-01
Hierarchies of semidefinite programs have been used to approximate or even solve polynomial programs. This approach rapidly becomes computationally expensive and is often tractable only for problems of small size. In this paper, we propose a dynamic inequality generation scheme to generate valid pol
Gate complexity using Dynamic Programming
Sridharan, Srinivas; Gu, Mile; James, Matthew R.
2008-01-01
The relationship between efficient quantum gate synthesis and control theory has been a topic of interest in the quantum control literature. Motivated by this work, we describe in the present article how the dynamic programming technique from optimal control may be used for the optimal synthesis of quantum circuits. We demonstrate simulation results on an example system on SU(2), to obtain plots related to the gate complexity and sample paths for different logic gates.
Application of approximate entropy on dynamic characteristics of epileptic absence seizure
Institute of Scientific and Technical Information of China (English)
Yi Zhou; Ruimei Huang; Ziyi Chen; Xin Chang; Jialong Chen; Lingli Xie
2012-01-01
Electroencephalogram signals are time-varying complex electrophysiological signals. Existing studies show that approximate entropy, which is a nonlinear dynamics index, is not an ideal method for electroencephalogram analysis. Clinical electroencephalogram measurements usually contain electrical interference signals, creating additional challenges in terms of maintaining robustness of the analytic methods. There is an urgent need for a novel method of nonlinear dynamical analysis of the electroencephalogram that can characterize seizure-related changes in cerebral dynamics. The aim of this paper was to study the fluctuations of approximate entropy in preictal, ictal, and postictal electroencephalogram signals from a patient with absence seizures, and to improve the algorithm used to calculate the approximate entropy. The approximate entropy algorithm, especially our modified version, could accurately describe the dynamical changes of the brain during absence seizures. We could also demonstrate that the complexity of the brain was greater in the normal state than in the ictal state. The fluctuations of the approximate entropy before epileptic seizures observed in this study can form a goodbasis for further study on the prediction of seizures with nonlinear dynamics.
An Approximate Algorithm for a Class of Nonlinear Bilevel Integer Programming
Institute of Scientific and Technical Information of China (English)
LI Lei; TENG Chun-xian; TIAN Guang-yue
2002-01-01
The algorithm for a class of nonlinear bilevel integer programming is discussed in this paper. It is based on the theory and algorithm for nonlinear integer programming. The continuity methods for integer programming are studied in this paper. After simulated annealing algorithm is applied to the upper-level programming problem and the thought of filled function method for continuous global optimization is applied to the corresponding lower-level programming, an approximate algorithm is established. The satisfactory algorithm is elaborated in the following example.
λ-PDF AND GEGENBAUER POLYNOMIAL APPROXIMATION FOR DYNAMIC RESPONSE PROBLEMS OF RANDOM STRUCTURES
Institute of Scientific and Technical Information of China (English)
FANG Tong; LENG Xiaolei; MA Xiaoping; MENG Guang
2004-01-01
A bounded, mono-peak, and symmetrically distributed probability density function,called λ-PDF, together with the Gegenbauer polynomial approximation, is used in dynamic response problems of random structures. The λ-PDF can reasonably model a variety of random parameters in engineering random structures. The Gegenbauer polynomial approximation can be viewed as a new extension of the weighted residual method into the random space. Both of them can be easily used by scientists and engineers, and applied to a variety of response problems of random structures. The numerical example shows the effectiveness of the proposed method to study dynamic phenomena in random structures.
Lu, Jianfeng
2016-01-01
In the spirit of the fewest switches surface hopping, the frozen Gaussian approximation with surface hopping (FGA-SH) method samples a path integral representation of the non-adiabatic dynamics in the semiclassical regime. An improved sampling scheme is developed in this work for FGA-SH based on birth and death branching processes. The algorithm is validated for the standard test examples of non-adiabatic dynamics.
Analytical approximation to the dynamics of a binary stars system with time depending mass variation
López, Gustavo V
2016-01-01
We study the classical dynamics of a binary stars when there is an interchange of mass between them. Assuming that one of the star is more massive than the other, the dynamics of the lighter one is analyzed as a function of its time depending mass variation. Within our approximations and models for mass transference, we obtain a general result which establishes that if the lightest star looses mass, its period increases. If the lightest star win mass, its period decreases.
Programming an interpreter using molecular dynamics
J.A. Bergstra; C.A. Middelburg
2007-01-01
PGA (ProGram Algebra) is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of \\PGA, which bears on the use of dynamic data structures in programming. We consider the programmi
Potential function methods for approximately solving linear programming problems theory and practice
Bienstock, Daniel
2002-01-01
Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.
Feil, T. M.; Homeier, H. H. H.
2004-04-01
We present programs for the calculation and evaluation of special type Hermite-Padé-approximations. They allow the user to either numerically approximate multi-valued functions represented by a formal series expansion or to compute explicit approximants for them. The approximation scheme is based on Hermite-Padé polynomials and includes both Padé and algebraic approximants as limiting cases. The algorithm for the computation of the Hermite-Padé polynomials is based on a set of recursive equations which were derived from a generalization of continued fractions. The approximations retain their validity even on the cuts of the complex Riemann surface which allows for example the calculation of resonances in quantum mechanical problems. The programs also allow for the construction of multi-series approximations which can be more powerful than most summation methods. Program summaryTitle of program: hp.sr Catalogue identifier: ADSO Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSO Program obtainable from: CPC Program Library, Queen's University Belfast, Northern Ireland Licensing provisions: Persons requesting the program must sign the standard CPC non-profit use license Computer: Sun Ultra 10 Installation: Computing Center, University of Regensburg, Germany Operating System: Sun Solaris 7.0 Program language used: MapleV.5 Distribution format: tar gzip file Memory required to execute with typical data: 32 MB; the program itself needs only about 20 kB Number of bits in a word: 32 No. of processors used: 1 Has the code been vectorized?: no No. of bytes in distributed program, including test data etc.: 38194 No. of lines in distributed program, including test data, etc.: 4258 Nature of physical problem: Many physical and chemical quantum systems lead to the problem of evaluating a function for which only a limited series expansion is known. These functions can be numerically approximated by summation methods even if the corresponding series is only asymptotic
Approximate-model Based Estimation Method for Dynamic Response of Forging Processes
Institute of Scientific and Technical Information of China (English)
LEI Jie; LU Xinjiang; LI Yibo; HUANG Minghui; ZOU Wei
2015-01-01
Many high-quality forging productions require the large-sized hydraulic press machine (HPM) to have a desirable dynamic response. Since the forging process is complex under the low velocity, its response is difficult to estimate. And this often causes the desirable low-velocity forging condition difficult to obtaln. So far little work has been found to estimate the dynamic response of the forging process under low velocity. In this paper, an approximate-model based estimation method is proposed to estimate the dynamic response of the forging process under low velocity. First, an approximate model is developed to represent the forging process of this complex HPM around the low-velocity working point. Under guaranteeing the modeling performance, the model may greatly ease the complexity of the subsequent estimation of the dynamic response because it has a good linear structure. On this basis, the dynamic response is estimated and the conditions for stability, vibration, and creep are derived according to the solution of the velocity. All these analytical results are further verified by both simulations and experiment. In the simulation verification for modeling, the original movement model and the derived approximate model always have the same dynamic responses with very small approximate error. The simulations and experiment finally demonstrate and test the effectiveness of the derived conditions for stability, vibration, and creep, and these conditions will benefit both the prediction of the dynamic response of the forging process and the design of the controller for the high-quality forging. The proposed method is an effective solution to achieve the desirable low-velocity forging condition.
Gravitational-wave dynamics and black-hole dynamics: second quasi-spherical approximation
Hayward, Sean A.
2001-01-01
Gravitational radiation with roughly spherical wavefronts, produced by roughly spherical black holes or other astrophysical objects, is described by an approximation scheme. The first quasi-spherical approximation, describing radiation propagation on a background, is generalized to include additional non-linear effects, due to the radiation itself. The gravitational radiation is locally defined and admits an energy tensor, satisfying all standard local energy conditions and entering the trunc...
Neuro-dynamic programming for the efficient management of reservoir networks
de Rigo, Daniele; Rizzoli, Andrea Emilio; Soncini-Sessa, Rodolfo; Weber, Enrico; Zenesi, Pietro
2001-01-01
Significance This article introduced in 2001 one of the very first successful applications of advanced machine learning techniques to solve complex, multicriteria management problems in water resources dealing with networks of water reservoirs. It applied approximate dynamic programming (here, neuro-dynamic programming - whose approximation of stochastic dynamic programming relies on artificial neural networks) to the integrated water resources management. The methodology is general enoug...
Energy Technology Data Exchange (ETDEWEB)
Shirdel-Havar, A. H., E-mail: Amir.hushang.shirdel@gmail.com; Masoudian Saadabad, R. [Department of Physics, University of Sistan and Baluchestan, Zahedan 98135-674 (Iran, Islamic Republic of)
2015-03-21
Based on ballistic-diffusive approximation, a method is presented to model heat transfer in nanocomposites containing metal nanoparticles. This method provides analytical expression for the temperature dynamics of metallic nanoparticles embedded in a dielectric medium. In this study, nanoparticles are considered as spherical shells, so that Boltzmann equation is solved using ballistic-diffusive approximation to calculate the electron and lattice thermal dynamics in gold nanoparticles, while thermal exchange between the particles is taken into account. The model was used to investigate the influence of particle size and metal concentration of the medium on the electron and lattice thermal dynamics. It is shown that these two parameters are crucial in determining the nanocomposite thermal behavior. Our results showed that the heat transfer rate from nanoparticles to the matrix decreases as the nanoparticle size increases. On the other hand, increasing the metal concentration of the medium can also decrease the heat transfer rate.
International Nuclear Information System (INIS)
Based on ballistic-diffusive approximation, a method is presented to model heat transfer in nanocomposites containing metal nanoparticles. This method provides analytical expression for the temperature dynamics of metallic nanoparticles embedded in a dielectric medium. In this study, nanoparticles are considered as spherical shells, so that Boltzmann equation is solved using ballistic-diffusive approximation to calculate the electron and lattice thermal dynamics in gold nanoparticles, while thermal exchange between the particles is taken into account. The model was used to investigate the influence of particle size and metal concentration of the medium on the electron and lattice thermal dynamics. It is shown that these two parameters are crucial in determining the nanocomposite thermal behavior. Our results showed that the heat transfer rate from nanoparticles to the matrix decreases as the nanoparticle size increases. On the other hand, increasing the metal concentration of the medium can also decrease the heat transfer rate
Gravitational-wave dynamics and black-hole dynamics second quasi-spherical approximation
Hayward, S A
2001-01-01
Gravitational radiation with roughly spherical wavefronts, produced by roughly spherical black holes or other astrophysical objects, is described by an approximation scheme. The first quasi-spherical approximation, describing radiation propagation on a background, is generalized to include additional non-linear effects, due to the radiation itself. The gravitational radiation is locally defined and admits an energy tensor, satisfying all standard local energy conditions and entering the truncated Einstein equations as an effective energy tensor. This second quasi-spherical approximation thereby includes gravitational radiation reaction, such as the back-reaction on the black hole. With respect to a canonical flow of time, the combined energy-momentum of the matter and gravitational radiation is covariantly conserved. The corresponding Noether charge is a local gravitational mass-energy. Energy conservation is formulated as a local first law relating the gradient of the gravitational mass to work and energy-su...
BUILDING MATHEMATICAL MODELS IN DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
LIANA RODICA PATER
2012-05-01
Full Text Available In short, we can say that dynamic programming is a method of optimization of systems, using their mathematical representation in phases or sequences or as we say, periods. Such systems are common in economic studies at the implementation of programs on the most advanced techniques, such as for example that involving cosmic navigation. Another concept that is involved in the study of dynamic programs is the economic horizon (number of periods or phases that a dynamic program needs. This concept often leads to the examination of the convergence of certain variables on infinite horizon. In many cases from the real economy by introducing updating, dynamic programs can be made convergent.
Improved Approximation of Interactive Dynamic Influence DiagramsUsing Discriminative Model Updates
DEFF Research Database (Denmark)
Prashant, Doshi; Zeng, Yifeng
2009-01-01
Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. We formalize...... the concept of a minimal model set, which facilitates qualitative comparisons between different approximation techniques. We then present a new approximation technique that minimizes the space of candidate models by discriminating between model updates. We empirically demonstrate that our approach improves...
Dynamics of Zonal Flows: Failure of Wave-Kinetic Theory, and New Geometrical Optics Approximations
Parker, Jeffrey B
2016-01-01
The self-organization of turbulence into regular zonal flows can be fruitfully investigated with quasilinear methods and statistical descriptions. A wave kinetic equation that assumes asymptotically large-scale zonal flows is pathological. From an exact description of quasilinear dynamics emerges two better geometrical optics approximations. These involve not only the mean flow shear but also the second and third derivative of the mean flow. One approximation takes the form of a new wave kinetic equation, but is only valid when the zonal flow is quasi-static and wave action is conserved.
Approximation-Exact Penalty Function Method for Solving a Class of Stochastic Programming
Institute of Scientific and Technical Information of China (English)
Wang Guang-min; Wan Zhong-ping
2003-01-01
We present an approximation-exact penalty function method for solving the single stage stochastic programming problem with continuous random variable. The original problem is transformed into a determinate nonlinear programming problem with a discrete random variable sequence, which is obtained by some discrete method. We construct an exact penalty function and obtain an unconstrained optimization. It avoids the difficulty in solution by the rapid growing of the number of constraints for discrete precision. Under lenient conditions, we prove the equivalence of the minimum solution of penalty function and the solution of the determinate programming, and prove that the solution sequences of the discrete problem converge to a solution to the original problem.
Rossi, Mariana; Paesani, Francesco; Bowman, Joel; Ceriotti, Michele
2014-01-01
Including quantum mechanical effects on the dynamics of nuclei in the condensed phase is challenging, because the complexity of exact methods grows exponentially with the number of quantum degrees of freedom. Efforts to circumvent these limitations can be traced down to two approaches: methods that treat a small subset of the degrees of freedom with rigorous quantum mechanics, considering the rest of the system as a static or classical environment, and methods that treat the whole system quantum mechanically, but using approximate dynamics. Here we perform a systematic comparison between these two philosophies for the description of quantum effects in vibrational spectroscopy, taking the Embedded Local Monomer (LMon) model and a mixed quantum-classical (MQC) model as representatives of the first family of methods, and centroid molecular dynamics (CMD) and thermostatted ring polymer molecular dynamics (TRPMD) as examples of the latter. We use as benchmarks D$_2$O doped with HOD and pure H$_2$O at three distinc...
Dynamic Programming Applications in Water Resources
Yakowitz, Sidney
1982-08-01
The central intention of this survey is to review dynamic programming models for water resource problems and to examine computational techniques which have been used to obtain solutions to these problems. Problem areas surveyed here include aqueduct design, irrigation system control, project development, water quality maintenance, and reservoir operations analysis. Computational considerations impose severe limitation on the scale of dynamic programming problems which can be solved. Inventive numerical techniques for implementing dynamic programming have been applied to water resource problems. Discrete dynamic programming, differential dynamic programming, state incremental dynamic programming, and Howard's policy iteration method are among the techniques reviewed. Attempts have been made to delineate the successful applications, and speculative ideas are offered toward attacking problems which have not been solved satisfactorily.
Cascade statistics in the binary collision approximation and in full molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Hou, M. [Universite Libre de Bruxelles (Belgium). Physique des Solides Irradies; Pan, Z.Y. [Fudan Univ., Shanghai (China). Dept. of Physics
1995-08-01
The Binary Collision Approximation (BCA) and Molecular Dynamics (MD) are used to simulate low energy atomic collision cascades in solids. Results are compared and discussed on the example of copper and gold self irradiation. For MD, long range N-body potentials are built, similar to those deduced from the second moment semi-empirical tight binding model. The pair interaction contribution is splined to a Moliere screened Coulomb potential at small separation distances. The BCA calculations are performed with the MARLOWE program, using the same Moliere potential as for MD, and modelling the N-body contribution by a binding of the atoms to their equilibrium lattice sites. The scattering integrals are estimated by means of a 4 points Gauss-Mehler quadrature. In MD, the NVT equations of motion are integrated with a constant time step of 2 fs. For the NVE cascade simulations, the Newton equations of motion are solved with a dynamically adjusted time step, kept lower than 2 fs. The influence of the time step on the simulated trajectories is discussed. The mean number of moving atoms with total energy above threshold values ranging from 1 to 100 eV is estimated as a function of time over 300 fs both with MARLOWE and by MD. This estimate is repeated for external primary energies ranging from 250 eV to 1 keV. In the case of copper, the BCA results are found to be in remarkable agreement with MD over about 200 fs cascade development, provided the size of the crystallite used in MD is sufficiently large in order to account for the early mechanical response of the close environment. This agreement between the two methods is found to be the best when the binding energy of the target atoms as modelled in the BCA is adjusted to a value close to the cohesive energy. In the case of gold, the agreement between BCA and MD is reasonable and the results suggest the need of an accurate modelling of linear collision sequences in the BCA. (orig.).
Methods and tools for simplified dynamic simulations in real time based on expression approximation
Directory of Open Access Journals (Sweden)
Štefan M.
2007-10-01
Full Text Available The core of this paper is the methodology of the dynamicalmodels’ simplification for the real time simulation. The simplified simulation models are based on neuro-fuzzymodelling approach, which was originally designed for predictive control-orientedmodelling of nonlinear dynamical systems. The two ways of the neuro-fuzzymodelling utilization are presented. First, the training of the predictive dynamical neuro-fuzzymodel and, second, the training of the statical approximation of the right-hand side of the system’s state space description. We demonstrate the results on the examples of nonlinear spring damper system and double pendulum.
Approximate but Accurate Quantum Dynamics from the Mori Formalism: I. Nonequilibrium Dynamics
Montoya-Castillo, Andrés
2016-01-01
We present a formalism that explicitly unifies the commonly used Nakajima-Zwanzig approach for reduced density matrix dynamics with the more versatile Mori theory in the context of nonequilibrium dynamics. Employing a Dyson-type expansion to circumvent the difficulty of projected dynamics, we obtain a self-consistent equation for the memory kernel which requires only knowledge of normally evolved auxiliary kernels. To illustrate the properties of the current approach, we focus on the spin-boson model and limit our attention to the use of a simple and inexpensive quasi-classical dynamics, given by the Ehrenfest method, for the calculation of the auxiliary kernels. For the first time, we provide a detailed analysis of the dependence of the properties of the memory kernels obtained via different projection operators, namely the thermal (Redfield-type) and population based (NIBA-type) projection operators. We further elucidate the conditions that lead to short-lived memory kernels and the regions of parameter spa...
Classical dynamics of a charged particle in a laser field beyond the dipole approximation
Jameson, Paul; Khvedelidze, Arsen
2008-01-01
The classical dynamics of a charged particle traveling in a laser field modeled by an elliptically polarized monochromatic electromagnetic plane wave is discussed within the time reparametrization invariant form of the non-relativistic Hamilton-Jacobi theory. The exact parametric representation for a particle's orbit in an arbitrary plane wave background beyond the dipole approximation and including effect of the magnetic field is derived. For an elliptically polarized monochromatic plane wav...
A dynamic subgrid-scale modeling framework for large eddy simulation using approximate deconvolution
Maulik, Romit
2016-01-01
We put forth a dynamic modeling framework for sub-grid parametrization of large eddy simulation of turbulent flows based upon the use of the approximate deconvolution procedure to compute the Smagorinsky constant self-adaptively from the resolved flow quantities. Our numerical assessments for solving the Burgers turbulence problem shows that the proposed approach could be used as a viable tool to address the turbulence closure problem due to its flexibility.
Dynamic Slicing of Object-Oriented Programs
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Program slice has many applications such as program debugging,testing, maintena n ce, and complexity measurement. A static slice consists of all statements in pro gram P that may effect the value of variable v at some point p, and a dynamic s lice consists only of statements that influence the value of variable occurrence for specific program inputs. In this paper, we concern the problem of dynamic s licing of object-oriented programs which, to our knowledge, has not been addres s ed in the literatures. To solve this problem, we present the dynamic object-ori e nted dependence graph (DODG)which is an arc-classified digraph to explicitly re p resent various dynamic dependence between statement instances for a particular e xecution of an object-oriented program. Based on the DODG, we present a two-ph as e backward algorithm for computing a dynamic slice of an object-oriented program.
Semantic Predicate Types and Approximation for Class-based Object Oriented Programming
van Bakel, Steffen
2011-01-01
We apply the principles of the intersection type discipline to the study of class-based object oriented programs and; our work follows from a similar approach (in the context of Abadi and Cardelli's Varsigma-object calculus) taken by van Bakel and de'Liguoro. We define an extension of Featherweight Java, FJc and present a predicate system which we show to be sound and expressive. We also show that our system provides a semantic underpinning for the object oriented paradigm by generalising the concept of approximant from the Lambda Calculus and demonstrating an approximation result: all expressions to which we can assign a predicate have an approximant that satisfies the same predicate. Crucial to this result is the notion of predicate language, which associates a family of predicates with a class.
A Discrete Meta-Control Procedure for Approximating Solutions to Binary Programs
Directory of Open Access Journals (Sweden)
Zelda B. Zabinsky
2013-09-01
Full Text Available Large-scale binary integer programs occur frequently in many real-world applications. For some binary integer problems, finding an optimal solution or even a feasible solution is computationally expensive. In this paper, we develop a discrete meta-control procedure to approximately solve large-scale binary integer programs efficiently. The key idea is to map the vector of n binary decision variables into a scalar function defined over a time interval [0; n] and construct a linear quadratic tracking (LQT problem that can be solved efficiently. We prove that an LQT formulation has an optimal binary solution, analogous to a classical bang-bang control in continuous time. Our LQT approach can provide advantages in reducing computation while generating a good approximate solution. Numerical examples are presented to demonstrate the usefulness of the proposed method.
Weak Dynamic Programming Principle for Viscosity Solutions
Bouchard, Bruno; Touzi, Nizar
2011-01-01
We prove a weak version of the dynamic programming principle for standard stochastic control problems and mixed control-stopping problems, which avoids the technical difficulties related to the measurable selection argument. In the Markov case, our result is tailor-maid for the derivation of the dynamic programming equation in the sense of viscosity solutions.
Genomic Signal Search by Dynamic Programming
Institute of Scientific and Technical Information of China (English)
ZHENG Wei-Mou
2003-01-01
A general and flexible multi-motif model is proposed based on dynamic programming. By extending theGibbs sampler to the dynamic programming and introducing temperature, an efficient algorithm is developed. Branchpoint signalsequences and translation initiation sequences extracted from the rice genome are then examined.
Pusok, Adina E.; Kaus, Boris J. P.; Popov, Anton A.
2016-04-01
Most of the major mountain belts and orogenic plateaus are found within the overlying plate of active or fossil subduction and/or collision zones. Moreover, they evolve differently from one another as the result of specific combinations of surface and mantle processes. These differences arise for several reasons, such as different rheological properties, different amounts of regional isostatic compensation, and different mechanisms by which forces are applied to the convergent plates. Previous 3D geodynamic models of subduction/collision processes have used various rheological approximations, making numerical results difficult to compare, since there is no clear image on the extent of these approximations on the dynamics. Here, we employ the code LaMEM to perform high-resolution long-term 3D simulations of subduction/continental collision in an integrated lithospheric and upper-mantle scale model. We test the effect of rheological approximations on mantle and lithosphere dynamics in a geometrically simplified model setup that resembles a tectonic map of the India-Asia collision zone. We use the "sticky-air" approach to allow for the development of topography and the dynamics of subduction and collision is entirely driven by slab-pull (i.e. "free subduction"). The models exhibit a wide range of behaviours depending on the rheological law employed: from linear to temperature-dependent visco-elasto-plastic rheology that takes into account both diffusion and dislocation creep. For example, we find that slab dynamics varies drastically between end member models: in viscous approximations, slab detachment is slow following a viscous thinning, while for a non-linear visco-elasto-plastic rheology, slab detachment is relatively fast, inducing strong mantle flow in the slab window. We also examine the stress states in the subducting and overriding plates and topography evolution in the upper plate, and we discuss the implications on lithosphere dynamics at convergent margins
Approximating Model Equivalence in Interactive Dynamic Influence Diagrams Using Top K Policy Paths
DEFF Research Database (Denmark)
Zeng, Y.; Chen, Y.; Doshi, Prashant
2011-01-01
Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of behavioral models ascribed to other agents over time. Previous...... approaches mainly cluster behaviorally equivalent models to reduce the complexity of I-DID solutions. In this paper, we seek to further reduce the model space by introducing an approximate measure of behavioral equivalence (BE) and using it to group models. Specifically, we focus on $K$ most probable paths...... in the solution of each model and compare these policy paths to determine approximate BE. We discuss the challenges in computing the top $K$ policy paths and experimentally evaluate the performance of this heuristic approach in terms of the scalability and quality of the solution....
Cosmological dynamics: from the Eulerian to the Lagrangian frame. Part I. Newtonian approximation
International Nuclear Information System (INIS)
We analyse the non-linear gravitational dynamics of a pressure-less fluid in the Newtonian limit of General Relativity in both the Eulerian and Lagrangian pictures. Starting from the Newtonian metric in the Poisson gauge, we transform to the synchronous and comoving gauge and obtain the Lagrangian metric within the Newtonian approximation. Our approach is fully non-perturbative, which implies that if our quantities are expanded according to the rules of standard perturbation theory, all terms are exactly recovered at any order in perturbation theory, only provided they are Newtonian. We explicitly show this result up to second order and in both gauges. Our transformation clarifies the meaning of the change of spatial and time coordinates from the Eulerian to the Lagrangian frame in the Newtonian approximation
Approximation-Exact Penalty Function Method for Solving a Class of Stochastic Programming
Institute of Scientific and Technical Information of China (English)
WangGuang-min; WanZhong-ping
2003-01-01
We present an approximation-exact penalty function method for solving the single stage stochastic programming problem with continuous random variable. The original problem is transformed into a determinate nonlinear programming problem with a discrete random variable sequence, which is obtained by some discrete method. We construct an exact penalty function and obtain an unconstrained optimization. It avoids the difficulty in solution by the rapid growing of the number of constraints for discrete precision.Under lenient conditions, we prove the equivalence of the minimum solution of penalty function and the solution of the determinate programming, and prove that the solution sequences of the discrete problem converge to a solution to the original problem.
Dynamics of Jaynes-Cummings Model in the Absence of Rotating-Wave Approximation
Institute of Scientific and Technical Information of China (English)
FAN Yun-Xia; LIU Tao; FENG Mang; WANG Ke-Lin
2007-01-01
The Jaynes-Cummings model (JCM) is studied in the absence of the rotating-wave approximation (RWA)by a coherent-state expansion technique. In comparison with the previous paper in which the coherent-state expansion was performed only to the third order, we carry out in this paper a complete expansion to demonstrate exactly the dynamics of the JCM without the RWA. Our study gives a systematic method to solve the non-RWA problem, which would be useful in various physical systems, e.g., in a system with an ultracold trapped ion experiencing the running waves of lasers.
Jiang, Bin; Song, Hongwei; Yang, Minghui; Guo, Hua
2016-04-01
The quantum dynamics of water dissociative chemisorption on the rigid Ni(111) surface is investigated using a recently developed nine-dimensional potential energy surface. The quantum dynamical model includes explicitly seven degrees of freedom of D2O at fixed surface sites, and the final results were obtained with a site-averaging model. The mode specificity in the site-specific results is reported and analyzed. Finally, the approximate sticking probabilities for various vibrationally excited states of D2O are obtained considering surface lattice effects and formally all nine degrees of freedom. The comparison with experiment reveals the inaccuracy of the density functional theory and suggests the need to improve the potential energy surface.
Van Raemdonck, Mario; Alcoba, Diego R; Poelmans, Ward; De Baerdemacker, Stijn; Torre, Alicia; Lain, Luis; Massaccesi, Gustavo E; Van Neck, Dimitri; Bultinck, Patrick
2015-09-14
A class of polynomial scaling methods that approximate Doubly Occupied Configuration Interaction (DOCI) wave functions and improve the description of dynamic correlation is introduced. The accuracy of the resulting wave functions is analysed by comparing energies and studying the overlap between the newly developed methods and full configuration interaction wave functions, showing that a low energy does not necessarily entail a good approximation of the exact wave function. Due to the dependence of DOCI wave functions on the single-particle basis chosen, several orbital optimisation algorithms are introduced. An energy-based algorithm using the simulated annealing method is used as a benchmark. As a computationally more affordable alternative, a seniority number minimising algorithm is developed and compared to the energy based one revealing that the seniority minimising orbital set performs well. Given a well-chosen orbital basis, it is shown that the newly developed DOCI based wave functions are especially suitable for the computationally efficient description of static correlation and to lesser extent dynamic correlation.
DYNAMICAL SPIN SUSCEPTIBILITY IN THE TD-LDA AND QSGW APPROXIMATIONS
Energy Technology Data Exchange (ETDEWEB)
SCHILFGAARDE, MARK VAN; KOTANI, TAKAO
2012-10-15
Abstract. This project was aimed at building the transverse dynamical spin susceptibility with the TD-LDA and the recently-developed Quasparticle Self-Consisent Approximations, which determines an optimum quasiparticle picture in a self-consistent manner within the GW approximation. Our main results were published into two papers, (J. Phys. Cond. Matt. 20, 95214 (2008), and Phys. Rev. B83, 060404(R) (2011). In the first paper we present spin wave dispersions for MnO, NiO, and -MnAs based on quasiparticle self-consistent GW approximation (QSGW). For MnO and NiO, QSGW results are in rather good agreement with experiments, in contrast to the LDA and LDA+U descriptions. For -MnAs, we find a collinear ferromagnetic ground state in QSGW, while this phase is unstable in the LDA. In the second, we apply TD-LDA to the CaFeAs2 Ã¢ÂÂ the first attempt the first ab initio calculation of dynamical susceptibililty in a system with complex electronic structure Magnetic excitations in the striped phase of CaFe2As2 are studied as a function of local moment amplitude. We find a new kind of excitation: sharp resonances of Stoner-like (itinerant) excitations at energies comparable to the NÃÂ´eel temperature, originating largely from a narrow band of Fe d states near the Fermi level, and coexisting with more conventional (localized) spin waves. Both kinds of excitations can show multiple branches, highlighting the inadequacy of a description based on a localized spin model.
DYNAMICAL SPIN SUSCEPTIBILITY IN THE TD-LDA AND QSGW APPROXIMATIONS
Energy Technology Data Exchange (ETDEWEB)
SCHILFGAARDE, MARK VAN; KOTANI, TAKAO
2012-10-15
Abstract. This project was aimed at building the transverse dynamical spin susceptibility with the TD-LDA and the recently-developed Quasparticle Self-Consisent Approximations, which determines an optimum quasiparticle picture in a self-consistent manner within the GW approximation. Our main results were published into two papers, (J. Phys. Cond. Matt. 20, 95214 (2008), and Phys. Rev. B83, 060404(R) (2011). In the first paper we present spin wave dispersions for MnO, NiO, and -MnAs based on quasiparticle self-consistent GW approximation (QSGW). For MnO and NiO, QSGW results are in rather good agreement with experiments, in contrast to the LDA and LDA+U descriptions. For -MnAs, we find a collinear ferromagnetic ground state in QSGW, while this phase is unstable in the LDA. In the second, we apply TD-LDA to the CaFeAs2 the first attempt the first ab initio calculation of dynamical susceptibililty in a system with complex electronic structure Magnetic excitations in the striped phase of CaFe2As2 are studied as a function of local moment amplitude. We find a new kind of excitation: sharp resonances of Stoner-like (itinerant) excitations at energies comparable to the ´eel temperature, originating largely from a narrow band of Fe d states near the Fermi level, and coexisting with more conventional (localized) spin waves. Both kinds of excitations can show multiple branches, highlighting the inadequacy of a description based on a localized spin model.
Impact of nonlocal correlations over different energy scales: A dynamical vertex approximation study
Rohringer, G.; Toschi, A.
2016-09-01
In this paper, we investigate how nonlocal correlations affect, selectively, the physics of correlated electrons over different energy scales, from the Fermi level to the band edges. This goal is achieved by applying a diagrammatic extension of dynamical mean field theory (DMFT), the dynamical vertex approximation (D Γ A ), to study several spectral and thermodynamic properties of the unfrustrated Hubbard model in two and three dimensions. Specifically, we focus first on the low-energy regime by computing the electronic scattering rate and the quasiparticle mass renormalization for decreasing temperatures at a fixed interaction strength. This way, we obtain a precise characterization of the several steps through which the Fermi-liquid physics is progressively destroyed by nonlocal correlations. Our study is then extended to a broader energy range, by analyzing the temperature behavior of the kinetic and potential energy, as well as of the corresponding energy distribution functions. Our findings allow us to identify a smooth but definite evolution of the nature of nonlocal correlations by increasing interaction: They either increase or decrease the kinetic energy w.r.t. DMFT depending on the interaction strength being weak or strong, respectively. This reflects the corresponding evolution of the ground state from a nesting-driven (Slater) to a superexchange-driven (Heisenberg) antiferromagnet (AF), whose fingerprints are, thus, recognizable in the spatial correlations of the paramagnetic phase. Finally, a critical analysis of our numerical results of the potential energy at the largest interaction allows us to identify possible procedures to improve the ladder-based algorithms adopted in the dynamical vertex approximation.
Institute of Scientific and Technical Information of China (English)
He Zhuo-Ran; Wu Tai-Lin; Ouyang Qi; Tu Yu-Hai
2012-01-01
Recent extensive studies of Escherichia coli (E.coli) chemotaxis have achieved a deep understanding of its microscopic control dynamics.As a result,various quantitatively predictive models have been developed to describe the chemotactic behavior of E.coli motion.However,a population-level partial differential equation (PDE) that rationally incorporates such microscopic dynamics is still insufficient.Apart from the traditional Keller-Segel (K-S) equation,many existing population-level models developed from the microscopic dynamics are integro-PDEs.The difficulty comes mainly from cell tumbles which yield a velocity jumping process.Here,we propose a Langevin approximation method that avoids such a difficulty without appreciable loss of precision.The resulting model not only quantitatively reproduces the results of pathway-based single-cell simulators,but also provides new inside information on the mechanism of E.coli chemotaxis.Our study demonstrates a possible alternative in establishing a simple population-level model that allows for the complex microscopic mechanisms in bacterial chemotaxis.
Integrating Pareto Optimization into Dynamic Programming
Thomas Gatter; Robert Giegerich; Cédric Saule
2016-01-01
Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when scoring schemes A and B can correctly evaluate the search space via dynamic programming, then so can Pareto optimization with respect to A and B. However, the integration of Pareto optimization into ...
Adaptive dynamic programming for linear impulse systems
Institute of Scientific and Technical Information of China (English)
Xiao-hua WANG; Juan-juan YU; Yao HUANG; Hua WANG; Zhong-hua MIAO
2014-01-01
We investigate the optimization of linear impulse systems with the reinforcement learning based adaptive dynamic programming (ADP) method. For linear impulse systems, the optimal objective function is shown to be a quadric form of the pre-impulse states. The ADP method provides solutions that iteratively converge to the optimal objective function. If an initial guess of the pre-impulse objective function is selected as a quadratic form of the pre-impulse states, the objective function iteratively converges to the optimal one through ADP. Though direct use of the quadratic objective function of the states within the ADP method is theoretically possible, the numerical singularity problem may occur due to the matrix inversion therein when the system dimensionality increases. A neural network based ADP method can circumvent this problem. A neural network with polynomial activation functions is selected to approximate the pre-impulse objective function and trained iteratively using the ADP method to achieve optimal control. After a successful training, optimal impulse control can be derived. Simulations are presented for illustrative purposes.
Integrating Pareto Optimization into Dynamic Programming
Directory of Open Access Journals (Sweden)
Thomas Gatter
2016-01-01
Full Text Available Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when scoring schemes A and B can correctly evaluate the search space via dynamic programming, then so can Pareto optimization with respect to A and B. However, the integration of Pareto optimization into dynamic programming opens a wide range of algorithmic alternatives, which we study in substantial detail in this article, using real-world applications in biosequence analysis, a field where dynamic programming is ubiquitous. Our results are two-fold: (1 We introduce the operation of a “Pareto algebra product” in the dynamic programming framework of Bellman’s GAP. Users of this framework can now ask for Pareto optimization with a single keystroke. Careful evaluation of the implementation alternatives by means of an extended Bellman’s GAP compiler demonstrates the dependence of the best implementation choice on the application at hand. (2 We extract from our experiments several pieces of advice to programmers who do not use a system such as Bellman’s GAP, but who choose to hand-craft their dynamic programming recurrences, incorporating Pareto optimization from scratch.
Dynamic Programming: An Introduction by Example
Zietz, Joachim
2007-01-01
The author introduces some basic dynamic programming techniques, using examples, with the help of the computer algebra system "Maple". The emphasis is on building confidence and intuition for the solution of dynamic problems in economics. To integrate the material better, the same examples are used to introduce different techniques. One covers the…
Guidelines for dynamic international programs
International Nuclear Information System (INIS)
Matters of global concern-deforestation, global warming, biodiversity loss, sustainable development, fuelwood crises, watershed destruction, and large-scale flooding-frequently involve forests and natural resources. In the future, university students will enter a global setting that more than ever depends on a strong knowledge of international issues. USA land-grant universities are attempting to prepare students for this challenge by improving their international programs including forestry. To improve university programs, several factors will need to be addressed and are discussed, with examples, in this article: commitment of the faculty; program specialization; geographic specialization; reward systems for international contributions; international collaboration; recycled dollars within the university; active teaching programs; research; extention and outreach; language training; international faculty; travel grants; twinning relationships with sister institutions; selective in pursuit of international development assistance; and study centers. 6 refs
Synthesis of Large Dynamic Concurrent Programs from Dynamic Specifications
Attie, Paul C.
2008-01-01
We present a tractable method for synthesizing arbitrarily large concurrent programs, for a shared memory model with common hardware-available primitives such as atomic registers, compare-and-swap, load-linked/store conditional, etc. The programs we synthesize are dynamic: new processes can be created and added at run-time, and so our programs are not finite-state, in general. Nevertheless, we successfully exploit automatic synthesis and model-checking methods based on propositional temporal ...
Classical dynamics of a charged particle in a laser field beyond the dipole approximation
Jameson, Paul
2008-01-01
The classical dynamics of a charged particle traveling in a laser field modeled by an elliptically polarized monochromatic electromagnetic plane wave is discussed within the time reparametrization invariant form of the non-relativistic Hamilton-Jacobi theory. The exact parametric representation for a particle's orbit in an arbitrary plane wave background beyond the dipole approximation and including effect of the magnetic field is derived. For an elliptically polarized monochromatic plane wave the particle's trajectory, as an explicit function of the laboratory frame's time, is given in terms of the Jacobian elliptic functions, whose modulus is proportional to the laser's intensity and depends on the polarization of radiation. It is shown that the system exposes the ``intensity duality'', correspondence between the motion in the backgrounds with various intensities. In virtue of the modular properties of the Jacobian functions, by starting with the representative ``fundamental solution'' and applying a certai...
The dynamics of a spinning particle in a linear in spin Hamiltonian approximation
Lukes-Gerakopoulos, Georgios; Patsis, Panos A; Seyrich, Jonathan
2016-01-01
We investigate for order and chaos the dynamical system of a spinning test particle of mass $m$ moving in the spacetime background of a Kerr black hole of mass M. This system is approximated in our investigation by the linear in spin Hamiltonian function provided in [E. Barausse, and A. Buonanno, Phys.Rev. D 81, 084024 (2010)]. We study the corresponding phase space by using 2D projections on a surface of section and the method of color and rotation on a 4D Poincar\\'e section. Various topological structures coming from the non-integrability of the linear in spin Hamiltonian are found and discussed. Moreover, an interesting result is that from the value of the dimensionless spin $S/(m M)=10^{-4}$ of the particle and below, the impact of the non-integrability of the system on the motion of the particle seems to be negligible.
Object Tracking System Using Approximate Median Filter, Kalman Filter and Dynamic Template Matching
Directory of Open Access Journals (Sweden)
G. Mallikarjuna Rao
2014-04-01
Full Text Available In this work, we dealt with the tracking of single object in a sequence of frames either from a live camera or a previously saved video. A moving object is detected frame-by-frame with high accuracy and efficiency using Median approximation technique. As soon as the object has been detected, the same is tracked by kalman filter estimation technique along with a more accurate Template Matching algorithm. The templates are dynamically generated for this purpose. This guarantees any change in object pose which does not be hindered from tracking procedure. The system is capable of handling entry and exit of an object. Such a tracking scheme is cost effective and it can be used as an automated video conferencing system and also has application as a surveillance tool. Several trials of the tracking show that the approach is correct and extremely fast, and it's a more robust performance throughout the experiments.
DEFF Research Database (Denmark)
Ruban, V.P.; Senchenko, Sergey
2004-01-01
The evolution of piecewise constant distributions of a conserved quantity related to the frozen-in canonical vorticity in effectively two-dimensional incompressible ideal EMHD flows is analytically investigated by the Hamiltonian method. The study includes the case of axisymmetric flows with zero...... azimuthal velocity component and also the case of flows with the helical symmetry of vortex lines. For sufficiently large size of such a patch of the conserved quantity. a local approximation in the dynamics of the patch boundary is suggested, based on the possibility to represent the total energy...... as the sum of area and boundary terms. Only the boundary energy produces deformation of the shape with time. Stationary moving configurations are described....
Montoya-Castillo, Andrés
2016-01-01
The ability to efficiently and accurately calculate equilibrium time correlation functions of many-body condensed phase quantum systems is one of the outstanding problems in theoretical chemistry. The Nakajima-Zwanzig-Mori formalism coupled to the self-consistent solution of the memory kernel has recently proven to be highly successful for the computation of nonequilibrium dynamical averages. Here, we extend this formalism to treat symmetrized equilibrium time correlation functions for the spin-boson model. Following the first paper in this series [A. Montoya-Castillo and D. R. Reichman, J. Chem. Phys. $\\bf{144}$, 184104 (2016)], we use a Dyson-type expansion of the projected propagator to obtain a self-consistent solution for the memory kernel that requires only the calculation of normally evolved auxiliary kernels. We employ the approximate mean-field Ehrenfest method to demonstrate the feasibility of this approach. Via comparison with numerically exact results for the correlation function $\\mathcal{C}_{zz}...
Kosmala, Margaret; Miller, Philip; Ferreira, Sam; Funston, Paul; Keet, Dewald; Packer, Craig
2016-01-01
Emerging infectious diseases of wildlife are of increasing concern to managers and conservation policy makers, but are often difficult to study and predict due to the complexity of host-disease systems and a paucity of empirical data. We demonstrate the use of an Approximate Bayesian Computation statistical framework to reconstruct the disease dynamics of bovine tuberculosis in Kruger National Park's lion population, despite limited empirical data on the disease's effects in lions. The modeling results suggest that, while a large proportion of the lion population will become infected with bovine tuberculosis, lions are a spillover host and long disease latency is common. In the absence of future aggravating factors, bovine tuberculosis is projected to cause a lion population decline of ~3% over the next 50 years, with the population stabilizing at this new equilibrium. The Approximate Bayesian Computation framework is a new tool for wildlife managers. It allows emerging infectious diseases to be modeled in complex systems by incorporating disparate knowledge about host demographics, behavior, and heterogeneous disease transmission, while allowing inference of unknown system parameters.
Computer program for flexible rotor dynamics analysis
Shen, F. A.
1974-01-01
Program analyzes general nonaxisymmetric and nonsynchronous transient and steady-state rotor dynamic performance of bending- and shear-wise flexible rotor-bearing system under various operating conditions. Program can be used as analytical study tool for general transient spin-speed and/or non-axisymmetric rotor motion.
Hybrid Differential Dynamic Programming with Stochastic Search
Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob
2016-01-01
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
Analytical descriptions of cross-polarisation dynamics: relaxing the secular approximations
Hirschinger, J.; Raya, J.
2015-11-01
In this work, analytical expressions of the cross-polarisation (CP) dynamics under both static and magic-angle spinning (MAS) conditions are obtained by solving the generalised Liouville-von Neumann quantum mechanical equation beyond the standard approximations, i.e., reintroducing neglected non-secular terms in the system superoperator. Although the simple model of a two-spin system interacting with a spin bath gives a rather crude description of CP dynamics, it accounts well for the orientation dependence of CP in a static sample of ferrocene powder and permits to detect slight departures from the Hartmann-Hahn matching condition. This approach also has the advantage of yielding manageable analytical expressions that can be used even by less inclined or experienced workers to obtain results that are good enough in an operational sense. Moreover, the resulting spin diffusion rate constants containing different sources of anisotropy of the system-environment interaction as well as their dependence on the MAS frequency are related semi-quantitatively to the local network of dipolar interactions. Finally, it is shown that non-secular solutions improve significantly the analysis of CPMAS-based separated-local-field spectroscopy experimental data in the absence of homonuclear decoupling.
Parkhill, John A; Tempel, David G; Aspuru-Guzik, Alan
2012-01-01
In this work we develop a theory of correlated many-electron dynamics dressed by the presence of a finite-temperature harmonic bath. The theory is based on the ab-initio Hamiltonian, and thus well-defined apart from any phenomenological choice of collective basis states or electronic coupling model. The equation-of-motion includes some bath effects non-perturbatively, and can be used to simulate line- shapes beyond the Markovian approximation and open electronic dynamics which are subjects of renewed recent interest. Energy conversion and transport depend critically on the ratio of electron-electron coupling to bath-electron coupling, which is a fitted parameter if a phenomenological basis of many-electron states is used to develop an electronic equation of motion. Since the present work doesn't appeal to any such basis, it avoids this ambiguity. The new theory produces a level of detail beyond the adiabatic Born-Oppenheimer states, but with cost scaling like the Born-Oppenheimer approach. While developing th...
Garvie, Marcus R; Burkardt, John; Morgan, Jeff
2015-03-01
We describe simple finite element schemes for approximating spatially extended predator-prey dynamics with the Holling type II functional response and logistic growth of the prey. The finite element schemes generalize 'Scheme 1' in the paper by Garvie (Bull Math Biol 69(3):931-956, 2007). We present user-friendly, open-source MATLAB code for implementing the finite element methods on arbitrary-shaped two-dimensional domains with Dirichlet, Neumann, Robin, mixed Robin-Neumann, mixed Dirichlet-Neumann, and Periodic boundary conditions. Users can download, edit, and run the codes from http://www.uoguelph.ca/~mgarvie/ . In addition to discussing the well posedness of the model equations, the results of numerical experiments are presented and demonstrate the crucial role that habitat shape, initial data, and the boundary conditions play in determining the spatiotemporal dynamics of predator-prey interactions. As most previous works on this problem have focussed on square domains with standard boundary conditions, our paper makes a significant contribution to the area.
Garvie, Marcus R; Burkardt, John; Morgan, Jeff
2015-03-01
We describe simple finite element schemes for approximating spatially extended predator-prey dynamics with the Holling type II functional response and logistic growth of the prey. The finite element schemes generalize 'Scheme 1' in the paper by Garvie (Bull Math Biol 69(3):931-956, 2007). We present user-friendly, open-source MATLAB code for implementing the finite element methods on arbitrary-shaped two-dimensional domains with Dirichlet, Neumann, Robin, mixed Robin-Neumann, mixed Dirichlet-Neumann, and Periodic boundary conditions. Users can download, edit, and run the codes from http://www.uoguelph.ca/~mgarvie/ . In addition to discussing the well posedness of the model equations, the results of numerical experiments are presented and demonstrate the crucial role that habitat shape, initial data, and the boundary conditions play in determining the spatiotemporal dynamics of predator-prey interactions. As most previous works on this problem have focussed on square domains with standard boundary conditions, our paper makes a significant contribution to the area. PMID:25616741
The structure of approximate two electron wavefunctions in intense laser driven ionization dynamics
International Nuclear Information System (INIS)
The structure of approximate two-electron wavefunctions in strong-field-driven ionization dynamics is investigated in depth, both theoretically and numerically. Theoretical analyses clarify that for two-electron singlet systems, the previously proposed time-dependent extended Hartree–Fock (TD-EHF) method (1995 Phys. Rev. A 51 3999) is equivalent to the multiconfiguration time-dependent Hartree–Fock method with two occupied orbitals. The latter wavefunction is further transformed into the natural expansion form, enabling the direct propagation of the natural orbitals (NOs). These methods, as well as the conventional time-dependent Hartree–Fock (TDHF) method, are numerically assessed as regards providing a description of the ionization dynamics of a one-dimensional helium atom model. This numerical analysis (i) explains the reason behind the well-known failure of the TDHF method to describe tunneling ionization, (ii) demonstrates the interpretive power of the TD-EHF wavefunction in both the original nonorthogonal formulation and the NO-based formulation, and (iii) highlights different manifestations of the electron correlation (an effect beyond the single-determinant description), in tunneling ionization, high harmonic generation, and nonsequential double ionization. Possible extensions of the NO basis approach to multielectron systems are briefly discussed. (paper)
Galler, Anna; Gunacker, Patrik; Tomczak, Jan; Thunström, Patrik; Held, Karsten
Recently, approaches such as the dynamical vertex approximation (D ΓA) or the dual-fermion method have been developed. These diagrammatic approaches are going beyond dynamical mean field theory (DMFT) by including nonlocal electronic correlations on all length scales as well as the local DMFT correlations. Here we present our efforts to extend the D ΓA methodology to ab-initio materials calculations (ab-initio D ΓA). Our approach is a unifying framework which includes both GW and DMFT-type of diagrams, but also important nonlocal correlations beyond, e.g. nonlocal spin fluctuations. In our multi-band implementation we are using a worm sampling technique within continuous-time quantum Monte Carlo in the hybridization expansion to obtain the DMFT vertex, from which we construct the reducible vertex function using the two particle-hole ladders. As a first application we show results for transition metal oxides. Support by the ERC project AbinitioDGA (306447) is acknowledged.
A Hybrid Dynamic Programming Method for Concave Resource Allocation Problems
Institute of Scientific and Technical Information of China (English)
姜计荣; 孙小玲
2005-01-01
Concave resource allocation problem is an integer programming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems are encountered in optimization models involving economies of scale. In this paper, a new hybrid dynamic programming method was proposed for solving concave resource allocation problems. A convex underestimating function was used to approximate the objective function and the resulting convex subproblem was solved with dynamic programming technique after transforming it into a 0-1 linear knapsack problem. To ensure the convergence, monotonicity and domain cut technique was employed to remove certain integer boxes and partition the revised domain into a union of integer boxes. Computational results were given to show the efficiency of the algorithm.
Classical dynamics of a charged particle in a laser field beyond the dipole approximation
Jameson, Paul; Khvedelidze, Arsen
2008-05-01
The classical dynamics of a charged particle traveling in a laser field modeled by an elliptically polarized monochromatic electromagnetic plane wave is discussed within the time reparametrization invariant form of the nonrelativistic Hamilton-Jacobi theory. The exact parametric representation for a particle’s orbit in an arbitrary plane wave background beyond the dipole approximation and including effect of the magnetic field is derived. For an elliptically polarized monochromatic plane wave the particle’s trajectory, as an explicit function of the laboratory frame’s time, is given in terms of the Jacobian elliptic functions, whose modulus is proportional to the laser’s intensity and depends on the polarization of radiation. It is shown that the system exposes the intensity duality, correspondence between the motion in the backgrounds with various intensities. In virtue of the modular properties of the Jacobian functions, by starting with the representative “fundamental solution” and applying a certain modular transformation one can obtain the particle’s orbit in the monochromatic plane wave background with arbitrarily prescribed characteristics.
Mao, Runfang; Lee, Ming-Tsung; Vishnyakov, Aleksey; Neimark, Alexander V
2015-09-01
Using dissipative particle dynamics (DPD) simulations, we explore the specifics of micellization in the solutions of anionic and cationic surfactants and their mixtures. Anionic surfactant sodium dodecyl sulfate (SDS) and cationic surfactant cetyltrimethylammonium bromide (CTAB) are chosen as characteristic examples. Coarse-grained models of the surfactants are constructed and parameterized using a combination of atomistic molecular simulation and infinite dilution activity coefficient calibration. Electrostatic interactions of charged beads are treated using a smeared charge approximation: the surfactant heads and dissociated counterions are modeled as beads with charges distributed around the bead center in an implicit dielectric medium. The proposed models semiquantitatively describe self-assembly in solutions of SDS and CTAB at various surfactant concentrations and molarities of added electrolyte. In particular, the model predicts a decline in the free surfactant concentration with the increase of the total surfactant loading, as well as characteristic aggregation transitions in single-component surfactant solutions caused by the addition of salt. The calculated values of the critical micelle concentration reasonably agree with experimental observations. Modeling of catanionic SDS-CTAB mixtures show consecutive transitions to worm-like micelles and then to vesicles caused by the addition of CTAB to micellar solution of SDS. PMID:26241704
Microsoft Dynamics NAV 7 programming cookbook
Raul, Rakesh
2013-01-01
Written in the style of a cookbook. Microsoft Dynamics NAV 7 Programming Cookbook is full of recipes to help you get the job done.If you are a junior / entry-level NAV developer then the first half of the book is designed primarily for you. You may or may not have any experience programming. It focuses on the basics of NAV programming.If you are a mid-level NAV developer, you will find these chapters explain how to think outside of the NAV box when building solutions. There are also recipes that senior developers will find useful.
A boundedness result for the direct heuristic dynamic programming.
Liu, Feng; Sun, Jian; Si, Jennie; Guo, Wentao; Mei, Shengwei
2012-08-01
Approximate/adaptive dynamic programming (ADP) has been studied extensively in recent years for its potential scalability to solve large state and control space problems, including those involving continuous states and continuous controls. The applicability of ADP algorithms, especially the adaptive critic designs has been demonstrated in several case studies. Direct heuristic dynamic programming (direct HDP) is one of the ADP algorithms inspired by the adaptive critic designs. It has been shown applicable to industrial scale, realistic and complex control problems. In this paper, we provide a uniformly ultimately boundedness (UUB) result for the direct HDP learning controller under mild and intuitive conditions. By using a Lyapunov approach we show that the estimation errors of the learning parameters or the weights in the action and critic networks remain UUB. This result provides a useful controller convergence guarantee for the first time for the direct HDP design. PMID:22397949
On Static and Dynamic Control-Flow Information in Program Analysis and Transformation
DEFF Research Database (Denmark)
Damian, Daniel
This thesis addresses several aspects of static and dynamic control-flow information in programming languages, by investigating its interaction with program transformation and program analysis. Control-flow information indicates for each point in a program the possible program points to be executed...... of the program may be executed next. A control-flow analysis approximates the dynamic control-flow information with conservative static control-flow information. We explore the impact of a continuation-passing-style (CPS) transformation on the result of a constraint-based control-flow analysis over Moggi...... next. Control-flow information in a program may be static, as when the syntax of the program directly determines which parts of the program may be executed next. Control-flow information may be dynamic, as when run-time values and inputs of the program are required to determine which parts...
Quantum optical device accelerating dynamic programming
Grigoriev, D.; Kazakov, A.; Vakulenko, S
2005-01-01
In this paper we discuss analogue computers based on quantum optical systems accelerating dynamic programming for some computational problems. These computers, at least in principle, can be realized by actually existing devices. We estimate an acceleration in resolving of some NP-hard problems that can be obtained in such a way versus deterministic computers
Waste Heat Approximation for Understanding Dynamic Compression in Nature and Experiments
Jeanloz, R.
2015-12-01
Energy dissipated during dynamic compression quantifies the residual heat left in a planet due to impact and accretion, as well as the deviation of a loading path from an ideal isentrope. Waste heat ignores the difference between the pressure-volume isentrope and Hugoniot in approximating the dissipated energy as the area between the Rayleigh line and Hugoniot (assumed given by a linear dependence of shock velocity on particle velocity). Strength and phase transformations are ignored: justifiably, when considering sufficiently high dynamic pressures and reversible transformations. Waste heat mis-estimates the dissipated energy by less than 10-20 percent for volume compressions under 30-60 percent. Specific waste heat (energy per mass) reaches 0.2-0.3 c02 at impact velocities 2-4 times the zero-pressure bulk sound velocity (c0), its maximum possible value being 0.5 c02. As larger impact velocities are implied for typical orbital velocities of Earth-like planets, and c02 ≈ 2-30 MJ/kg for rock, the specific waste heat due to accretion corresponds to temperature rises of about 3-15 x 103 K for rock: melting accompanies accretion even with only 20-30 percent waste heat retained. Impact sterilization is similarly quantified in terms of waste heat relative to the energy required to vaporize H2O (impact velocity of 7-8 km/s, or 4.5-5 c0, is sufficient). Waste heat also clarifies the relationship between shock, multi-shock and ramp loading experiments, as well as the effect of (static) pre-compression. Breaking a shock into 2 steps significantly reduces the dissipated energy, with minimum waste heat achieved for two equal volume compressions in succession. Breaking a shock into as few as 4 steps reduces the waste heat to within a few percent of zero, documenting how multi-shock loading approaches an isentrope. Pre-compression, being less dissipative than an initial shock to the same strain, further reduces waste heat. Multi-shock (i.e., high strain-rate) loading of pre
Synthesis of Large Dynamic Concurrent Programs from Dynamic Specifications
Attie, Paul C
2008-01-01
We present a tractable method for synthesizing arbitrarily large concurrent programs, for a shared memory model with common hardware-available primitives such as atomic registers, compare-and-swap, load-linked/store conditional, etc. The programs we synthesize are dynamic: new processes can be created and added at run-time, and so our programs are not finite-state, in general. Nevertheless, we successfully exploit automatic synthesis and model-checking methods based on propositional temporal logic. Our method is algorithmically efficient, with complexity polynomial in the number of component processes (of the program) that are ``alive'' at any time. Our method does not explicitly construct the automata-theoretic product of all processes that are alive, thereby avoiding \\intr{state explosion}. Instead, for each pair of processes which interact, our method constructs an automata-theoretic product (\\intr{pair-machine}) which embodies all the possible interactions of these two processes. From each pair-machine, w...
Performance Potential-based Neuro-dynamic Programming for SMDPs
Institute of Scientific and Technical Information of China (English)
TANGHao; YUANJi-Bin; LUYang; CHENGWen-Juan
2005-01-01
An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimal generator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimization of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamic programming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performance error bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, a numerical example is provided.
Directory of Open Access Journals (Sweden)
Anders Gjelsvik
1982-07-01
Full Text Available A first-order differential dynamic programming (DDP algorithm is used for computing optimal control for a five-reservoir system, where the stochastic inflow process has been approximated by a few discrete disturbance values in each time step. The method is found to be faster than linear programming, previously tried on the same system model.
Approximate Modified Policy Iteration
Scherrer, Bruno; Ghavamzadeh, Mohammad; Geist, Matthieu
2012-01-01
Modified policy iteration (MPI) is a dynamic programming (DP) algorithm that contains the two celebrated policy and value iteration methods. Despite its generality, MPI has not been thoroughly studied, especially its approximation form which is used when the state and/or action spaces are large or infinite. In this paper, we propose three approximate MPI (AMPI) algorithms that are extensions of the well-known approximate DP algorithms: fitted-value iteration, fitted-Q iteration, and classification-based policy iteration. We provide an error propagation analysis for AMPI that unifies those for approximate policy and value iteration. We also provide a finite-sample analysis for the classification-based implementation of AMPI (CBMPI), which is more general (and somehow contains) than the analysis of the other presented AMPI algorithms. An interesting observation is that the MPI's parameter allows us to control the balance of errors (in value function approximation and in estimating the greedy policy) in the fina...
Eradication of Ebola Based on Dynamic Programming
Zhu, Jia-Ming; Wang, Lu; Liu, Jia-Bao
2016-01-01
This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost. PMID:27313655
Local minimization algorithms for dynamic programming equations
Kalise, Dante; Kröner, Axel; Kunisch, Karl
2015-01-01
The numerical realization of the dynamic programming principle for continuous-time optimal control leads to nonlinear Hamilton-Jacobi-Bellman equations which require the minimization of a nonlinear mapping over the set of admissible controls. This minimization is often performed by comparison over a finite number of elements of the control set. In this paper we demonstrate the importance of an accurate realization of these minimization problems and propose algorithms by which this can be achi...
Dynamic Programming, Maximum Principle and Vintage Capital
Fabbri, Giorgio; Iacopetta, Maurizio
2007-01-01
We present an application of the Dynamic Programming (DP) and of the Maximum Principle (MP) to solve an optimization over time when the production function is linear in the stock of capital (Ak model). Two views of capital are considered. In one, which is embraced by the great majority of macroeconomic models, capital is homogeneous and depreciates at a constant exogenous rate. In the other view each piece of capital has its own ﬁnite productive life cycle (vintage capital). The interpretatio...
Weak Dynamic Programming for Generalized State Constraints
Bouchard, Bruno; Nutz, Marcel
2012-01-01
We provide a dynamic programming principle for stochastic optimal control problems with expectation constraints. A weak formulation, using test functions and a probabilistic relaxation of the constraint, avoids restrictions related to a measurable selection but still implies the Hamilton-Jacobi-Bellman equation in the viscosity sense. We treat open state constraints as a special case of expectation constraints and prove a comparison theorem to obtain the equation for closed state constraints.
Eradication of Ebola Based on Dynamic Programming.
Zhu, Jia-Ming; Wang, Lu; Liu, Jia-Bao
2016-01-01
This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost. PMID:27313655
Comparison of dynamical approximation schemes for non-linear gravitational clustering
Melott, A L
1994-01-01
I report on controlled comparison of gravitational approximation schemes linear/lognormal/adhesion/frozen-flow/Zel'dovich(ZA) and ZA's second--order generalization. In the last two cases we also created new versions of the approximation by truncation, i.e., by finding an optimum smoothing window (see text) for the initial conditions. The Zel'dovich approximation, with optimized initial smoothing, worked extremely well. Its second-order generalization was slightly better. The success of our best-choice was a result of the treatment of the phases of nonlinear Fourier components. The adhesion approximation produced the most accurate nonlinear power spectrum and density distribution, but its phase errors suggest mass condensations were moved somewhat incorrectly. Due to its better reproduction of the mass density distribution function and power spectrum, adhesion might be preferred for some uses. We recommend either n-body simulations or our modified versions of ZA, depending on the purpose. Modified ZA can rapid...
Optimization of decision rules based on dynamic programming approach
Zielosko, Beata
2014-01-14
This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.
Joint Chance-Constrained Dynamic Programming
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob
2012-01-01
This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.
On a Natural Dynamics for Linear Programming
Straszak, Damian
2015-01-01
In this paper we study dynamics inspired by Physarum polycephalum (a slime mold) for solving linear programs [NTY00, IJNT11, JZ12]. These dynamics are arrived at by a local and mechanistic interpretation of the inner workings of the slime mold and a global optimization perspective has been lacking even in the simplest of instances. Our first result is an interpretation of the dynamics as an optimization process. We show that Physarum dynamics can be seen as a steepest-descent type algorithm on a certain Riemannian manifold. Moreover, we prove that the trajectories of Physarum are in fact paths of optimizers to a parametrized family of convex programs, in which the objective is a linear cost function regularized by an entropy barrier. Subsequently, we rigorously establish several important properties of solution curves of Physarum. We prove global existence of such solutions and show that they have limits, being optimal solutions of the underlying LP. Finally, we show that the discretization of the Physarum dy...
Xiaofeng Lin; Heng Zhang; Li Wei; Huixia Liu
2009-01-01
This paper applies a neural-network-based approximate dynamic programming (ADP) method, namely, the action dependent heuristic dynamic programming (ADHDP), to an industrial sucrose crystallization optimal control problem. The industrial sucrose crystallization is a nonlinear and slow time-varying process. It is quite difficult to establish a precise mechanism model of the crystallization, because of complex internal mechanism and interacting variables. We developed a neural network model of t...
Dynamic programming algorithms for biological sequence comparison.
Pearson, W R; Miller, W
1992-01-01
Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.
Zimmermann, Tomas
2011-01-01
We propose to measure nonadiabaticity of molecular quantum dynamics rigorously with the quantum fidelity between the Born-Oppenheimer and fully nonadiabatic dynamics. It is shown that this measure of nonadiabaticity applies in situations where other criteria, such as the energy gap criterion or the extent of population transfer, fail. We further propose to estimate this quantum fidelity efficiently with a generalization of the dephasing representation to multiple surfaces. Two variants of the multiple-surface dephasing representation (MSDR) are introduced, in which the nuclei are propagated either with the fewest-switches surface hopping (FSSH) or with the locally mean field dynamics (LMFD). The LMFD can be interpreted as the Ehrenfest dynamics of an ensemble of nuclear trajectories, and has been used previously in the nonadiabatic semiclassical initial value representation. In addition to propagating an ensemble of classical trajectories, the MSDR requires evaluating nonadiabatic couplings and solving the Sc...
Gontchar, Igor
2015-01-01
Accuracy of the Kramers approximate formula for the thermal decay rate of the metastable state is studied for the two-dimensional potential pocket. This is done by the comparison with the quasistationary rate resulting from the dynamical modeling. It is shown that the Kramers rate is in agreement with the quasistationary rate within the statistical errors provided the absorptive border is far enough from the potential ridge restricting the metastable state. As the absorptive border (or its part) gets closer to the ridge the Kramers formula underestimate the quasistationary rate. The difference reaches approximately the factor of 2 when the absorptive border coincides with the ridge.
International Nuclear Information System (INIS)
In this work a two-particle irreducible (2PI) closed-time-path (CTP) effective action is used to describe the nonequilibrium dynamics of a Bose-Einstein condensate selectively loaded into every third site of a one-dimensional optical lattice. The motivation of this work is the recent experimental realization of this system. Patterned loading methods may be useful for quantum computing with trapped atoms. This system also serves to illustrate many basic issues in nonequilibrium quantum-field theory pertaining to the dynamics of quantum correlations and fluctuations which goes beyond the capability of a mean-field theory. By numerically evolving in time the initial-state configuration using the Bose-Hubbard Hamiltonian an exact quantum solution is available for this system in the case of few atoms and wells. One can also use it to test various approximate methods. Under the 2PI CTP scheme with this initial configuration, three different approximations are considered: (a) the Hartree-Fock-Bogoliubov (HFB) approximation (b) the next-to-leading-order 1/N expansion of the 2PI effective action up to second order in the interaction strength, and (c) a second-order perturbative expansion in the interaction strength. We present detailed comparisons between these approximations and determine their range of validity by contrasting them with the exact many-body solution for a moderate number of atoms and wells. As a general feature we observe that because the second-order 2PI approximations include multiparticle scattering in a systematic way, they are able to capture damping effects exhibited in the exact solution, which a mean-field collisionless approach fails to produce. While the second-order approximations show a clear improvement over the HFB approximation, our numerical results show that they fail at late times, when interaction effects are significant
Granular contact dynamics using mathematical programming methods
DEFF Research Database (Denmark)
Krabbenhoft, K.; Lyamin, A. V.; Huang, J.;
2012-01-01
A class of variational formulations for discrete element analysis of granular media is presented. These formulations lead naturally to convex mathematical programs that can be solved using standard and readily available tools. In contrast to traditional discrete element analysis, the present...... granular contact dynamics formulation uses an implicit time discretization, thus allowing for large time steps. Moreover, in the limit of an infinite time step, the general dynamic formulation reduces to a static formulation that is useful in simulating common quasi-static problems such as triaxial tests...... and similar laboratory experiments. A significant portion of the paper is dedicated to exploring the consequences of the associated frictional sliding rule implied by the variational formulation adopted. In this connection, a new interior-point algorithm for general linear complementarity problems...
A Dynamic Programming Approach to Constrained Portfolios
DEFF Research Database (Denmark)
Kraft, Holger; Steffensen, Mogens
2013-01-01
This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies...... the martingale method. More precisely, we construct the non-separable value function by formalizing the optimal constrained terminal wealth to be a (conjectured) contingent claim on the optimal non-constrained terminal wealth. This is relevant by itself, but also opens up the opportunity to derive new solutions...
Eradication of Ebola Based on Dynamic Programming
Directory of Open Access Journals (Sweden)
Jia-Ming Zhu
2016-01-01
Full Text Available This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost.
Upper Bounds on Numerical Approximation Errors
DEFF Research Database (Denmark)
Raahauge, Peter
2004-01-01
This paper suggests a method for determining rigorous upper bounds on approximationerrors of numerical solutions to infinite horizon dynamic programming models.Bounds are provided for approximations of the value function and the policyfunction as well as the derivatives of the value function...... to approximations of a standard (strictly concave)growth model.KEYWORDS: Numerical approximation errors, Bellman contractions, Error bounds...
International Nuclear Information System (INIS)
A self-consistent approximation scheme is formulated for the calculation of the dynamical linear polarizability of classical electron monolayers. The derivation is carried out in two stages. In the first stage, the authors formulate a simple response function relation linking linear and quadratic polarizabilities; the dynamical coupling function is expressed entirely in terms of the latter. The basic elements in the derivation are the first BBGKY kinetic equation (prepared in the velocity average approximation) and the non-linear fluctuation-dissipation theorem. The new response function relation is exact at zero frequency and exactly satisfies the third frequency moment sum rule. In the second stage, self-consistency is guaranteed by approximating the quadratic polarizability in terms of linear ones. The theory is examined in the weak coupling limit where it is found that a dominant γ-independent non-RPA contribution to the damping is missing. The structure of the missing term is identified at arbitrary coupling strengths. Work is in progress to see how it can be incorporated into the approximation scheme. (author)
Domínguez, Luis F.
2012-06-25
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear programming subproblem and a mixed-integer nonlinear programming subproblem to provide a series of parametric upper and lower bounds. The primal subproblem is formulated by fixing the integer variables and solved through a series of multiparametric quadratic programming (mp-QP) problems based on quadratic approximations of the objective function, while the deterministic master subproblem is formulated so as to provide feasible integer solutions for the next primal subproblem. To reduce the computational effort when infeasibilities are encountered at the vertices of the critical regions (CRs) generated by the primal subproblem, a simplicial approximation approach is used to obtain CRs that are feasible at each of their vertices. The algorithm terminates when there does not exist an integer solution that is better than the one previously used by the primal problem. Through a series of examples, the proposed algorithm is compared with a multiparametric mixed-integer outer approximation (mp-MIOA) algorithm to demonstrate its computational advantages. © 2012 American Institute of Chemical Engineers (AIChE).
Runway Scheduling Using Generalized Dynamic Programming
Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar
2011-01-01
A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.
Automated Flight Routing Using Stochastic Dynamic Programming
Ng, Hok K.; Morando, Alex; Grabbe, Shon
2010-01-01
Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.
Kinematic and dynamic modeling and approximate analysis of a roller chain drive
DEFF Research Database (Denmark)
Fuglede, Niels; Thomsen, Jon Juel
2016-01-01
A simple roller chain drive consisting of two sprockets connected by tight chain spans is investigated. First, a kinematic model is presented which include both spans and sprockets. An approach for calculating the chain wrapping length is presented, which also allows for the exact calculation...... of sprocket center positions for a given chain length. The kinematic analysis demonstrates that the total length of the chain wrapped around the sprockets generally varies during one tooth period. Analytical predictions for the wrapping length are compared to multibody simulation results and show very good...... agreement. It is thereby demonstrated that chain drives with tight chain spans must include compliant components to function. Second, a dynamic model is presented which includes the two spans and the driven sprocket. Assuming the presence of a stationary operating state, the presented dynamic model allows...
Approximate expression for the dynamic structure factor in the Lieb-Liniger model
Cherny, Alexander Yu.; Brand, Joachim
2009-01-01
Recently, Imambekov and Glazman [Phys. Rev. Lett. 100, 206805 (2008)] showed that the dynamic structure factor (DSF) of the 1D Bose gas demonstrates power-law behaviour along the limiting dispersion curve of the collective modes and calculated the corresponding exponents exactly. Combining these recent results with a previously obtained strong-coupling expansion we present an interpolation formula for the DSF of the 1D Bose gas. The obtained expression is further consistent with exact low ene...
Equilibria of dynamic games with many players: Existence, approximation, and market structure
Adlakha, Sachin; Johari, Ramesh; Gabriel Y. Weintraub
2015-01-01
In this paper we study stochastic dynamic games with many players; these are a fundamental model for a wide range of economic applications. The standard solution concept for such games is Markov perfect equilibrium (MPE), but it is well known that MPE computation becomes intractable as the number of players increases. We instead consider the notion of stationary equilibrium (SE), where players optimize assuming the empirical distribution of others' states remains constant at its long run aver...
Institute of Scientific and Technical Information of China (English)
Da-chuan; XU; Shu-zhong; ZHANG
2007-01-01
In this paper,we consider a class of quadratic maximization problems.For a subclass of the problems,we show that the SDP relaxation approach yields an approximation solution with the ratio is dependent on the data of the problem with α being a uniform lower bound.In light of this new bound,we show that the actual worst-case performance ratio of the SDP relaxation approach (with the triangle inequalities added) is at least α + δd if every weight is strictly positive,where δd ＞ 0 is a constant depending on the problem dimension and data.
Pulliam, T. H.; Steger, J. L.
1985-01-01
In 1977 and 1978, general purpose centrally space differenced implicit finite difference codes in two and three dimensions have been introduced. These codes, now called ARC2D and ARC3D, can run either in inviscid or viscous mode for steady or unsteady flow. Since the introduction of the ARC2D and ARC3D codes, overall computational efficiency could be improved by making use of a number of algorithmic changes. These changes are related to the use of a spatially varying time step, the use of a sequence of mesh refinements to establish approximate solutions, implementation of various ways to reduce inversion work, improved numerical dissipation terms, and more implicit treatment of terms. The present investigation has the objective to describe the considered improvements and to quantify advantages and disadvantages. It is found that using established and simple procedures, a computer code can be maintained which is competitive with specialized codes.
Exact and approximate dynamics of the quantum mechanical O(N) model
Mihaila, B; Cooper, F; Dawson, J; Habib, S; Mihaila, Bogdan; Athan, Tara; Cooper, Fred; Dawson, John; Habib, Salman
2000-01-01
We study a quantum dynamical system of N, O(N) symmetric, nonlinear oscillators as a toy model to investigate the systematics of a 1/N expansion. The closed time path (CTP) formalism melded with an expansion in 1/N is used to derive time evolution equations valid to order 1/N (next-to-leading order). The effective potential is also obtained to this order and its properties areelucidated. In order to compare theoretical predictions against numerical solutions of the time-dependent Schrodinger equation, we consider two initial conditions consistent with O(N) symmetry, one of them a quantum roll, the other a wave packet initially to one side of the potential minimum, whose center has all coordinates equal. For the case of the quantum roll we map out the domain of validity of the large-N expansion. We discuss unitarity violation in the 1/N expansion; a well-known problem faced by moment truncation techniques. The 1/N results, both static and dynamic, are also compared to those given by the Hartree variational ans...
Directory of Open Access Journals (Sweden)
Abay Molla Kassa
2014-07-01
Full Text Available In this paper, we developed a novel algorithmic approach for thesolution of multi-parametric non-convex programming problems withcontinuous decision variables. The basic idea of the proposedapproach is based on successive convex relaxation of each non-convexterms and sensitivity analysis theory. The proposed algorithm isimplemented using MATLAB software package and numericalexamples are presented to illustrate the effectiveness andapplicability of the proposed method on multi-parametric non-convexprogramming problems with polyhedral constraints.
Thoma, M.; Grosfeld, K.; Barbi, D.; Determann, J.; Goeller, S.; Mayer, C.; Pattyn, F.
2014-01-01
Glaciers and ice caps exhibit currently the largest cryospheric contributions to sea level rise. Modelling the dynamics and mass balance of the major ice sheets is therefore an important issue to investigate the current state and the future response of the cryosphere in response to changing environmental conditions, namely global warming. This requires a powerful, easy-to-use, versatile multi-approximation ice dynamics model. Based on the well-known and established ice sheet model of Pattyn (2003) we develop the modular multi-approximation thermomechanic ice model RIMBAY, in which we improve the original version in several aspects like a shallow ice-shallow shelf coupler and a full 3D-grounding-line migration scheme based on Schoof's (2007) heuristic analytical approach. We summarise the full Stokes equations and several approximations implemented within this model and we describe the different numerical discretisations. The results are cross-validated against previous publications dealing with ice modelling, and some additional artificial set-ups demonstrate the robustness of the different solvers and their internal coupling. RIMBAY is designed for an easy adaption to new scientific issues. Hence, we demonstrate in very different set-ups the applicability and functionality of RIMBAY in Earth system science in general and ice modelling in particular.
Model of skyscraper evacuation with the use of space symmetry and fluid dynamic approximation
Sikora, W; Kupczak, A
2011-01-01
The simulation of evacuation of pedestrians from skyscraper is a situation where the symmetry analysis method and equations of fluid dynamics finds to be very useful. When applied, they strongly reduce the number of free parameters used in simulations and in such a way speed up the calculations and make them easier to manage by the programmer and what is even more important, they can give a fresh insight into a problem of evacuation and help with incorporation of "Ambient Intelligent Devices" into future real buildings. We have analyzed various, simplified, cases of evacuation from skyscraper by employing improved "Social Force Model". For each of them we obtained the average force acting on the pedestrian as a function of the evacuation time. The results clearly show that both methods mentioned above, can be successfully implemented in the simulation process and return with satisfactory conclusions.
Dynamically Computing Approximate Frequency Counts in Sliding Window over Data Stream
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs sub-windows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε + 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n(n≤N) elements. The second algorithm outputs at most 1/ε+2 elements. The analytical and experimental results show that our algorithms are accurate and effective.
Euchner, Holger; Yamada, Tsunetomo; Schober, Helmut; Rols, Stephane; Mihalkovič, Marek; Tamura, Ryuji; Ishimasa, Tsutomu; de Boissieu, Marc
2012-10-17
Periodic approximants to quasicrystals offer a unique opportunity to better understand the structure, physical properties and stabilizing mechanisms of their quasicrystal counterparts. We present a detailed study of the order-disorder phase transition occurring at about 160 K in the Zn(6)Sc cubic approximant to the icosahedral quasicrystal i-MgZnSc. This transition goes along with an anti-parallel ordering of the tetrahedra located at the centres of large atomic clusters, which are packed on a bcc lattice. Single crystal x-ray diffuse scattering shows that the tetrahedra display pre-transitional short range ordering above T(c) (Yamada et al 2012 in preparation). Using quasielastic neutron scattering (QENS) we clearly evidence this short range order to be dynamical in nature above T(c). The QENS data are consistent with a model of tetrahedra 'jumping' between almost equivalent positions, which is supported by molecular dynamics simulations. This demonstrates a unique dynamical flexibility of the Zn(6)Sc structure even at room temperature.
Interpreting scratch assays using pair density dynamics and approximate Bayesian computation.
Johnston, Stuart T; Simpson, Matthew J; McElwain, D L Sean; Binder, Benjamin J; Ross, Joshua V
2014-09-01
Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate, λ. Estimating D and λ is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and λ have been proposed, these previous methods lead to point estimates of D and λ, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and λ using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and λ from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and λ. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and λ, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.
Directory of Open Access Journals (Sweden)
Xiaofeng Lin
2009-10-01
Full Text Available This paper applies a neural-network-based approximate dynamic programming (ADP method, namely, the action dependent heuristic dynamic programming (ADHDP, to an industrial sucrose crystallization optimal control problem. The industrial sucrose crystallization is a nonlinear and slow time-varying process. It is quite difficult to establish a precise mechanism model of the crystallization, because of complex internal mechanism and interacting variables. We developed a neural network model of the crystallization based on the data from the actual sugar boiling process of sugar refinery. The ADHDP is a learningand approximation-based approach which can solve the optimization control problem of nonlinear system. The paper covers the basic principle of this learning scheme and the design of neural network controller based on the approach. The result of simulation shows the controller based on action dependent heuristic dynamic programming approach can optimize industrial sucrose crystallization.
Nedorezov, L V
2015-01-01
For approximation of some well-known time series of Paramecia caudatun population dynamics (G. F. Gause, The Struggle for Existence, 1934) Verhulst and Gompertz models were used. The parameters were estimated for each of the models in two different ways: with the least squares method (global fitting) and non-traditional approach (a method of extreme points). The results obtained were compared and also with those represented by G. F. Gause. Deviations of theoretical (model) trajectories from experimental time series were tested using various non-parametric statistical tests. It was shown that the least square method-estimations lead to the results which not always meet the requirements imposed for a "fine" model. But in some cases a small modification of the least square method-estimations is possible allowing for satisfactory representations of experimental data set for approximation.
Pareto optimization in algebraic dynamic programming.
Saule, Cédric; Giegerich, Robert
2015-01-01
Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.
Goal representation heuristic dynamic programming on maze navigation.
Ni, Zhen; He, Haibo; Wen, Jinyu; Xu, Xin
2013-12-01
Goal representation heuristic dynamic programming (GrHDP) is proposed in this paper to demonstrate online learning in the Markov decision process. In addition to the (external) reinforcement signal in literature, we develop an adaptively internal goal/reward representation for the agent with the proposed goal network. Specifically, we keep the actor-critic design in heuristic dynamic programming (HDP) and include a goal network to represent the internal goal signal, to further help the value function approximation. We evaluate our proposed GrHDP algorithm on two 2-D maze navigation problems, and later on one 3-D maze navigation problem. Compared to the traditional HDP approach, the learning performance of the agent is improved with our proposed GrHDP approach. In addition, we also include the learning performance with two other reinforcement learning algorithms, namely Sarsa(λ) and Q-learning, on the same benchmarks for comparison. Furthermore, in order to demonstrate the theoretical guarantee of our proposed method, we provide the characteristics analysis toward the convergence of weights in neural networks in our GrHDP approach. PMID:24805221
Dodin, Amro; Brumer, Paul
2015-01-01
We present closed-form analytic solutions to non-secular Bloch-Redfield master equations for quantum dynamics of a V-type system driven by weak coupling to a thermal bath. We focus on noise-induced Fano coherences among the excited states induced by incoherent driving of the V-system initially in the ground state. For suddenly turned-on incoherent driving, the time evolution of the coherences is determined by the damping parameter $\\zeta=\\frac{1}{2}(\\gamma_1+\\gamma_2)/\\Delta_p$, where $\\gamma_i$ are the radiative decay rates of the excited levels $i=1,2$, and $\\Delta_p=\\sqrt{\\Delta^2 + (1-p^2)\\gamma_1\\gamma_2}$ depends on the excited-state level splitting $\\Delta>0$ and the angle between the transition dipole moments in the energy basis. The coherences oscillate as a function of time in the underdamped limit ($\\zeta\\gg1$), approach a long-lived quasi-steady state in the overdamped limit ($\\zeta\\ll 1$), and display an intermediate behavior at critical damping ($\\zeta= 1$). The sudden incoherent turn-on generat...
Speed of sound in solid molecular hydrogen-deuterium: Quantum Molecular Dynamics Approximation
Guerrero, Carlo Luis; Perlado, Jose Manuel
2016-05-01
Uniformity of the solid layer is one of the critical points for an efficient ignition of the Deuterium-Tritium (DT) target. During the compression process this layer, perturbations grow as the Rayleigh-Taylor instability. Knowing the mechanical properties of this layer and its thermo-mechanical limits is necessary if we want to control or to minimize these instabilities. In this work we have used a simplified approach, replacing the DT ice system with a mixture of hydrogen-deuterium (HD) because beta decay of tritium complicates the analysis in the former case. Through simulation with ab initio methods we have calculated the elastic constants, the bulk modulus and sound velocity for hydrogen isotopes in solid molecular state. In this work we present the results for hydrogen-deuterium mixtures 50%-50%, at 15 K and with a compression which covers the range of 1 to 15 GPa. This system is interesting for study the early stages of the dynamic compression and provides conditions that are close to the manufacture of DT target in inertial confinement fusion. Discontinuities in the curve that have been observed on pure hydrogen, which are associated with phase transitions and the phase hysteresis.
Masmoudi, Nabil
2014-01-01
We present an approximate, but efficient and sufficiently accurate P-wave ray tracing and dynamic ray tracing procedure for 3D inhomogeneous, weakly orthorhombic media with varying orientation of symmetry planes. In contrast to commonly used approaches, the orthorhombic symmetry is preserved at any point of the model. The model is described by six weak-anisotropy parameters and three Euler angles, which may vary arbitrarily, but smoothly, throughout the model. We use the procedure for the calculation of rays and corresponding two-point traveltimes in a VSP experiment in a part of the BP benchmark model generalized to orthorhombic symmetry.
Directory of Open Access Journals (Sweden)
Yan Li
2012-01-01
Full Text Available We consider the dynamic proportional reinsurance in a two-dimensional compound Poisson risk model. The optimization in the sense of minimizing the ruin probability which is defined by the sum of subportfolio is being ruined. Via the Hamilton-Jacobi-Bellman approach we find a candidate for the optimal value function and prove the verification theorem. In addition, we obtain the Lundberg bounds and the Cramér-Lundberg approximation for the ruin probability and show that as the capital tends to infinity, the optimal strategies converge to the asymptotically optimal constant strategies. The asymptotic value can be found by maximizing the adjustment coefficient.
Dodin, Amro; Tscherbul, Timur V.; Brumer, Paul
2016-06-01
Closed-form analytic solutions to non-secular Bloch-Redfield master equations for quantum dynamics of a V-type system driven by weak coupling to a thermal bath, relevant to light harvesting processes, are obtained and discussed. We focus on noise-induced Fano coherences among the excited states induced by incoherent driving of the V-system initially in the ground state. For suddenly turned-on incoherent driving, the time evolution of the coherences is determined by the damping parameter ζ = /1 2 ( γ 1 + γ 2) / Δ p , where γi are the radiative decay rates of the excited levels i = 1, 2, and Δ p = √{ Δ 2 + ( 1 - p 2) γ 1 γ 2 } depends on the excited-state level splitting Δ > 0 and the angle between the transition dipole moments in the energy basis. The coherences oscillate as a function of time in the underdamped limit (ζ ≫ 1), approach a long-lived quasi-steady state in the overdamped limit (ζ ≪ 1), and display an intermediate behavior at critical damping (ζ = 1). The sudden incoherent turn-on is shown to generate a mixture of excited eigenstates |e1> and |e2> and their in-phase coherent superposition | ϕ + > = /1 √{ r 1 + r 2 } ( √{ r 1 } | e 1 > + √{ r 2 } | e 2 >) , which is remarkably long-lived in the overdamped limit (where r1 and r2 are the incoherent pumping rates). Formation of this coherent superposition enhances the decay rate from the excited states to the ground state. In the strongly asymmetric V-system where the coupling strengths between the ground state and the excited states differ significantly, additional asymptotic quasistationary coherences are identified, which arise due to slow equilibration of one of the excited states. Finally, we demonstrate that noise-induced Fano coherences are maximized with respect to populations when r1 = r2 and the transition dipole moments are fully aligned.
Dodin, Amro; Tscherbul, Timur V; Brumer, Paul
2016-06-28
Closed-form analytic solutions to non-secular Bloch-Redfield master equations for quantum dynamics of a V-type system driven by weak coupling to a thermal bath, relevant to light harvesting processes, are obtained and discussed. We focus on noise-induced Fano coherences among the excited states induced by incoherent driving of the V-system initially in the ground state. For suddenly turned-on incoherent driving, the time evolution of the coherences is determined by the damping parameter ζ=12(γ1+γ2)/Δp, where γi are the radiative decay rates of the excited levels i = 1, 2, and Δp=Δ(2)+(1-p(2))γ1γ2 depends on the excited-state level splitting Δ > 0 and the angle between the transition dipole moments in the energy basis. The coherences oscillate as a function of time in the underdamped limit (ζ ≫ 1), approach a long-lived quasi-steady state in the overdamped limit (ζ ≪ 1), and display an intermediate behavior at critical damping (ζ = 1). The sudden incoherent turn-on is shown to generate a mixture of excited eigenstates |e1〉 and |e2〉 and their in-phase coherent superposition |ϕ+〉=1r1+r2(r1|e1〉+r2|e2〉), which is remarkably long-lived in the overdamped limit (where r1 and r2 are the incoherent pumping rates). Formation of this coherent superposition enhances the decay rate from the excited states to the ground state. In the strongly asymmetric V-system where the coupling strengths between the ground state and the excited states differ significantly, additional asymptotic quasistationary coherences are identified, which arise due to slow equilibration of one of the excited states. Finally, we demonstrate that noise-induced Fano coherences are maximized with respect to populations when r1 = r2 and the transition dipole moments are fully aligned. PMID:27369498
Toh, H
1997-08-01
Two approximations were introduced into the double dynamic programming algorithm, in order to reduce the computational time for structural alignment. One of them was the so-called distance cut-off, which approximately describes the structural environment of each residue by its local environment. In the approximation, a sphere with a given radius is placed at the center of the side chain of each residue. The local environment of a residue is constituted only by the residues with side chain centers that are present within the sphere, which is expressed by a set of center-to-center distances from the side chain of the residue to those of all the other constituent residues. The residues outside the sphere are neglected from the local environment. Another approximation is associated with the distance cut-off, which is referred to here as the delta N cut-off. If two local environments are similar to each other, the numbers of residues constituting the environments are expected to be similar. The delta N cut-off was introduced based on the idea. If the difference between the numbers of the constituent residues of two local environments is greater than a given threshold value, delta N, the evaluation of the similarity between the local environments is skipped. The introduction of the two approximations dramatically reduced the computational time for structural alignment by the double dynamic programming algorithm. However, the approximations also decreased the accuracy of the alignment. To improve the accuracy with the approximations, a program with a two-step alignment algorithm was constructed. At first, an alignment was roughly constructed with the approximations. Then, the epsilon-suboptimal region for the alignment was determined. Finally, the double dynamic programming algorithm with full structural environments was applied to the residue pairs within the epsilon-suboptimal region to produce an improved alignment.
Directory of Open Access Journals (Sweden)
Grigis A
2006-01-01
Full Text Available A method for determination and two methods for approximation of the domain of attraction Da(0 of the asymptotically stable zero steady state of an autonomous, ℝ-analytical, discrete dynamical system are presented. The method of determination is based on the construction of a Lyapunov function V, whose domain of analyticity is Da(0. The first method of approximation uses a sequence of Lyapunov functions Vp, which converge to the Lyapunov function V on Da(0. Each Vp defines an estimate Np of Da(0. For any x ∈ Da(0, there exists an estimate which contains x. The second method of approximation uses a ball B(R ⊂ Da(0 which generates the sequence of estimates Mp = f-p(B(R. For any x ∈ Da(0, there exists an estimate which contains x. The cases ||∂0f||<1 and ρ(∂0f < 1 ≤||∂0f|| are treated separately because significant differences occur.
Spatial cluster detection using dynamic programming
Directory of Open Access Journals (Sweden)
Sverchkov Yuriy
2012-03-01
Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic
A Dynamic Programming Approach to Adaptive Fractionation
Ramakrishnan, Jagdish; Bortfeld, Thomas; Tsitsiklis, John
2011-01-01
We formulate a previously introduced adaptive fractionation problem in a dynamic programming (DP) framework and explore various solution techniques. The two messages of this paper are: (i) the DP model is a useful framework for studying adaptive radiation therapy, particularly adaptive fractionation, and (ii) there is a potential for substantial decrease in dose to the primary organ-at-risk (OAR), or equivalently increase in tumor escalation, when using an adaptive fraction size. The essence of adaptive fractionation is to increase the fraction size when observing a "favorable" anatomy or when the tumor and OAR are far apart and to decrease the fraction size when they are close together. Given that a fixed prescribed dose must be delivered to the tumor over the course of the treatment, such an approach results in a lower cumulative dose to the OAR when compared to that resulting from standard fractionation. We first establish a benchmark by using the DP algorithm to solve the problem exactly. In this case, we...
Segmentation of Indus Texts: A Dynamic Programming Approach.
Siromoney, Gift; Huq, Abdul
1988-01-01
Demonstrates how a dynamic programing algorithm can be developed to segment unusually long written inscriptions from the Indus Valley Civilization. Explains the problem of segmentation, discusses the dynamic programing algorithm used, and includes tables which illustrate the segmentation of the inscriptions. (GEA)
Diophantine approximation and badly approximable sets
DEFF Research Database (Denmark)
Kristensen, S.; Thorn, R.; Velani, S.
2006-01-01
. The classical set Bad of `badly approximable' numbers in the theory of Diophantine approximation falls within our framework as do the sets Bad(i,j) of simultaneously badly approximable numbers. Under various natural conditions we prove that the badly approximable subsets of Omega have full Hausdorff dimension....... Applications of our general framework include those from number theory (classical, complex, p-adic and formal power series) and dynamical systems (iterated function schemes, rational maps and Kleinian groups)....
International Nuclear Information System (INIS)
We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnaha-Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as is the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drive strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles
DEFF Research Database (Denmark)
Costa, Rafael S.; Machado, Daniel; Rocha, Isabel;
2010-01-01
The construction of dynamic metabolic models at reaction network level requires the use of mechanistic enzymatic rate equations that comprise a large number of parameters. The lack of knowledge on these equations and the difficulty in the experimental identification of their associated parameters...... using the hybrid model composed of Michaelis–Menten and the approximate lin-log kinetics indicate that this is a possible suitable approach to model complex large-scale networks where the exact rate laws are unknown.......The construction of dynamic metabolic models at reaction network level requires the use of mechanistic enzymatic rate equations that comprise a large number of parameters. The lack of knowledge on these equations and the difficulty in the experimental identification of their associated parameters......, represent nowadays the limiting factor in the construction of such models. In this study, we compare four alternative modeling approaches based on Michaelis–Menten kinetics for the bi-molecular reactions and different types of simplified rate equations for the remaining reactions (generalized mass action...
ALPprolog --- A New Logic Programming Method for Dynamic Domains
Drescher, Conrad
2011-01-01
Logic programming is a powerful paradigm for programming autonomous agents in dynamic domains, as witnessed by languages such as Golog and Flux. In this work we present ALPprolog, an expressive, yet efficient, logic programming language for the online control of agents that have to reason about incomplete information and sensing actions.
A. J. G. Babu; Balasubramanian Ram
1988-01-01
This paper suggests a method of formulating any nonlinear integer programming problem, with any number of constraints, as an equivalent single constraint problem, thus reducing the dimensionality of the associated dynamic programming problem.
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
Euchner, H; Yamada, T; Rols, S; Ishimasa, T; Kaneko, Y; Ollivier, J; Schober, H; Mihalkovic, M; de Boissieu, M
2013-03-20
A comparison of periodic approximants and their quasicrystalline counterparts offers the opportunity to better understand the structure, physical properties and stabilizing mechanisms of these complex phases. We present a combined experimental and molecular dynamics study of the lattice dynamics of the icosahedral quasicrystals i-ZnMgSc and i-ZnAgSc and compare it to recently published results obtained for the cubic 1/1-approximant Zn(6)Sc. Both phases, quasicrystal and approximant, are built up from large atomic clusters which contain a tetrahedral shell at the cluster centre and are packed either quasiperiodically or on a bcc lattice. Using quasielastic neutron scattering and atomic scale simulations, we show that in the quasicrystal the tetrahedra display a dynamics similar to that observed in the 1/1-approximant: the tetrahedra behave as a 'single molecule' and reorient dynamically on a timescale of the order of a few ps. The tetrahedra reorientation is accompanied by a large distortion of the surrounding cluster shells which provide a unique dynamical flexibility to the quasicrystal. However, whereas in the 1/1-approximant the tetrahedron reorientation is observed down to T(c) = 160 K, where a phase transition takes place, in the quasicrystal the tetrahedron dynamics is gradually freezing from 550 to 300 K, similarly to a glassy system.
Directory of Open Access Journals (Sweden)
Gustavo M. Souza
2004-09-01
Full Text Available Approximate Entropy (ApEn, a model-independent statistics to quantify serial irregularities, was used to evaluate changes in sap flow temporal dynamics of two tropical species of trees subjected to water deficit. Water deficit induced a decrease in sap flow of G. ulmifolia, whereas C. legalis held stable their sap flow levels. Slight increases in time series complexity were observed in both species under drought condition. This study showed that ApEn could be used as a helpful tool to assess slight changes in temporal dynamics of physiological data, and to uncover some patterns of plant physiological responses to environmental stimuli.Entropia Aproximada (ApEn, um modelo estatístico independente para quantificar irregularidade em séries temporais, foi utilizada para avaliar alterações na dinâmica temporal do fluxo de seiva em duas espécies arbóreas tropicais submetidas à deficiência hídrica. A deficiência hídrica induziu uma grande redução no fluxo de seiva em G. ulmifolia, enquanto que na espécie C. legalis manteve-se estável. A complexidade das séries temporais foi levemente aumentada sob deficiência hídrica. O estudo mostrou que ApEn pode ser usada como um método para detectar pequenas alterações na dinâmica temporal de dados fisiológicos, e revelar alguns padrões de respostas fisiológicas a estímulos ambientais.
Capacities, Measurable Selection and Dynamic Programming Part I: Abstract Framework
Karoui, Nicole El; Tan, Xiaolu
2013-01-01
We give a brief presentation of the capacity theory and show how it derives naturally a measurable selection theorem following the approach of Dellacherie (1972). Then we present the classical method to prove the dynamic programming of discrete time stochastic control problem, using measurable selection arguments. At last, we propose a continuous time extension, that is an abstract framework for the continuous time dynamic programming principle (DPP).
Applying dynamic programming to a gas-lift optimization problem
Energy Technology Data Exchange (ETDEWEB)
Camponogara, Eduardo; Nakashima, Paulo H.R. [Santa Catarina Univ., Florianopolis (Brazil). Dept. de Automacao e Sistemas]. E-mails: camponog@das.ufsc.br; phrn@das.ufsc.br
2003-07-01
The ever-increasing demand for nonrenewable resources and the pressure from stockholders are two forces pressing the oil industry for higher efficiency. The opportunities for advances abound in all sectors of the industry, in particular production processes in gas-lift oil wells, which are often favored to draw oil from high-depth reservoirs. Of concern in this paper is the task of distributing the limited supply of gas to the wells so as to induce an optimal oil production. Narrowing this task to the steady-state response of the wells gives rise to the gas-lift optimization problem, whose variables decide which wells should be active as well as the gas-injection and whose objective is profit maximization. The paper elaborates on a few properties of the problem and delivers a dynamic programming algorithm to find approximate solutions. The effectiveness of the algorithm was demonstrated by contrasting its solutions against upper bounds obtained with continuous relaxation. As closure, the paper outlines a few directions for future research. (author)
Optimization of conventional water treatment plant using dynamic programming.
Mostafa, Khezri Seyed; Bahareh, Ghafari; Elahe, Dadvar; Pegah, Dadras
2015-12-01
In this research, the mathematical models, indicating the capability of various units, such as rapid mixing, coagulation and flocculation, sedimentation, and the rapid sand filtration are used. Moreover, cost functions were used for the formulation of conventional water and wastewater treatment plant by applying Clark's formula (Clark, 1982). Also, by applying dynamic programming algorithm, it is easy to design a conventional treatment system with minimal cost. The application of the model for a case reduced the annual cost. This reduction was approximately in the range of 4.5-9.5% considering variable limitations. Sensitivity analysis and prediction of system's feedbacks were performed for different alterations in proportion from parameters optimized amounts. The results indicated (1) that the objective function is more sensitive to design flow rate (Q), (2) the variations in the alum dosage (A), and (3) the sand filter head loss (H). Increasing the inflow by 20%, the total annual cost would increase to about 12.6%, while 20% reduction in inflow leads to 15.2% decrease in the total annual cost. Similarly, 20% increase in alum dosage causes 7.1% increase in the total annual cost, while 20% decrease results in 7.9% decrease in the total annual cost. Furthermore, the pressure decrease causes 2.95 and 3.39% increase and decrease in total annual cost of treatment plants.
Optimal Control of a Fed-batch Fermentation Process by Neuro-Dynamic Programming
Tatiana Ilkova; Stoyan Tzonkov
2004-01-01
In this paper the method for optimal control of a fermentation process is presented, that is based on an approach for optimal control - Neuro-Dynamic programming. For this aim the approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this approach computing time and procedure are decreased and quality of the biomass at the end of the process is increased.
Optimal Control of a Fed-batch Fermentation Process by Neuro-Dynamic Programming
Directory of Open Access Journals (Sweden)
Tatiana Ilkova
2004-10-01
Full Text Available In this paper the method for optimal control of a fermentation process is presented, that is based on an approach for optimal control - Neuro-Dynamic programming. For this aim the approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this approach computing time and procedure are decreased and quality of the biomass at the end of the process is increased.
Barnes, Chris P.; Huvet, Maxime; Bugeon, Laurence; Thorne, Thomas; Lamb, Jonathan R.; Dallman, Margaret J.; Stumpf, Michael P. H.
2016-01-01
In vivo studies allow us to investigate biological processes at the level of the organism. But not all aspects of in vivo systems are amenable to direct experimental measurements. In order to make the most of such data we therefore require statistical tools that allow us to obtain reliable estimates for e.g. kinetic in vivo parameters. Here we show how we can use approximate Bayesian computation approaches in order to analyse leukocyte migration in zebrafish embryos in response to injuries. We track individual leukocytes using live imaging following surgical injury to the embryos’ tail-fins. The signalling gradient that leukocytes follow towards the site of the injury cannot be directly measured but we can estimate its shape and how it changes with time from the directly observed patterns of leukocyte migration. By coupling simple models of immune signalling and leukocyte migration with the unknown gradient shape into a single statistical framework we can gain detailed insights into the tissue-wide processes that are involved in the innate immune response to wound injury. In particular we find conclusive evidence for a temporally and spatially changing signalling gradient that modulates the changing activity of the leukocyte population in the embryos. We conclude with a robustness analysis which highlights the most important factors determining the leukocyte dynamics. Our approach relies only on the ability to simulate numerically the process under investigation and is therefore also applicable in other in vivo contexts and studies. PMID:22327539
Dynamic Performance Tuning Supported by Program Specification
Directory of Open Access Journals (Sweden)
Eduardo César
2002-01-01
Full Text Available Performance analysis and tuning of parallel/distributed applications are very difficult tasks for non-expert programmers. It is necessary to provide tools that automatically carry out these tasks. These can be static tools that carry out the analysis on a post-mortem phase or can tune the application on the fly. Both kind of tools have their target applications. Static automatic analysis tools are suitable for stable application while dynamic tuning tools are more appropriate to applications with dynamic behaviour. In this paper, we describe KappaPi as an example of a static automatic performance analysis tool, and also a general environment based on parallel patterns for developing and dynamically tuning parallel/distributed applications.
Robust Adaptive Dynamic Programming for Optimal Nonlinear Control Design
Jiang, Yu; Jiang, Zhong-Ping
2013-01-01
This paper studies the robust optimal control design for uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (robust-ADP). The objective is to fill up a gap in the past literature of ADP where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The...
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL
2012-10-01
It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.
Dynamic Learning Objects to Teach Java Programming Language
Narasimhamurthy, Uma; Al Shawkani, Khuloud
2010-01-01
This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…
Attack diagnosis on binary executables using dynamic program slicing
Huang, Shan; Zheng, Yudi; Zhang, Ruoyu
2011-12-01
Nowadays, the level of the practically used programs is often complex and of such a large scale so that it is not as easy to analyze and debug them as one might expect. And it is quite difficult to diagnose attacks and find vulnerabilities in such large-scale programs. Thus, dynamic program slicing becomes a popular and effective method for program comprehension and debugging since it can reduce the analysis scope greatly and drop useless data that do not influence the final result. Besides, most of existing dynamic slicing tools perform dynamic slicing in the source code level, but the source code is not easy to obtain in practice. We believe that we do need some kinds of systems to help the users understand binary programs. In this paper, we present an approach of diagnosing attacks using dynamic backward program slicing based on binary executables, and provide a dynamic binary slicing tool named DBS to analyze binary executables precisely and efficiently. It computes the set of instructions that may have affected or been affected by slicing criterion set in certain location of the binary execution stream. This tool also can organize the slicing results by function call graphs and control flow graphs clearly and hierarchically.
De Backer, A.; Sand, A.; Ortiz, C. J.; Domain, C.; Olsson, P.; Berthod, E.; Becquart, C. S.
2016-02-01
The damage produced by primary knock-on atoms (PKA) in W has been investigated from the threshold displacement energy (TDE) where it produces one self interstitial atom-vacancy pair to larger energies, up to 100 keV, where a large molten volume is formed. The TDE has been determined in different crystal directions using the Born-Oppenheimer density functional molecular dynamics (DFT-MD). A significant difference has been observed without and with the semi-core electrons. Classical MD has been used with two different empirical potentials characterized as ‘soft’ and ‘hard’ to obtain statistics on TDEs. Cascades of larger energy have been calculated, with these potentials, using a model that accounts for electronic losses (Sand et al 2013 Europhys. Lett. 103 46003). Two other sets of cascades have been produced using the binary collision approximation (BCA): a Monte Carlo BCA using SDTrimSP (Eckstein et al 2011 SDTrimSP: Version 5.00. Report IPP 12/8) (similar to SRIM www.srim.org) and MARLOWE (RSICC Home Page. (https://rsicc.ornl.gov/codes/psr/psr1/psr-137.html) (accessed May, 2014)). The comparison of these sets of cascades gave a recombination distance equal to 12 Å which is significantly larger from the one we reported in Hou et al (2010 J. Nucl. Mater. 403 89) because, here, we used bulk cascades rather than surface cascades which produce more defects (Stoller 2002 J. Nucl. Mater. 307 935, Nordlund et al 1999 Nature 398 49). Investigations on the defect clustering aspect showed that the difference between BCA and MD cascades is considerably reduced after the annealing of the cascade debris at 473 K using our Object Kinetic Monte Carlo model, LAKIMOCA (Domain et al 2004 J. Nucl. Mater. 335 121).
Tatiana Ilkova
2005-01-01
A fed-batch fermentation process is examined in this paper for experimental and further dynamic optimization. The static optimization is developed for to be found out the optimal initial concentrations of the basic biochemical variables - biomass, substrate and substrate in the feeding solution. For the static optimization of the process the method of Dynamic programming is used. After that these initial values are used for the dynamic optimization carried out by a submethod of Neuro-dynamic ...
Xu, Lei
2007-02-01
According to the proof by Liu, Chiu, and Xu (2004) on the so-called one-bit-matching conjecture (Xu, Cheung, and Amari, 1998a), all the sources can be separated as long as there is an one-to-one same-sign correspondence between the kurtosis signs of all source probability density functions (pdf's) and the kurtosis signs of all model pdf's, which is widely believed and implicitly supported by many empirical studies. However, this proof is made only in a weak sense that the conjecture is true when the global optimal solution of an independent component analysis criterion is reached. Thus, it cannot support the successes of many existing iterative algorithms that usually converge at one of the local optimal solutions. This article presents a new mathematical proof that is obtained in a strong sense that the conjecture is also true when any one of local optimal solutions is reached in helping to investigating convex-concave programming on a polyhedral set. Theorems are also provided not only on partial separation of sources when there is a partial matching between the kurtosis signs, but also on an interesting duality of maximization and minimization on source separation. Moreover, corollaries are obtained on an interesting duality, with supergaussian sources separated by maximization and subgaussian sources separated by minimization. Also, a corollary is obtained to confirm the symmetric orthogonalization implementation of the kurtosis extreme approach for separating multiple sources in parallel, which works empirically but lacks mathematical proof. Furthermore, a linkage has been set up to combinatorial optimization from a distribution approximation perspective and a Stiefel manifold perspective, with algorithms that guarantee convergence as well as satisfaction of constraints.
Modelling of windmill induction generators in dynamic simulation programs
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectivel...... rotor. It is shown that it is possible to include a transient model in dynamic stability programs and thus obtain correct results also in dynamic stability programs. A mechanical model of the shaft system has also been included in the generator model......For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectively...... with and without a model of the mechanical shaft. The reason for the discrepancies are explained, and it is shown that the phenomenon is due partly to the presence of DC offset currents in the induction machine stator, and partly to the mechanical shaft system of the wind turbine and the generator...
Dynamic electricity pricing—Which programs do consumers prefer?
International Nuclear Information System (INIS)
Dynamic pricing is being discussed as one method of demand side management (DSM) which could be crucial for integrating more renewable energy sources into the electricity system. At the same time, there have been very few analyses of consumer preferences in this regard: Which type of pricing program are consumers most likely to choose and why? This paper sheds some light on these issues based on two empirical studies from Germany: (1) A questionnaire study including a conjoint analysis-design and (2) A field experiment with test-residents of a smart home laboratory. The results show that consumers are open to dynamic pricing, but prefer simple programs to complex and highly dynamic ones; smart home technologies including demand automation are seen as a prerequisite for DSM. The study provides some indications that consumers might be more willing to accept more dynamic pricing programs if they have the chance to experience in practice how these can be managed in everyday life. At the same time, the individual and societal advantages of such programs are not obvious to consumers. For this reason, any market roll-out will need to be accompanied by convincing communication and information campaigns to ensure that these advantages are perceived. - Highlights: • Little is known about consumer preferences on dynamic pricing. • Two studies are conducted to analyze this topic. • A survey shows that consumers without experience prefer conventional programs. • Test residents of a smart home were more open to dynamic pricing. • They also prefer well-structured programs
Including UPFC dynamic phasor model into transient stability program
Ni, Y; Liu, H.; Zhu, H; Li, Y
2005-01-01
In this paper a novel time simulation approach is introduced to implement transient stability analysis with FACTS devices, in which FACTS devices will use dynamic phasor models and interface properly with conventional electromechanical transient-model-based stability program. The unified power flow controller (UPFC) is used as an example to demo the realization of the approach. In the paper, the UPFC dynamic phasor model and control scheme are presented first and followed by the interface for...
Non-convex dynamic programming and optimal investment
Penannen, Teemu; Perkkiö, Ari-Pekka; Rásonyi, Miklós
2015-01-01
We establish the existence of minimizers in a rather general setting of dynamic stochastic optimization without assuming either convexity or coercivity of the objective function. We apply this to prove the existence of optimal portfolios for non-concave utility maximization problems in financial market models with frictions (such as illiquidity), a first result of its kind. The proofs are based on the dynamic programming principle whose validity is established under quite general assumptions.
Multi-view video color correction using dynamic programming
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.
Dynamic Programming for Mean-field type Control
Laurière, Mathieu; Pironneau, Olivier
2014-01-01
For mean-field type control problems, stochastic dynamic programming requires adaptation. We propose to reformulate the problem as a distributed control problem by assuming that the PDF $\\rho$ of the stochastic process exists. Then we show that Bellman's principle applies to the dynamic programming value function $V(\\tau,\\rho_\\tau)$ where the dependency on $\\rho_\\tau$ is functional as in P.L. Lions' analysis of mean-filed games (2007). We derive HJB equations and apply them to two examples, a...
Fast and Cache-Oblivious Dynamic Programming with Local Dependencies
DEFF Research Database (Denmark)
Bille, Philip; Stöckel, Morten
2012-01-01
are widely used in bioinformatics to compare DNA and protein sequences. These problems can all be solved using essentially the same dynamic programming scheme over a two-dimensional matrix, where each entry depends locally on at most 3 neighboring entries. We present a simple, fast, and cache......-oblivious algorithm for this type of local dynamic programming suitable for comparing large-scale strings. Our algorithm outperforms the previous state-of-the-art solutions. Surprisingly, our new simple algorithm is competitive with a complicated, optimized, and tuned implementation of the best cache-aware algorithm...
Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot
Directory of Open Access Journals (Sweden)
Marcin Szuster
2014-01-01
Full Text Available Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal. The structure of the supervisory term derives from the stability analysis realised using the Lyapunov stability theorem. The globalised dual heuristic dynamic programming algorithm consists of two structures: the actor and the critic, realised in a form of neural networks. The actor generates the suboptimal control law, while the critic evaluates the realised control strategy by approximation of value function from the Bellman’s equation. The presented discrete tracking control system works online, the neural networks’ weights adaptation process is realised in every iteration step, and the neural networks preliminary learning procedure is not required. The performance of the proposed control system was verified by a series of computer simulations and experiments realised using the wheeled mobile robot Pioneer 2-DX.
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.
General Existence of Solutions to Dynamic Programming Principle
Liu, Qing; Schikorra, Armin
2013-01-01
We provide an alternative approach to the existence of solutions to dynamic programming equations arising in the discrete game-theoretic interpretations for various nonlinear partial differential equations including the infinity Laplacian, mean curvature flow and Hamilton-Jacobi type. Our general result is similar to Perron's method but adapted to the discrete situation.
Chatterjee, Koushik; Pastorczak, Ewa; Jawulski, Konrad; Pernal, Katarzyna
2016-06-01
A perfect-pairing generalized valence bond (GVB) approximation is known to be one of the simplest approximations, which allows one to capture the essence of static correlation in molecular systems. In spite of its attractive feature of being relatively computationally efficient, this approximation misses a large portion of dynamic correlation and does not offer sufficient accuracy to be generally useful for studying electronic structure of molecules. We propose to correct the GVB model and alleviate some of its deficiencies by amending it with the correlation energy correction derived from the recently formulated extended random phase approximation (ERPA). On the examples of systems of diverse electronic structures, we show that the resulting ERPA-GVB method greatly improves upon the GVB model. ERPA-GVB recovers most of the electron correlation and it yields energy barrier heights of excellent accuracy. Thanks to a balanced treatment of static and dynamic correlation, ERPA-GVB stays reliable when one moves from systems dominated by dynamic electron correlation to those for which the static correlation comes into play.
Shoemaker, David M.
Described and listed herein with concomitant sample input and output is the Fortran IV program which estimates parameters and standard errors of estimate per parameters for parameters estimated through multiple matrix sampling. The specific program is an improved and expanded version of an earlier version. (Author/BJG)
Ahlkrona, Josefin; Lötstedt, Per; Kirchner, Nina; Zwinger, Thomas
2016-03-01
We propose and implement a new method, called the Ice Sheet Coupled Approximation Levels (ISCAL) method, for simulation of ice sheet flow in large domains during long time-intervals. The method couples the full Stokes (FS) equations with the Shallow Ice Approximation (SIA). The part of the domain where SIA is applied is determined automatically and dynamically based on estimates of the modeling error. For a three dimensional model problem, ISCAL computes the solution substantially faster with a low reduction in accuracy compared to a monolithic FS. Furthermore, ISCAL is shown to be able to detect rapid dynamic changes in the flow. Three different error estimations are applied and compared. Finally, ISCAL is applied to the Greenland Ice Sheet on a quasi-uniform grid, proving ISCAL to be a potential valuable tool for the ice sheet modeling community.
Ahlkrona, Josefin; Kirchner, Nina; Zwinger, Thomas
2015-01-01
We propose and implement a new method, called the Ice Sheet Coupled Approximation Levels (ISCAL) method, for simulation of ice sheet flow in large domains under long time-intervals. The method couples the exact, full Stokes (FS) equations with the Shallow Ice Approximation (SIA). The part of the domain where SIA is applied is determined automatically and dynamically based on estimates of the modeling error. For a three dimensional model problem where the number of degrees of freedom is comparable to a real world application, ISCAL performs almost an order of magnitude faster with a low reduction in accuracy compared to a monolithic FS. Furthermore, ISCAL is shown to be able to detect rapid dynamic changes in the flow. Three different error estimations are applied and compared. Finally, ISCAL is applied to the Greenland Ice Sheet, proving ISCAL to be a potential valuable tool for the ice sheet modeling community.
Directory of Open Access Journals (Sweden)
Wenjie Bi
2014-01-01
Full Text Available Dynamic portfolio choice is an important problem in finance, but the optimal strategy analysis is difficult when considering multiple stochastic volatility variables such as the stock price, interest rate, and income. Besides, recent research in experimental economics indicates that the agent shows limited attention, considering only the variables with high fluctuations but ignoring those with small ones. By extending the sparse max method, we propose an approach to solve dynamic programming problem with small stochastic volatility and the agent’s bounded rationality. This approach considers the agent’s behavioral factors and avoids effectively the “Curse of Dimensionality” in a dynamic programming problem with more than a few state variables. We then apply it to Merton dynamic portfolio choice model with stochastic volatility and get a tractable solution. Finally, the numerical analysis shows that the bounded rational agent may pay no attention to the varying equity premium and interest rate with small variance.
Hughes, S. S.; Nawotniak, S. E. Kobs; Borg, C.; Mallonee, H. C.; Purcell, S.; Neish, C.; Garry, W. B.; Haberle, C. W.; Lim, D. S. S.; Heldmann, J. L.
2016-01-01
Compositionally and morphologically diverse lava flows erupted on the Great Rift of Idaho approximately 2.2 ka (kilo-annum, 1000 years ago) during a volcanic "flare-up" of activity following an approximately 2 ky (kiloyear, 1000 years) hiatus in eruptions. Volcanism at Craters of the Moon (COTM), Wapi and Kings Bowl lava fields around this time included primitive and evolved compositions, separated over 75 kilometers along the approximately 85 kilometers-long rift, with striking variability in lava flow emplacement mechanisms and surface morphologies. Although the temporal associations may be coincidental, the system provides a planetary analog to better understand magma dynamics along rift systems, including that associated with lunar floor-fractured craters. This study aims to help bridge the knowledge gap between ancient rift volcanism evident on the Moon and other terrestrial planets, and active rift volcanism, e.g., at Hawai'i and Iceland.
Motorin, A. A.; Stupitsky, E. L.; Kholodov, A. S.
2016-07-01
The spatiotemporal pattern for the development of a plasma cloud formed in the ionosphere and the main cloud gas-dynamic characteristics have been obtained from 3D calculations of the explosion-type plasmodynamic flows previously performed by us. An approximate method for estimating the plasma temperature and ionization degree with the introduction of the effective adiabatic index has been proposed based on these results.
Niven, Ivan
2008-01-01
This self-contained treatment originated as a series of lectures delivered to the Mathematical Association of America. It covers basic results on homogeneous approximation of real numbers; the analogue for complex numbers; basic results for nonhomogeneous approximation in the real case; the analogue for complex numbers; and fundamental properties of the multiples of an irrational number, for both the fractional and integral parts.The author refrains from the use of continuous fractions and includes basic results in the complex case, a feature often neglected in favor of the real number discuss
Improvement of DYANA. The dynamic analysis program for event transition
International Nuclear Information System (INIS)
In the probabilistic safety assessment (PSA), the fault tree/event tree technique has been widely used to evaluate accident sequence frequencies. However, event transition which operators actually face can not be dynamically treated by the conventional technique. Therefore, we have made the dynamic analysis program(DYANA) for event transition for a liquid metal cooled fast breeder reactor. In the previous development, we made basic model for analysis. However, we have a problem that calculation time is too long. At the current term, we made parallelization of DYANA using MPI. So we got good performance on WS claster. It performance is close to ideal one. (author)
Dynamic Programming for Structured Continuous Markov Decision Problems
Dearden, Richard; Meuleau, Nicholas; Washington, Richard; Feng, Zhengzhu
2004-01-01
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it to piecewise linear representations, using techniques from POMDPs to represent and reason about linear surfaces efficiently. We show that for complex, structured problems, our approach exploits the natural structure so that optimal solutions can be computed efficiently.
Elia, Petros
2007-01-01
Explicit codes are constructed that achieve the diversity-multiplexing gain tradeoff of the cooperative-relay channel under the dynamic decode-and-forward protocol for any network size, for all delays and for all numbers of transmit and receive antennas at the relays.
Park, Se Yong; Sahai, Anant
2013-01-01
Continuing the first part of the paper, we consider scalar decentralized average-cost infinite-horizon LQG problems with two controllers. This paper focuses on the slow dynamics case when the eigenvalue of the system is small and prove that the single-controller optimal strategies ---linear strategies--- are constant ratio optimal among all distributed control strategies.
2006-01-01
This interactive tutorial presents the following concepts of Approximation Techniques: Methods of Weighted Residual (MWR), Weak Formulatioin, Piecewise Continuous Function, Galerkin Finite Element FormulationExplanations especially for mathematical statements are provided using mouseover the highlight equations. ME4613 Finite Element Methods
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
A B-Spline-Based Colocation Method to Approximate the Solutions to the Equations of Fluid Dynamics
Energy Technology Data Exchange (ETDEWEB)
Johnson, Richard Wayne; Landon, Mark Dee
1999-07-01
The potential of a B-spline collocation method for numerically solving the equations of fluid dynamics is discussed. It is known that B-splines can resolve curves with drastically fewer data than can their standard shape function counterparts. This feature promises to allow much faster numerical simulations of fluid flow than standard finite volume/finite element methods without sacrificing accuracy. An example channel flow problem is solved using the method.
A B-Spline-Based Colocation Method to Approximate the Solutions to the Equations of Fluid Dynamics
Energy Technology Data Exchange (ETDEWEB)
M. D. Landon; R. W. Johnson
1999-07-01
The potential of a B-spline collocation method for numerically solving the equations of fluid dynamics is discussed. It is known that B-splines can resolve complex curves with drastically fewer data than can their standard shape function counterparts. This feature promises to allow much faster numerical simulations of fluid flow than standard finite volume/finite element methods without sacrificing accuracy. An example channel flow problem is solved using the method.
Neuro-dynamic programming for cooperative inventory control
Bauso, D.; Giarré, L.; Pesenti, R.
2004-01-01
In Multi-Retailer Inventory Control the possibility of sharing set up costs motivates communication and coordination among the retailers. We solve the problem of finding suboptimal distributed reordering policies which minimize set up, ordering, storage and shortage costs, incurred by the retailers over a finite horizon. Neuro-Dynamic Programming (NDP) reduces the computational complexity of the solution algorithm from exponential to polynomial on the number of retailers.
Restricted Dynamic Programming Heuristic for Precedence Constrained Bottleneck Generalized TSP
Salii, Y.
2015-01-01
We develop a restricted dynamical programming heuristic for a complicated traveling salesman problem: a) cities are grouped into clusters, resp. Generalized TSP; b) precedence constraints are imposed on the order of visiting the clusters, resp. Precedence Constrained TSP; c) the costs of moving to the next cluster and doing the required job inside one are aggregated in a minimax manner, resp. Bottleneck TSP; d) all the costs may depend on the sequence of previously visited clusters, resp. Seq...
Systems and methods for interpolation-based dynamic programming
Rockwood, Alyn
2013-01-03
Embodiments of systems and methods for interpolation-based dynamic programming. In one embodiment, the method includes receiving an object function and a set of constraints associated with the objective function. The method may also include identifying a solution on the objective function corresponding to intersections of the constraints. Additionally, the method may include generating an interpolated surface that is in constant contact with the solution. The method may also include generating a vector field in response to the interpolated surface.
Risk-aware decision making and dynamic programming
Defourny, Boris; Ernst, Damien; Wehenkel, Louis
2008-01-01
This paper considers sequential decision making problems under uncertainty, the tradeoff between the expected return and the risk of high loss, and methods that use dynamic programming to find optimal policies. It is argued that using Bellman's Principle determines how risk considerations on the return can be incorporated. The discussion centers around returns generated by Markov Decision Processes and conclusions concern a large class of methods in Reinforcement Learning.
Deterministic Dynamic Programming in Discrete Time: A Monotone Convergence Principle
Takashi Kamihigashi; Masayuki Yao
2015-01-01
We consider infinite-horizon deterministic dynamic programming problems in discrete time. We show that the value function is always a fixed point of a modified version of the Bellman operator. We also show that value iteration monotonically converges to the value function if the initial function is dominated by the value function, is mapped upward by the modified Bellman operator, and satisfies a transversality-like condition. These results require no assumption except for the general framewo...
SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
Viorel MINZU
2015-12-01
Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.
Grip, Helena; Tengman, Eva; Häger, Charlotte K
2015-07-16
Finite helical axis (FHA) measures of the knee joint during weight-bearing tasks may capture dynamic knee stability following Anterior Cruciate Ligament (ACL) injury. The aim was to investigate dynamic knee stability during two-leg squat (TLS) and one-leg side hop (SH) in a long-term follow-up of ACL injury, and to examine correlations with knee laxity (KT-1000), osteoarthritis (OA, Kellgren-Lawrence) and knee function (Lysholm score). Participants were injured 17-28 years ago and then treated with surgery (n=33, ACLR) or physiotherapy only (n=37, ACLPT) and healthy-knee controls (n=33) were tested. Movements were registered with an optical motion capture system. We computed three FHA inclination angles, its' Anterior-Posterior (A-P) position, and an index quantifying directional changes (DI), during stepwise knee flexion intervals of ∼15°. Injured knees were less stable compared to healthy controls' and to contralateral non-injured knees, regardless of treatment: the A-P intersection was more anterior (indicating a more anterior positioning of tibia relative to femur) positively correlating with high laxity/low knee function, and during SH, the FHA was more inclined relative to the flexion-extension axis, possibly due to reduced rotational stability. During the TLS, A-P intersection was more anterior in the non-injured knee than the injured, and DI was higher, probably related to higher load on the non-injured knee. ACLR had less anterior A-P intersection than ACLPT, suggesting that surgery enhanced stability, although rotational stability may remain reduced. More anterior A-P intersection and greater inclination between the FHA and the knee flexion-extension axis best revealed reduced dynamic stability ∼23 years post-injury.
Programming Unconventional Computers: Dynamics, Development, Self-Reference
Directory of Open Access Journals (Sweden)
Susan Stepney
2012-10-01
Full Text Available Classical computing has well-established formalisms for specifying, refining, composing, proving, and otherwise reasoning about computations. These formalisms have matured over the past 70 years or so. Unconventional Computing includes the use of novel kinds of substrates–from black holes and quantum effects, through to chemicals, biomolecules, even slime moulds–to perform computations that do not conform to the classical model. Although many of these unconventional substrates can be coerced into performing classical computation, this is not how they “naturally” compute. Our ability to exploit unconventional computing is partly hampered by a lack of corresponding programming formalisms: we need models for building, composing, and reasoning about programs that execute in these substrates. What might, say, a slime mould programming language look like? Here I outline some of the issues and properties of these unconventional substrates that need to be addressed to find “natural” approaches to programming them. Important concepts include embodied real values, processes and dynamical systems, generative systems and their meta-dynamics, and embodied self-reference.
Directory of Open Access Journals (Sweden)
Bruno H. Dias
2010-01-01
Full Text Available This paper presents a new approach for the expected cost-to-go functions modeling used in the stochastic dynamic programming (SDP algorithm. The SDP technique is applied to the long-term operation planning of electrical power systems. Using state space discretization, the Convex Hull algorithm is used for constructing a series of hyperplanes that composes a convex set. These planes represent a piecewise linear approximation for the expected cost-to-go functions. The mean operational costs for using the proposed methodology were compared with those from the deterministic dual dynamic problem in a case study, considering a single inflow scenario. This sensitivity analysis shows the convergence of both methods and is used to determine the minimum discretization level. Additionally, the applicability of the proposed methodology for two hydroplants in a cascade is demonstrated. With proper adaptations, this work can be extended to a complete hydrothermal system.
Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai
2013-09-01
In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
Wang, Anna; Fung, Jerome; Razavi, Sepideh; Kretzschmar, Ilona; Chaudhary, Kundan; Lewis, Jennifer A; Manoharan, Vinothan N
2013-01-01
We present a new, high-speed technique to track the three-dimensional translation and rotation of non-spherical colloidal particles. We capture digital holograms of micrometer-scale silica rods and sub-micrometer-scale Janus particles freely diffusing in water, and then fit numerical scattering models based on the discrete dipole approximation to the measured holograms. This inverse-scattering approach allows us to extract the the position and orientation of the particles as a function of time, along with static parameters including the size, shape, and refractive index. The best-fit sizes and refractive indices of both particles agree well with expected values. The technique is able to track the center of mass of the rod to a precision of 35 nm and its orientation to a precision of 1.5$^\\circ$, comparable to or better than the precision of other 3D diffusion measurements on non-spherical particles. Furthermore, the measured translational and rotational diffusion coefficients for the silica rods agree with hy...
Approximate Representations and Approximate Homomorphisms
Moore, Cristopher
2010-01-01
Approximate algebraic structures play a defining role in arithmetic combinatorics and have found remarkable applications to basic questions in number theory and pseudorandomness. Here we study approximate representations of finite groups: functions f:G -> U_d such that Pr[f(xy) = f(x) f(y)] is large, or more generally Exp_{x,y} ||f(xy) - f(x)f(y)||^2$ is small, where x and y are uniformly random elements of the group G and U_d denotes the unitary group of degree d. We bound these quantities in terms of the ratio d / d_min where d_min is the dimension of the smallest nontrivial representation of G. As an application, we bound the extent to which a function f : G -> H can be an approximate homomorphism where H is another finite group. We show that if H's representations are significantly smaller than G's, no such f can be much more homomorphic than a random function. We interpret these results as showing that if G is quasirandom, that is, if d_min is large, then G cannot be embedded in a small number of dimensi...
Supplier selection and order lot sizing using dynamic programming
Directory of Open Access Journals (Sweden)
M. M. Moqri
2011-04-01
Full Text Available In this paper, we consider a multi-period integrated supplier selection and order lot sizing problem where a single buyer plans to purchase a single product in multiple periods from several qualified suppliers who are able to provide the required product with the needed quality in a timely manner. Product price and order cost differs among different suppliers. Buyer’s demand for the product is deterministic and varies for different time periods. The problem is to determine how much product from which supplier must be ordered in each period such that buyer’s demand is satisfied without violating some side constraints. We have developed a mathematical programming model to deal with this problem, and proposed a forward dynamic programming approach to obtain optimal solutions in reasonable amount of time even for large scale problems. Finally, a numerical example is conducted in which solutions obtained from the proposed dynamic programming algorithm is compared with solutions from the branch-and-bound algorithm. Through the numerical example we have shown the efficiency of our algorithm.
CERN. Geneva
2015-01-01
Most physics results at the LHC end in a likelihood ratio test. This includes discovery and exclusion for searches as well as mass, cross-section, and coupling measurements. The use of Machine Learning (multivariate) algorithms in HEP is mainly restricted to searches, which can be reduced to classification between two fixed distributions: signal vs. background. I will show how we can extend the use of ML classifiers to distributions parameterized by physical quantities like masses and couplings as well as nuisance parameters associated to systematic uncertainties. This allows for one to approximate the likelihood ratio while still using a high dimensional feature vector for the data. Both the MEM and ABC approaches mentioned above aim to provide inference on model parameters (like cross-sections, masses, couplings, etc.). ABC is fundamentally tied Bayesian inference and focuses on the “likelihood free” setting where only a simulator is available and one cannot directly compute the likelihood for the dat...
Schmidt, Wolfgang M
1980-01-01
"In 1970, at the U. of Colorado, the author delivered a course of lectures on his famous generalization, then just established, relating to Roth's theorem on rational approxi- mations to algebraic numbers. The present volume is an ex- panded and up-dated version of the original mimeographed notes on the course. As an introduction to the author's own remarkable achievements relating to the Thue-Siegel-Roth theory, the text can hardly be bettered and the tract can already be regarded as a classic in its field."(Bull.LMS) "Schmidt's work on approximations by algebraic numbers belongs to the deepest and most satisfactory parts of number theory. These notes give the best accessible way to learn the subject. ... this book is highly recommended." (Mededelingen van het Wiskundig Genootschap)
Musical structure analysis using similarity matrix and dynamic programming
Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay
2005-10-01
Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.
Directory of Open Access Journals (Sweden)
Walberer Maureen
2010-12-01
Full Text Available Abstract Background Neuroinflammation evolves as a multi-facetted response to focal cerebral ischemia. It involves activation of resident glia cell populations, recruitment of blood-derived leucocytes as well as humoral responses. Among these processes, phagocyte accumulation has been suggested to be a surrogate marker of neuroinflammation. We previously assessed phagocyte accumulation in human stroke by MRI. We hypothesize that phagocyte accumulation in the macrosphere model may resemble the temporal and spatial patterns observed in human stroke. Methods In a rat model of permanent focal ischemia by embolisation of TiO2-spheres we assessed key features of post-ischemic neuroinflammation by the means of histology, immunocytochemistry of glial activation and influx of hematogeneous cells, and quantitative PCR of TNF-α, IL-1, IL-18, and iNOS mRNA. Results In the boundary zone of the infarct, a transition of ramified microglia into ameboid phagocytic microglia was accompanied by an up-regulation of MHC class II on the cells after 3 days. By day 7, a hypercellular infiltrate consisting of activated microglia and phagocytic cells formed a thick rim around the ischemic infarct core. Interestingly, in the ischemic core microglia could only be observed at day 7. TNF-α was induced rapidly within hours, IL-1β and iNOS peaked within days, and IL-18 later at around 1 week after ischemia. Conclusions The macrosphere model closely resembles the characteristical dynamics of postischemic inflammation previously observed in human stroke. We therefore suggest that the macrosphere model is highly appropriate for studying the pathophysiology of stroke in a translational approach from rodent to human.
Heuristic reusable dynamic programming: efficient updates of local sequence alignment.
Hong, Changjin; Tewfik, Ahmed H
2009-01-01
Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm. PMID:19875856
Modelling dynamic programming problems by generalized d-graphs
Kátai, Zoltán
2010-01-01
In this paper we introduce the concept of generalized d-graph (admitting cycles) as special dependency-graphs for modelling dynamic programming (DP) problems. We describe the d-graph versions of three famous single-source shortest algorithms (The algorithm based on the topological order of the vertices, Dijkstra algorithm and Bellman-Ford algorithm), which can be viewed as general DP strategies in the case of three different class of optimization problems. The new modelling method also makes possible to classify DP problems and the corresponding DP strategies in term of graph theory.
Dynamic programming and graph algorithms in computer vision.
Felzenszwalb, Pedro F; Zabih, Ramin
2011-04-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.
GOP-Level Bit Allocation Using Reverse Dynamic Programming
Institute of Scientific and Technical Information of China (English)
LU Yang; XIE Jun; LI Hang; CUI Huijuan
2009-01-01
An efficient adaptive group of pictures (GOP)-Ievel bit allocation algorithm was developed based on reverse dynamic programming (RDP). The algorithm gives the initial delay and sequence distortion curve with just one iteration of the algorithm. A simple GOP-level rate and distortion model was then developed for two-level constant quality rate control. The initial delay values and the corresponding optimal GOP-level bit allocation scheme can be obtained for video streaming along with the proper initial delay for various distortion tolerance levels. Simulations show that the algorithm provides an efficient solution for delay and buffer con-strained GOP-level rate control for video streaming.
Dynamic programming parallel implementations for the knapsack problem
Andonov, Rumen; Raimbault, Frédéric; Quinton, Patrice
1993-01-01
A systolic algorithm for the dynamic programming approach to the knapsack problem is presented. The algorithm can run on any number of processors and has optimal time speedup and processor efficiency. The running time of the algorithm is [??](mc/q+m) on a ring of q processors, where c is the knapsack size and m is the number of object types. A new procedure for the backtracking phase of the algorithm with a time complexity [??](m) is also proposed which is an improvement on the usual strategi...
Dynamic Program Phase Detection in Distributed Shared-Memory Multiprocessors
Energy Technology Data Exchange (ETDEWEB)
Ipek, E; Martinez, J F; de Supinski, B R; McKee, S A; Schulz, M
2006-03-06
We present a novel hardware mechanism for dynamic program phase detection in distributed shared-memory (DSM) multiprocessors. We show that successful hardware mechanisms for phase detection in uniprocessors do not necessarily work well in DSM systems, since they lack the ability to incorporate the parallel application's global execution information and memory access behavior based on data distribution. We then propose a hardware extension to a well-known uniprocessor mechanism that significantly improves phase detection in the context of DSM multiprocessors. The resulting mechanism is modest in size and complexity, and is transparent to the parallel application.
CASSANDRE, 2-D Reactor Dynamic FEM Program with Thermohydraulic Feedback
International Nuclear Information System (INIS)
1 - Description of program or function: CASSANDRE is a two-dimensional (x-y or r-z) finite-elements neutronics code with thermohydraulic feedback for reactor dynamics prior to the disassembly phase. The code was conceived in order to be coupled with any thermohydraulics module, although thermohydraulics feedback is only considered in r-z geometry. In the steady state, criticality search is possible either by control-rod insertion or by homogeneous poisoning of the coolant. 2 - Method of solution: The program uses multigroup diffusion theory. Its main characteristics are the use of a generalized quasi-static model, the use of a flexible multigroup point-kinetics algorithm allowing for spectral matching, and the use of a finite elements description. 3 - Restrictions on the complexity of the problem: The user must prepare a cross section library
International Nuclear Information System (INIS)
A new finding of the site-averaging approximation was recently reported on the dissociative chemisorption of the HCl/DCl+Au(111) surface reaction [T. Liu, B. Fu, and D. H. Zhang, J. Chem. Phys. 139, 184705 (2013); T. Liu, B. Fu, and D. H. Zhang, J. Chem. Phys. 140, 144701 (2014)]. Here, in order to investigate the dependence of new site-averaging approximation on the initial vibrational state of H2 as well as the PES for the dissociative chemisorption of H2 on Cu(111) surface at normal incidence, we carried out six-dimensional quantum dynamics calculations using the initial state-selected time-dependent wave packet approach, with H2 initially in its ground vibrational state and the first vibrational excited state. The corresponding four-dimensional site-specific dissociation probabilities are also calculated with H2 fixed at bridge, center, and top sites. These calculations are all performed based on two different potential energy surfaces (PESs). It is found that the site-averaging dissociation probability over 15 fixed sites obtained from four-dimensional quantum dynamics calculations can accurately reproduce the six-dimensional dissociation probability for H2 (v = 0) and (v = 1) on the two PESs
The Design of Educational Programs in System Dynamics at Worcester Polytechnic Institute (WPI)
Oleg V. Pavlov; Doyle, James K.; Khalid Saeed; James M. Lyneis; Michael J. Radzicki
2014-01-01
Educational programs leading to degrees in system dynamics are rare and thus of critical importance to the future of the field of system dynamics. However, to a large extent such programs have not yet been made transparent to the system dynamics community as a whole. The present article describes the design and rationale for undergraduate and graduate programs at Worcester Polytechnic Institute (WPI). The goal of the article is to invite feedback from the system dynamics community about our s...
Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming
Saisho, Yuichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji
In deregulated electricity markets, the role of a distribution company is to purchase electricity from the wholesale electricity market at randomly fluctuating prices and to provide it to its customers at a given fixed price. Therefore the company has to take risk stemming from the uncertainties of electricity prices and/or demand fluctuation instead of the customers. The way to avoid the risk is to make a bilateral contact with generating companies or install its own power generation facility. This entails the necessity to develop a certain method to make an optimal strategy for electric power procurement. In such a circumstance, this research has the purpose for proposing a mathematical method based on stochastic dynamic programming and additionally considering the characteristics of the start-up cost of electric power generation facility to evaluate strategies of combination of the bilateral contract and power auto-generation with its own facility for procuring electric power in deregulated electricity market. In the beginning we proposed two approaches to solve the stochastic dynamic programming, and they are a Monte Carlo simulation method and a finite difference method to derive the solution of a partial differential equation of the total procurement cost of electric power. Finally we discussed the influences of the price uncertainty on optimal strategies of power procurement.
A mathematical programming approach for sequential clustering of dynamic networks
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
Directory of Open Access Journals (Sweden)
Rebecca Lee Smith
Full Text Available Hansen's disease (leprosy elimination has proven difficult in several countries, including Brazil, and there is a need for a mathematical model that can predict control program efficacy. This study applied the Approximate Bayesian Computation algorithm to fit 6 different proposed models to each of the 5 regions of Brazil, then fitted hierarchical models based on the best-fit regional models to the entire country. The best model proposed for most regions was a simple model. Posterior checks found that the model results were more similar to the observed incidence after fitting than before, and that parameters varied slightly by region. Current control programs were predicted to require additional measures to eliminate Hansen's Disease as a public health problem in Brazil.
Smith, Rebecca Lee; Gröhn, Yrjö Tapio
2015-01-01
Hansen's disease (leprosy) elimination has proven difficult in several countries, including Brazil, and there is a need for a mathematical model that can predict control program efficacy. This study applied the Approximate Bayesian Computation algorithm to fit 6 different proposed models to each of the 5 regions of Brazil, then fitted hierarchical models based on the best-fit regional models to the entire country. The best model proposed for most regions was a simple model. Posterior checks found that the model results were more similar to the observed incidence after fitting than before, and that parameters varied slightly by region. Current control programs were predicted to require additional measures to eliminate Hansen's Disease as a public health problem in Brazil. PMID:26107951
Patriarca, M.; Kuronen, A.; Robles, M.; Kaski, K.
2007-01-01
The study of crystal defects and the complex processes underlying their formation and time evolution has motivated the development of the program ALINE for interactive molecular dynamics experiments. This program couples a molecular dynamics code to a Graphical User Interface and runs on a UNIX-X11 Window System platform with the MOTIF library, which is contained in many standard Linux releases. ALINE is written in C, thus giving the user the possibility to modify the source code, and, at the same time, provides an effective and user-friendly framework for numerical experiments, in which the main parameters can be interactively varied and the system visualized in various ways. We illustrate the main features of the program through some examples of detection and dynamical tracking of point-defects, linear defects, and planar defects, such as stacking faults in lattice-mismatched heterostructures. Program summaryTitle of program:ALINE Catalogue identifier:ADYJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYJ_v1_0 Program obtainable from: CPC Program Library, Queen University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Computers:DEC ALPHA 300, Intel i386 compatible computers, G4 Apple Computers Installations:Laboratory of Computational Engineering, Helsinki University of Technology, Helsinki, Finland Operating systems under which the program has been tested:True64 UNIX, Linux-i386, Mac OS X 10.3 and 10.4 Programming language used:Standard C and MOTIF libraries Memory required to execute with typical data:6 Mbytes but may be larger depending on the system size No. of lines in distributed program, including test data, etc.:16 901 No. of bytes in distributed program, including test data, etc.:449 559 Distribution format:tar.gz Nature of physical problem:Some phenomena involving defects take place inside three-dimensional crystals at times which can be hardly predicted. For this reason they are
Estimating Arrhenius parameters using temperature programmed molecular dynamics
Imandi, Venkataramana; Chatterjee, Abhijit
2016-07-01
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
Novel algorithm for distributed replicas management based on dynamic programming
Institute of Scientific and Technical Information of China (English)
Wang Tao; Lu Xianliang; Hou Mengshu
2006-01-01
Replicas can improve the data reliability in distributed system. However, the traditional algorithms for replica management are based on the assumption that all replicas have the uniform reliability, which is inaccurate in some actual systems. To address such problem, a novel algorithm is proposed based on dynamic programming to manage the number and distribution of replicas in different nodes. By using Markov model, replicas management is organized as a multi-phase process, and the recursion equations are provided. In this algorithm, the heterogeneity of nodes, the expense for maintaining replicas and the engaged space have been considered. Under these restricted conditions, this algorithm realizes high data reliability in a distributed system. The results of case analysis prove the feasibility of the algorithm.
Dynamic programming on a tree for ultrasound elastography
Shams, Roozbeh; Boily, Mathieu; Martineau, Paul A.; Rivaz, Hassan
2016-04-01
Ultrasound Elastography is an emerging imaging technique that allows estimation of the mechanical characteristics of tissue. Two issues that need to be addressed before widespread use of elastography in clinical environments are real time constraints and deteriorating effects of signal decorrelation between pre- and post-compression images. Previous work has used Dynamic Programming (DP) to estimate tissue deformation. However, in case of large signal decorrelation, DP can fail. In this paper we, have proposed a novel solution to this problem by solving DP on a tree instead of a single Radio-Frequency line. Formulation of DP on a tree allows exploiting significantly more information, and as such, is more robust and accurate. Our results on phantom and in-vivo human data show that DP on tree significantly outperforms traditional DP in ultrasound elastography.
Condition-dependent mate choice: A stochastic dynamic programming approach.
Frame, Alicia M; Mills, Alex F
2014-09-01
We study how changing female condition during the mating season and condition-dependent search costs impact female mate choice, and what strategies a female could employ in choosing mates to maximize her own fitness. We address this problem via a stochastic dynamic programming model of mate choice. In the model, a female encounters males sequentially and must choose whether to mate or continue searching. As the female searches, her own condition changes stochastically, and she incurs condition-dependent search costs. The female attempts to maximize the quality of the offspring, which is a function of the female's condition at mating and the quality of the male with whom she mates. The mating strategy that maximizes the female's net expected reward is a quality threshold. We compare the optimal policy with other well-known mate choice strategies, and we use simulations to examine how well the optimal policy fares under imperfect information.
NEW METHOD FOR SHAPE RECOGNITION BASED ON DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
NOREDINNE GHERABI
2011-02-01
Full Text Available In this paper we present a new method for shape recognition based on dynamic programming. First, each contour of shape is represented by a set of points. After alignment and matching between two shapes, the outline of the shape is divided into parts according to N angular and M radial sectors , Each Sector contains a portion of the contour; thisportion is divided at the inflexion points into convex and concave sections, and the information about sections are extracted in order to provide a semantic content to the outline shape, then this information are coded and transformed into a string of symbols. Finally we find the best alignment of two complete strings and compute the optimal cost of similarity. The algorithm has been tested on a large set of shape databases and real images (MPEG-7, natural silhouette database.
Dynamic programming algorithm for detecting dim infrared moving targets
He, Lisha; Mao, Liangjing; Xie, Lijun
2009-10-01
Infrared (IR) target detection is a key part of airborne infrared weapon system, especially the detection of poor dim moving IR target embedded in complex context. This paper presents an improved Dynamic Programming (DP) algorithm in allusion to low Signal to Noise Ratio (SNR) infrared dim moving targets under cluttered context. The algorithm brings the dim target to prominence by accumulating the energy of pixels in the image sequence, after suppressing the background noise with a mathematical morphology preprocessor. As considering the continuity and stabilization of target's energy and forward direction, this algorithm has well solved the energy scattering problem that exists in the original DP algorithm. An effective energy segmentation threshold is given by a Contrast-Limited Adaptive Histogram Equalization (CLAHE) filter with a regional peak extraction algorithm. Simulation results show that the improved DP tracking algorithm performs well in detecting poor dim targets.
Optimal approach to quantum communication using dynamic programming.
Jiang, Liang; Taylor, Jacob M; Khaneja, Navin; Lukin, Mikhail D
2007-10-30
Reliable preparation of entanglement between distant systems is an outstanding problem in quantum information science and quantum communication. In practice, this has to be accomplished by noisy channels (such as optical fibers) that generally result in exponential attenuation of quantum signals at large distances. A special class of quantum error correction protocols, quantum repeater protocols, can be used to overcome such losses. In this work, we introduce a method for systematically optimizing existing protocols and developing more efficient protocols. Our approach makes use of a dynamic programming-based searching algorithm, the complexity of which scales only polynomially with the communication distance, letting us efficiently determine near-optimal solutions. We find significant improvements in both the speed and the final-state fidelity for preparing long-distance entangled states. PMID:17959783
Chimeric alignment by dynamic programming: Algorithm and biological uses
Energy Technology Data Exchange (ETDEWEB)
Komatsoulis, G.A.; Waterman, M.S. [Univ. of Southern California, Los Angeles, CA (United States)
1997-12-01
A new nearest-neighbor method for detecting chimeric 16S rRNA artifacts generated during PCR amplification from mixed populations has been developed. The method uses dynamic programming to generate an optimal chimeric alignment, defined as the highest scoring alignment between a query and a concatenation of a 5{prime} and a 3{prime} segment from two separate entries from a database of related sequences. Chimeras are detected by studying the scores and form of the chimeric and global sequence alignments. The chimeric alignment method was found to be marginally more effective than k-tuple based nearest-neighbor methods in simulation studies, but its most effective use is in concert with k-tuple methods. 15 refs., 3 figs., 1 tab.
Dispersion analysis techniques within the space vehicle dynamics simulation program
Snow, L. S.; Kuhn, A. E.
1975-01-01
The Space Vehicle Dynamics Simulation (SVDS) program was evaluated as a dispersion analysis tool. The Linear Error Analysis (LEA) post processor was examined in detail and simulation techniques relative to conducting a dispersion analysis using the SVDS were considered. The LEA processor is a tool for correlating trajectory dispersion data developed by simulating 3 sigma uncertainties as single error source cases. The processor combines trajectory and performance deviations by a root-sum-square (RSS process) and develops a covariance matrix for the deviations. Results are used in dispersion analyses for the baseline reference and orbiter flight test missions. As a part of this study, LEA results were verified as follows: (A) Hand calculating the RSS data and the elements of the covariance matrix for comparison with the LEA processor computed data. (B) Comparing results with previous error analyses. The LEA comparisons and verification are made at main engine cutoff (MECO).
Application of dynamic programming to structural repairing strategies
Institute of Scientific and Technical Information of China (English)
陈朝晖; LIU; Xila; 等
2002-01-01
A model of dynamic programming for repairing strategies of concrete structures during a projected service period is proposed,which takes into account the degradation in strength of components and the probability of accidental load.This model takes the safety grade of a structural system as the state variable of repairing strategies,and incorporates economic factors including expected repair cost,property loss due to structure failure,goods and material loss due to structure failure,loss of production interrupt due to structure failure,and inspection cost in decision making.It is found that the optimal repairing strategies are sensitive to the probability of accidental loads as well as the failure costs.The practicality of the model is demonstrated by an example.
Mitochondrial Dynamics Controls T Cell Fate through Metabolic Programming.
Buck, Michael D; O'Sullivan, David; Klein Geltink, Ramon I; Curtis, Jonathan D; Chang, Chih-Hao; Sanin, David E; Qiu, Jing; Kretz, Oliver; Braas, Daniel; van der Windt, Gerritje J W; Chen, Qiongyu; Huang, Stanley Ching-Cheng; O'Neill, Christina M; Edelson, Brian T; Pearce, Edward J; Sesaki, Hiromi; Huber, Tobias B; Rambold, Angelika S; Pearce, Erika L
2016-06-30
Activated effector T (TE) cells augment anabolic pathways of metabolism, such as aerobic glycolysis, while memory T (TM) cells engage catabolic pathways, like fatty acid oxidation (FAO). However, signals that drive these differences remain unclear. Mitochondria are metabolic organelles that actively transform their ultrastructure. Therefore, we questioned whether mitochondrial dynamics controls T cell metabolism. We show that TE cells have punctate mitochondria, while TM cells maintain fused networks. The fusion protein Opa1 is required for TM, but not TE cells after infection, and enforcing fusion in TE cells imposes TM cell characteristics and enhances antitumor function. Our data suggest that, by altering cristae morphology, fusion in TM cells configures electron transport chain (ETC) complex associations favoring oxidative phosphorylation (OXPHOS) and FAO, while fission in TE cells leads to cristae expansion, reducing ETC efficiency and promoting aerobic glycolysis. Thus, mitochondrial remodeling is a signaling mechanism that instructs T cell metabolic programming. PMID:27293185
DYNAMIC PROGRAMMING – ITS PRINCIPLES, APPLICATIONS, STRENGTHS, AND LIMITATIONS
Directory of Open Access Journals (Sweden)
BISWAJIT BHOWMIK
2010-09-01
Full Text Available The massive increase in computation power over the last few decades has substantially enhanced our ability to solve complex problems with their performance evaluations in diverse areas of science and engineering. With the recent developments in the field of optimizations, these methods are now become lucrative to make decisions. Dynamic Programming is one of the elegant algorithm design standards and is powerful tool which yields classic algorithms for a variety of combinatorial optimization problems. In this paper fundamental working principles, major area of applications of this approach has been introduced. The strengths which make it more prevailing than the others is also opened up. Focusing the imperative drawbacks afterward comparison study of this algorithm design technique in this paper brings a general awareness to the implementation strategies.
Speed improvement of B-snake algorithm using dynamic programming optimization.
Charfi, Maher; Zrida, Jalel
2011-10-01
This paper presents a novel approach to contour approximation carried out by means of the B-snake algorithm and the dynamic programming (DP) optimization technique. Using the proposed strategy for contour point search procedure, computing complexity is reduced to O(N×M(2)), whereas the standard DP method has an O(N×M(4)) complexity, with N being the number of contour sample points and M being the number of candidates in the search space. The storage requirement was also decreased from N×M(3) to N×M memory elements. Some experiments on noise corrupted synthetic image, magnetic resonance, and computer tomography medical images have shown that the proposed approach results are equivalent to those obtained by the standard DP algorithm.
Dynamic Line Rating Oncor Electric Delivery Smart Grid Program
Energy Technology Data Exchange (ETDEWEB)
Johnson, Justin; Smith, Cale; Young, Mike; Donohoo, Ken; Owen, Ross; Clark, Eddit; Espejo, Raul; Aivaliotis, Sandy; Stelmak, Ron; Mohr, Ron; Barba, Cristian; Gonzalez, Guillermo; Malkin, Stuart; Dimitrova, Vessela; Ragsdale, Gary; Mitchem, Sean; Jeirath, Nakul; Loomis, Joe; Trevino, Gerardo; Syracuse, Steve; Hurst, Neil; Mereness, Matt; Johnson, Chad; Bivens, Carrie
2013-05-04
Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar
Diophantine approximations on fractals
Einsiedler, Manfred; Shapira, Uri
2009-01-01
We exploit dynamical properties of diagonal actions to derive results in Diophantine approximations. In particular, we prove that the continued fraction expansion of almost any point on the middle third Cantor set (with respect to the natural measure) contains all finite patterns (hence is well approximable). Similarly, we show that for a variety of fractals in [0,1]^2, possessing some symmetry, almost any point is not Dirichlet improvable (hence is well approximable) and has property C (after Cassels). We then settle by similar methods a conjecture of M. Boshernitzan saying that there are no irrational numbers x in the unit interval such that the continued fraction expansions of {nx mod1 : n is a natural number} are uniformly eventually bounded.
Knowledge representation and rule-based solution system for dynamic programming model
Institute of Scientific and Technical Information of China (English)
胡祥培; 王旭茵
2003-01-01
A knowledge representation has been proposed using the state-space theory of Artificial Intelligencefor Dynamic Programming Model, in which a model can be defined as a six-tuple M = (I,G,O,T,D,S). Abuilding block modeling method uses the modules of a six-tuple to form a rule-based solution model. Moreover,a rule-based system has been designed and set up to solve the Dynamic Programming Model. This knowledge-based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynam-ic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Program-ming Model can also be conveniently realized in computer.
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2009-01-01
efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce...
A stochastic dynamic programming model for stream water quality management
Indian Academy of Sciences (India)
P P Mujumdar; Pavan Saxena
2004-10-01
This paper deals with development of a seasonal fraction-removal policy model for waste load allocation in streams addressing uncertainties due to randomness and fuzziness. A stochastic dynamic programming (SDP) model is developed to arrive at the steady-state seasonal fraction-removal policy. A fuzzy decision model (FDM) developed by us in an earlier study is used to compute the system performance measure required in the SDP model. The state of the system in a season is deﬁned by streamﬂows at the headwaters during the season and the initial DO deﬁcit at some pre-speciﬁed checkpoints. The random variation of streamﬂows is included in the SDP model through seasonal transitional probabilities. The decision vector consists of seasonal fraction-removal levels for the efﬂuent dischargers. Uncertainty due to imprecision (fuzziness) associated with water quality goals is addressed using the concept of fuzzy decision. Responses of pollution control agencies to the resulting end-of-season DO deﬁcit vector and that of dischargers to the fraction-removal levels are treated as fuzzy, and modelled with appropriate membership functions. Application of the model is illustrated with a case study of the Tungabhadra river in India.
Dynamic programming approach for newborn's incubator humidity control.
Bouattoura, D; Villon, P; Farges, G
1998-01-01
The anatomy, physiology, and biochemistry of the human skin have been studied for a long time. A special interest has been shown in the water permeability of the premature infant's skin, which is known to be an important factor in the maintenance of a controlled water and heat balance. The rate of evaporative heat exchange between the skin surface of a very premature infant and the surrounding incubator air may be so high that evaporative heat loss alone may exceed the infant's total metabolic heat production. However, it has been demonstrated in several investigations published in recent years that basal evaporative water loss can be consistently reduced by increasing the ambient humidity. Nevertheless, the passive humidification system (water reservoir) used in most incubators cannot achieve high and steady humidity levels. In this paper, we propose an active humidification system. The algorithm is based on a combination of optimal control theory and dynamic programming approach. The relative-humidity (R.H.) regulation is performed in range of 35-90% at 33 degrees C with small oscillations (+/- 0.5% R.H.) around the reference value (i.e., prescribed R.H.).
Dynamic programming approach for partial decision rule optimization
Amin, Talha
2012-10-04
This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.
Gao, Yangyang; Müller-Plathe, Florian
2016-02-25
By employing reverse nonequilibrium molecular dynamics simulations in a full atomistic resolution, the effect of surface-grafted chains on the thermal conductivity of graphene-polyamide-6.6 (PA) nanocomposites has been investigated. The interfacial thermal conductivity perpendicular to the graphene plane is proportional to the grafting density, while it first increases and then saturates with the grafting length. Meanwhile, the intrinsic in-plane thermal conductivity of graphene drops sharply as the grafting density increases. The maximum overall thermal conductivity of nanocomposites appears at an intermediate grafting density because of these two competing effects. The thermal conductivity of the composite parallel to the graphene plane increases with the grafting density and grafting length which is attributed to better interfacial coupling between graphene and PA. There exists an optimal balance between grafting density and grafting length to obtain the highest interfacial and parallel thermal conductivity. Two empirical formulas are suggested, which quantitatively account for the effects of grafting length and density on the interfacial and parallel thermal conductivity. Combined with effective medium approximation, for ungrafted graphene in random orientation, the model overestimates the thermal conductivity at low graphene volume fraction (f 10%). For unoriented grafted graphene, the model matches the experimental results well. In short, this work provides some valuable guides to obtain the nanocomposites with high thermal conductivity by grafting chain on the surface of graphene.
International Nuclear Information System (INIS)
This work is aimed at a predictive description of the thermodynamic properties of actinide (III) salt solutions at high concentration and 25 deg. C. A new solution of the binding mean spherical approximation (BIMSA) theory, based on the Wertheim formalism, for taking into account 1: 1 and also 1: 2 complex formation, is used to reproduce, from a simple procedure, experimental osmotic coefficient variation with concentration for three binary salt solutions of the same lanthanide (III) cation: dysprosium (III) perchlorate, nitrate, and chloride. The relevance of the fitted parameters is discussed, and their values are compared with available literature values. UV-vis/near-IR, time-resolved laser-induced fluorescence spectroscopy experiments, and molecular dynamics (MD) calculations were conducted for dilute to concentrated solutions (ca. 3 mol, kg-1) for a study of the microscopic behavior of DyCl3 binary solutions. Coupling MD calculations and extended X-ray absorption fine structure led to the determination of reliable distances. The MD results were used for a discussion of the parameters used in the BIMSA. (authors)
Gao, Yangyang; Müller-Plathe, Florian
2016-02-25
By employing reverse nonequilibrium molecular dynamics simulations in a full atomistic resolution, the effect of surface-grafted chains on the thermal conductivity of graphene-polyamide-6.6 (PA) nanocomposites has been investigated. The interfacial thermal conductivity perpendicular to the graphene plane is proportional to the grafting density, while it first increases and then saturates with the grafting length. Meanwhile, the intrinsic in-plane thermal conductivity of graphene drops sharply as the grafting density increases. The maximum overall thermal conductivity of nanocomposites appears at an intermediate grafting density because of these two competing effects. The thermal conductivity of the composite parallel to the graphene plane increases with the grafting density and grafting length which is attributed to better interfacial coupling between graphene and PA. There exists an optimal balance between grafting density and grafting length to obtain the highest interfacial and parallel thermal conductivity. Two empirical formulas are suggested, which quantitatively account for the effects of grafting length and density on the interfacial and parallel thermal conductivity. Combined with effective medium approximation, for ungrafted graphene in random orientation, the model overestimates the thermal conductivity at low graphene volume fraction (f 10%). For unoriented grafted graphene, the model matches the experimental results well. In short, this work provides some valuable guides to obtain the nanocomposites with high thermal conductivity by grafting chain on the surface of graphene. PMID:26800434
Garza, Alejandro J; Alencar, Ana G Sousa; Sun, Jianwei; Perdew, John P; Scuseria, Gustavo E
2015-01-01
Contrary to standard coupled cluster doubles (CCD) and Brueckner doubles (BD), singlet-paired analogues of CCD and BD (denoted here as CCD0 and BD0) do not break down when static correlation is present, but neglect substantial amounts of dynamic correlation. In fact, CCD0 and BD0 do not account for any contributions from multielectron excitations involving only same-spin electrons at all. We exploit this feature to add---without introducing double counting, self-interaction, or increase in cost---the missing correlation to these methods via meta-GGA density functionals (TPSS and SCAN). Furthermore, we improve upon these CCD0+DFT blends by invoking range separation: the short- and long-range correlations absent in CCD0/BD0 are evaluated with DFT and the direct random phase approximation (dRPA), respectively. This corrects the description of long-range van der Waals forces. Comprehensive benchmarking shows that the combinations presented here are very accurate for weakly correlated systems, while also providing...
Munneke, M.; Jong, Z. de; Zwinderman, A.H.; Jansen, A.; Ronday, H.K.; Peter, W.F.; Boonman, D.C.; Ende, C.H.M. van den; Vliet Vlieland, T.P.M.; Hazes, J.M.W.
2003-01-01
OBJECTIVE: To evaluate adherence and satisfaction of patients with rheumatoid arthritis (RA) in a long-term intensive dynamic exercise program. METHODS: A total of 146 RA patients started an intensive (strength and endurance training for 75 minutes, twice a week, for 2 years) exercise program (Rheum
Optimal Polygonal Approximation of Digital Planar Curves Using Genetic Algorithm and Tabu Search
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Three heuristic algorithms for optimal polygonal approximation of digital planar curves is presented.With Genetic Algorithm (GA), improved Genetic Algorithm (IGA) based on Pareto optimal solution and Tabu Search (TS), a near optimal polygonal approximation was obtained.Compared to the famous Teh-chin algorithm, our algorithms have obtained the approximated polygons with less number of vertices and less approximation error.Compared to the dynamic programming algorithm, the processing time of our algorithms are much less expensive.
EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon–Mann–Whitney Test
Directory of Open Access Journals (Sweden)
Alexander Marx
2016-02-01
Full Text Available In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney (WMW test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD. We found that approximated P values were generally higher than the exact solution provided by EDISON-WMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.
EDISON-WMW:Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test
Institute of Scientific and Technical Information of China (English)
Alexander Marx; Christina Backes; Eckart Meese; Hans-Peter Lenhof; Andreas Keller
2016-01-01
In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney (WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calcu-late the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we pre-sented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molec-ular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD). We found that approximated P values were generally higher than the exact solution provided by EDISONWMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http:// www.ccb.uni-saarland.de/software/wtest/.
Prestack wavefield approximations
Alkhalifah, Tariq
2013-09-01
The double-square-root (DSR) relation offers a platform to perform prestack imaging using an extended single wavefield that honors the geometrical configuration between sources, receivers, and the image point, or in other words, prestack wavefields. Extrapolating such wavefields, nevertheless, suffers from limitations. Chief among them is the singularity associated with horizontally propagating waves. I have devised highly accurate approximations free of such singularities which are highly accurate. Specifically, I use Padé expansions with denominators given by a power series that is an order lower than that of the numerator, and thus, introduce a free variable to balance the series order and normalize the singularity. For the higher-order Padé approximation, the errors are negligible. Additional simplifications, like recasting the DSR formula as a function of scattering angle, allow for a singularity free form that is useful for constant-angle-gather imaging. A dynamic form of this DSR formula can be supported by kinematic evaluations of the scattering angle to provide efficient prestack wavefield construction. Applying a similar approximation to the dip angle yields an efficient 1D wave equation with the scattering and dip angles extracted from, for example, DSR ray tracing. Application to the complex Marmousi data set demonstrates that these approximations, although they may provide less than optimal results, allow for efficient and flexible implementations. © 2013 Society of Exploration Geophysicists.
Brown, I. Foster
2008-06-01
Learning to question is essential for determining pathways of conservation and development in southwestern Amazonia during a time of rapid global environmental change. Teaching such an approach in graduate science programs in regional universities can be done using play-acting and simulation exercises. Multiple working hypotheses help students learn to question their own research results and expert witnesses. The method of successive approximations enables students to question the results of complex calculations, such as estimates of forest biomass. Balloons and rolls of toilet paper provide means of questioning two-dimensional representations of a three-dimensional Earth and the value of pi. Generation of systematic errors can illustrate the pitfalls of blind acceptance of data. While learning to question is essential, it is insufficient by itself; students must also learn how to be solutionologists in order to satisfy societal demands for solutions to environmental problems. A little irreverence can be an excellent didactic tool for helping students develop the skills necessary to lead conservation and development efforts in the region.
Energy Technology Data Exchange (ETDEWEB)
Tinianow, M.A.; Rotelli, R.L. Jr.; Baird, J.A.
1984-06-01
User instructions for the GEODYN Interactive Finite Element Computer Program are presented. The program is capable of performing the analysis of the three-dimensional transient dynamic response of a Polycrystalline Diamond Compact Bit - Bit Sub arising from the intermittent contact of the bit with the downhole rock formations. The program accommodates non-linear, time dependent, loading and boundary conditions.
Evolutionary programming for goal-driven dynamic planning
Vaccaro, James M.; Guest, Clark C.; Ross, David O.
2002-03-01
Many complex artificial intelligence (IA) problems are goal- driven in nature and the opportunity exists to realize the benefits of a goal-oriented solution. In many cases, such as in command and control, a goal-oriented approach may be the only option. One of many appropriate applications for such an approach is War Gaming. War Gaming is an important tool for command and control because it provides a set of alternative courses of actions so that military leaders can contemplate their next move in the battlefield. For instance, when making decisions that save lives, it is necessary to completely understand the consequences of a given order. A goal-oriented approach provides a slowly evolving tractably reasoned solution that inherently follows one of the principles of war: namely concentration on the objective. Future decision-making will depend not only on the battlefield, but also on a virtual world where military leaders can wage wars and determine their options by playing computer war games much like the real world. The problem with these games is that the built-in AI does not learn nor adapt and many times cheats, because the intelligent player has access to all the information, while the user has access to limited information provided on a display. These games are written for the purpose of entertainment and actions are calculated a priori and off-line, and are made prior or during their development. With these games getting more sophisticated in structure and less domain specific in scope, there needs to be a more general intelligent player that can adapt and learn in case the battlefield situations or the rules of engagement change. One such war game that might be considered is Risk. Risk incorporates the principles of war, is a top-down scalable model, and provides a good application for testing a variety of goal- oriented AI approaches. By integrating a goal-oriented hybrid approach, one can develop a program that plays the Risk game effectively and move
Testing Object-Oriented Programs using Dynamic Aspects and Non-Determinism
DEFF Research Database (Denmark)
Achenbach, Michael; Ostermann, Klaus
2010-01-01
decisions exposing private data. We present an approach that both improves the expressiveness of test cases using non-deterministic choice and reduces design modifications using dynamic aspect-oriented programming techniques. Non-deterministic choice facilitates local definitions of multiple executions...... without parameterization or generation of tests. It also eases modelling naturally non-deterministic program features like IO or multi-threading in integration tests. Dynamic AOP facilitates powerful design adaptations without exposing test features, keeping the scope of these adaptations local to each...... test. We also combine non-determinism and dynamic aspects in a new approach to testing multi-threaded programs using co-routines....
Directory of Open Access Journals (Sweden)
Ximing Wang
2015-04-01
Full Text Available To explore the problems associated with applying dynamic programming (DP in the energy management strategies of plug-in hybrid electric vehicles (PHEVs, a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.
Developing molecular dynamics simulation codes using mixed language programming
Energy Technology Data Exchange (ETDEWEB)
DeBoni, T.; Feo, J.T. [Lawrence Livermore National Lab., CA (United States); Caffey, H.; Hausheer, F. [BioNumerik Pharmaceuticals, Inc., San Antonio, TX (United States)
1994-05-01
We describe our experiences parallelizing a large-scale scientific application to model systems of discrete particles. We describe the approach and tasks undertaken to parallelize this application using two different programming paradigms: imperative and functional. The objectives of both exercises were to maximize performance, parallelism and portability, and to minimize program development costs. We believe this study reveals an important relationship between conventional and novel parallel programming paradigms, and identifies important attributes that novel paradigms must have to gain wide acceptance.
An effective algorithm for approximating adaptive behavior in seasonal environments
DEFF Research Database (Denmark)
Sainmont, Julie; Andersen, Ken Haste; Thygesen, Uffe Høgsbro;
2015-01-01
behavior; the so-called "myopic approximation", "short sighted", or "static optimization". We explore the performance of the myopic approximation with diel vertical migration (DVM) as an example of a daily routine, a behavior with seasonal dependence that trades off predation risk with foraging......-annual variations, aspects that can only be accessed in dynamic programming approaches with escalating computational costs. Furthermore, the explanatory power of the myopic approximation is notably higher than when behavior is not implemented, highlighting the importance for adaptive DVM behavior in ecological...
Program participation, labor force dynamics, and accepted wage rates
DEFF Research Database (Denmark)
Munch, Jakob Roland; Skipper, Lars
2008-01-01
We apply a recently suggested econometric approach to measure the effects of active labor market programs on employment, unemployment, and wage histories among participants. We find that participation in most of these training programs produces an initial locking-in effect and for some even a lower...... subpopulations. These longer spells of employment come at a cost of lower accepted hourly wage rates...
Fixed point theorems for compatible mappings of type (P and applications to dynamic programming
Directory of Open Access Journals (Sweden)
H. K. Pathak
1995-11-01
Full Text Available In this paper, we prove some common fixed point theorems for compatible mappings of type (P. As applications, the existence and uniqueness of common solutions for a class of the functional equations in dynamic programming are discussed.
Institute of Scientific and Technical Information of China (English)
闫春雷
2011-01-01
建立了不变凸多目标规划问题的η-逼近多目标规划问题与η-逼近Mond-Weir对偶问题,并通过其对偶性给出了原多目标规划问题与其Mond-Weir对偶问题的对偶性.%An 17-approximated multiobjective program associated with the original multiobjective problem involving invex functions and its 17-approximated Mond-Weir dual problem are constructed; By the help of ^-approximated dual problems various duality results are established for the original multiobjective problem and its original Mond-Weir duals .
Institute of Scientific and Technical Information of China (English)
陈志平
2003-01-01
A new deterministic formulation,called the conditional expectation formulation,is proposed for dynamic stochastic programming problems in order to overcome some disadvantages of existing deterministic formulations.We then check the impact of the new deterministic formulation and other two deterministic formulations on the corresponding problem size,nonzero elements and solution time by solving some typical dynamic stochastic programming problems with different interior point algorithms.Numerical results show the advantage and application of the new deterministic formulation.
Wang, Xinpu; Yang, Jun; Zhang, Xiaodong; Yu, Xiaopeng
To enhance the stability of power system, the active power and reactive power can be absorbed from or released to Superconducting magnetic energy storage (SMES) unit according to system power requirements. This paper proposes a control strategy based on action dependent heuristic dynamic programing (ADHDP) which can control SMES to improve the stability of electric power system with on-line learning ability. Based on back propagation (BP) neural network, ADHDP approximates the optimal control solution of nonlinear system through iteration step by step. This on-line learning ability improves its performance by learning from its own mistakes through reinforcement signal from external environment, so that it can adjust the neural network weights according to the back propagation error to achieve optimal control performance. To investigate the effectiveness of the proposed control strategy, simulation tests are carried out in Matlab/Simulink. And a conventional Proportional-Integral (PI) controlled method is used to compare the performance of ADHDP. Simulation results show that the proposed controller demonstrates superior damping performance on power system oscillation caused by three-phase fault and wind power fluctuation over the PI controller.
Effect of the CTL proliferation program on virus dynamics
DEFF Research Database (Denmark)
Wodarz, Dominik; Thomsen, Allan Randrup
2005-01-01
to occur independent from antigenic stimulation when virus load drops to low levels. This results in stronger effector activity at low virus loads, and in a higher chance of virus extinction. On the other hand, the more programmed divisions occur, the less efficient the response is at preventing high acute...... virus loads and thus acute symptoms. The reason is that the programmed divisions are independent from antigenic stimulation, and an increase in virus load does not speed up the rate of CTL expansion. We hypothesize that the 7-10 programmed divisions observed in vivo represent an optimal solution...
Panageas, Ioannis; Piliouras, Georgios
2014-01-01
What does it mean to fully understand the behavior of a network of competing agents? The golden standard typically is the behavior of learning dynamics in potential games, where many evolutionary dynamics, e.g., replicator, are known to converge to sets of equilibria. Even in such classic settings many critical questions remain unanswered. Inspired by topological and geometric considerations, we devise novel yardsticks and techniques that allow for much more detailed analysis of game dynamics...
Energy Technology Data Exchange (ETDEWEB)
Lewis, M.W.; Kashiwa, B.A.; Meier, R.W. [Los Alamos National Lab., NM (United States); Bishop, S. [US Army Night Vision and Electronic Sensors Directorate, Fort Belvoir, VA (United States)
1994-08-01
Two- and three-dimensional fluid-structure interaction computer programs for the simulation of nonlinear dynamics were developed and applied to a number of problems. The programs were created by coupling Arbitrary Lagrangian-Eulerian finite volume fluid dynamics programs with strictly Lagrangian finite element structural dynamics programs. The resulting coupled programs can use either fully explicit or implicit time integration. The implicit time integration is accomplished by iterations of the fluid dynamics pressure solver and the structural dynamics system solver. The coupled programs have been used to solve problems involving incompressible fluids, membrane and shell elements, compressible multiphase flows, explosions in both air and water, and large displacements. In this paper, we present the approach used for the coupling and describe test problems that verify the two-dimensional programs against an experiment and an analytical linear problem. The experiment involves an explosion underwater near an instrumented thin steel plate. The analytical linear problem is the vibration of an infinite cylinder surrounded by an incompressible fluid to a given radius.
Drobnes, Emilie; Littleton, A.; Pesnell, William D.; Beck, K.; Buhr, S.; Durscher, R.; Hill, S.; McCaffrey, M.; McKenzie, D. E.; Myers, D.; Scherrer, D.; Wawro, M.; Wolt, A.
2013-01-01
We outline the context and overall philosophy for the combined Solar Dynamics Observatory (SDO) Education and Public Outreach (E/PO) program, present a brief overview of all SDO E/PO programs along with more detailed highlights of a few key programs, followed by a review of our results to date, conclude a summary of the successes, failures, and lessons learned, which future missions can use as a guide, while incorporating their own content to enhance the public's knowledge and appreciation of science and technology as well as its benefit to society.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1991-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All the calculati...
DISCRETE DYNAMIC MODEL OF BEVEL GEAR – VERIFICATION THE PROGRAM SOURCE CODE FOR NUMERICAL SIMULATION
Directory of Open Access Journals (Sweden)
Krzysztof TWARDOCH
2014-06-01
Full Text Available In the article presented a new model of physical and mathematical bevel gear to study the influence of design parameters and operating factors on the dynamic state of the gear transmission. Discusses the process of verifying proper operation of copyright calculation program used to determine the solutions of the dynamic model of bevel gear. Presents the block diagram of a computing algorithm that was used to create a program for the numerical simulation. The program source code is written in an interactive environment to perform scientific and engineering calculations, MATLAB
Snow, L. S.; Kuhn, A. E.
1975-01-01
Previous error analyses conducted by the Guidance and Dynamics Branch of NASA have used the Guidance Analysis Program (GAP) as the trajectory simulation tool. Plans are made to conduct all future error analyses using the Space Vehicle Dynamics Simulation (SVDS) program. A study was conducted to compare the inertial measurement unit (IMU) error simulations of the two programs. Results of the GAP/SVDS comparison are presented and problem areas encountered while attempting to simulate IMU errors, vehicle performance uncertainties and environmental uncertainties using SVDS are defined. An evaluation of the SVDS linear error analysis capability is also included.
Transient dynamic and inelastic analysis of shells of revolution - a survey of programs
International Nuclear Information System (INIS)
Advances in the limits of structural use in the aerospace and nuclear power industries over the past years have increased the requirements upon the applicable analytical computer programs to include accurate capabilities for inelastic and transient dynamic analyses. In many minds, however, this advanced capability is unequivocally linked with the large scale, general purpose, finite element programs. This idea is also combined with the view that such analyses are therefore prohibitively expensive and should be relegated to the 'last resort' classification. While this, in the general sense, may indeed be the case, if the user needs only to analyze structures falling into limited categories, however, he may find that a variety of smaller special purpose programs are available which do not put an undue strain upon his resources. One such structural category is shells of revolution. This survey of programs concentrates upon the analytical tools which have been developed predominantly for shells of revolution. The survey is subdivided into three parts: (a) consideration of programs for transient dynamic analysis; (b) consideration of programs for inelastic analysis and finally; (c) consideration of programs capable of dynamic plasticity analysis. In each part, programs based upon finite difference, finite element, and numerical integration methods are considered. The programs are compared on the basis of analytical capabilities, and ease of idealization and use. In each part of the survey sample problems are utilized to exemplify the state-of-the-art. (Auth.)
Steering plasmodium with light: Dynamical programming of Physarum machine
Adamatzky, Andrew
2009-01-01
A plasmodium of Physarum polycephalum is a very large cell visible by unaided eye. The plasmodium is capable for distributed sensing, parallel information processing, and decentralized optimization. It is an ideal substrate for future and emerging bio-computing devices. We study space-time dynamics of plasmodium reactiom to localised illumination, and provide analogies between propagating plasmodium and travelling wave-fragments in excitable media. We show how plasmodium-based computing devic...
凹资源配置问题的混合动态规划方法%A Hybrid Dynamic Programming Method for Concave Resource Allocation Problems
Institute of Scientific and Technical Information of China (English)
姜计荣; 孙小玲
2005-01-01
Concave resource allocation problem is an integer programming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems are encountered in optimization models involving economies of scale. In this paper, a new hybrid dynamic programming method was proposed for solving concave resource allocation problems. A convex underestimating function was used to approximate the objective function and the resulting convex subproblem was solved with dynamic programming technique after transforming it into a 0-1 linear knapsack problem. To ensure the convergence, monotonicity and domain cut technique was employed to remove certain integer boxes and partition the Reviseddomain into a union of integer boxes. Computational results were given to show the efficiency of the algorithm.
Grammatikopoulos, Vasilis
2012-01-01
The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic elements of…
A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
Directory of Open Access Journals (Sweden)
Jooyong Yi
2013-09-01
Full Text Available Backtracking (i.e., reverse execution helps the user of a debugger to naturally think backwards along the execution path of a program, and thinking backwards makes it easy to locate the origin of a bug. So far backtracking has been implemented mostly by state saving or by checkpointing. These implementations, however, inherently do not scale. Meanwhile, a more recent backtracking method based on reverse-code generation seems promising because executing reverse code can restore the previous states of a program without state saving. In the literature, there can be found two methods that generate reverse code: (a static reverse-code generation that pre-generates reverse code through static analysis before starting a debugging session, and (b dynamic reverse-code generation that generates reverse code by applying dynamic analysis on the fly during a debugging session. In particular, we espoused the latter one in our previous work to accommodate non-determinism of a program caused by e.g., multi-threading. To demonstrate the usefulness of our dynamic reverse-code generation, this article presents a case study of various backtracking methods including ours. We compare the memory usage of various backtracking methods in a simple but nontrivial example, a bounded-buffer program. In the case of non-deterministic programs such as this bounded-buffer program, our dynamic reverse-code generation outperforms the existing backtracking methods in terms of memory efficiency.
Neuro-Dynamic Programming for Radiation Treatment Planning
Ferris, Michael C.; Voelker, Meta M.
2002-01-01
In many cases a radiotherapy treatment is delivered as a series of smaller dosages over a period of time. Currently, it is difficult to determine the actual dose that has been delivered at each stage, precluding the use of adaptive treatment plans. However, new generations of machines will give more accurate information of actual dose delivered, allowing a planner to compensate for errors in delivery. We formulate a model of the day-to-day planning problem as a stochastic linear program and e...
Klippenstein, Stephen J.; Babamov, Vasil K.; Marcus, R. A.
1986-01-01
Reactive transition probabilities and Boltzmann-averaged reactive transition probabilities for a slightly off-resonant model H-atom transfer system with an appreciable energy barrier are calculated using the approximate methods of Babamov et al. and of Crothers–Stückelberg. Both are compared with the corresponding quantities obtained from a numerical two-state treatment of the same model system. The method of Babamov et al. is seen to give more accurate results for the transition probabilitie...
Watermarking Java Programs using Dummy Methods with Dynamically Opaque Predicates
Akbar, Zaenal
2010-01-01
Software piracy, the illegal using, copying, and resale of applications is a major concern for anyone develops software. Software developers also worry about their applications being reverse engineered by extracting data structures and algorithms from an application and incorporated into competitor's code. A defense against software piracy is watermarking, a process that embeds a secret message in a cover software. Watermarking is a method that does not aim to stop piracy copying, but to prove ownership of the software and possibly even the data structures and algorithms used in the software. The language Java was designed to be compiled into a platform independent bytecode format. Much of the information contained in the source code remains in the bytecode, which means that decompilation is easier than with traditional native codes. In this thesis, we present a technique for watermarking Java programs by using a never-executed dummy method (Monden et.al., 2000) combined with opaque predicates (Collberg et.al...
Discrete neural dynamic programming in wheeled mobile robot control
Hendzel, Zenon; Szuster, Marcin
2011-05-01
In this paper we propose a discrete algorithm for a tracking control of a two-wheeled mobile robot (WMR), using an advanced Adaptive Critic Design (ACD). We used Dual-Heuristic Programming (DHP) algorithm, that consists of two parametric structures implemented as Neural Networks (NNs): an actor and a critic, both realized in a form of Random Vector Functional Link (RVFL) NNs. In the proposed algorithm the control system consists of the DHP adaptive critic, a PD controller and a supervisory term, derived from the Lyapunov stability theorem. The supervisory term guaranties a stable realization of a tracking movement in a learning phase of the adaptive critic structure and robustness in face of disturbances. The discrete tracking control algorithm works online, uses the WMR model for a state prediction and does not require a preliminary learning. Verification has been conducted to illustrate the performance of the proposed control algorithm, by a series of experiments on the WMR Pioneer 2-DX.
Repetitive elements dynamics in cell identity programming, maintenance and disease
Bodega, Beatrice
2014-12-01
The days of \\'junk DNA\\' seem to be over. The rapid progress of genomics technologies has been unveiling unexpected mechanisms by which repetitive DNA and in particular transposable elements (TEs) have evolved, becoming key issues in understanding genome structure and function. Indeed, rather than \\'parasites\\', recent findings strongly suggest that TEs may have a positive function by contributing to tissue specific transcriptional programs, in particular as enhancer-like elements and/or modules for regulation of higher order chromatin structure. Further, it appears that during development and aging genomes experience several waves of TEs activation, and this contributes to individual genome shaping during lifetime. Interestingly, TEs activity is major target of epigenomic regulation. These findings are shedding new light on the genome-phenotype relationship and set the premises to help to explain complex disease manifestation, as consequence of TEs activity deregulation.
Leike, Reimar H
2016-01-01
In Bayesian statistics probability distributions express beliefs. However, for many problems the beliefs cannot be computed analytically and approximations of beliefs are needed. We seek a ranking function that quantifies how "embarrassing" it is to communicate a given approximation. We show that there is only one ranking under the requirements that (1) the best ranked approximation is the non-approximated belief and (2) that the ranking judges approximations only by their predictions for actual outcomes. We find that this ranking is equivalent to the Kullback-Leibler divergence that is frequently used in the literature. However, there seems to be confusion about the correct order in which its functional arguments, the approximated and non-approximated beliefs, should be used. We hope that our elementary derivation settles the apparent confusion. We show for example that when approximating beliefs with Gaussian distributions the optimal approximation is given by moment matching. This is in contrast to many su...
Bakaleinikov, L. A.; Silbergleit, A. S.
The closeness of the approximate ( PL) and the exact ( P) Poincaré mappings for ODE systems with a hyperbolic critical point possessing a homoclinic orbit, is studied. The mappings are shown to be not uniformly close in their whole domain. The existence of the uniform estimate in a general case is provided by the restriction of mappings P, PL to some subset. The images of mappings PL and P occur to be uniformly close in the whole domain only for particular cases of 2-dimensional systems, systems with a single unstable direction at the equilibrium point and systems with two unstable directions corresponding to a complex conjugate pair of eigenvalues.
Interatomic forces in the electron-gas approximation
International Nuclear Information System (INIS)
This report describes the approximations involved in calculating the separate kinetic, coulomb, exchange and correlation contributions to the non-bonded interaction energy between closed-shell atoms. The basis of the method is an electron-gas model. The resulting potentials may be used in solid-state physics calculations or molecular dynamics simulations. Instructions are included for running three computer programs, HERSKILL, EXPAND and WEDEPOHL, which use the method described. (author)
Li, Yongping; Huang, Guohe
2009-03-01
In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability. PMID:19320267
Energy Technology Data Exchange (ETDEWEB)
Brown, M.A.; White, D.L.
1992-12-01
This study continues the series of evaluations of the Bonneville Power Administration's long-term Residential Weatherization Program (RWP) by examining the energy saved by its 1988 and 1989 participants. The sample of participants for this study was drawn from 10 utilities covering the region's three climate zones. Six of these utilities were included in the 1988 RWP evaluation, and eight of them were included in the 1989 RWP evaluation. This study analyzes data on 356 participating households in 1988, 433 participants in 1989, and a comparison group of 1170 nonparticipants in 1988 and 1466 in 1989. Previous evaluations of Bonneville's earlier weatherization programs provide an historic context for analyzing program dynamics.
Energy Technology Data Exchange (ETDEWEB)
Brown, M.A.; White, D.L.
1992-12-01
This study continues the series of evaluations of the Bonneville Power Administration`s long-term Residential Weatherization Program (RWP) by examining the energy saved by its 1988 and 1989 participants. The sample of participants for this study was drawn from 10 utilities covering the region`s three climate zones. Six of these utilities were included in the 1988 RWP evaluation, and eight of them were included in the 1989 RWP evaluation. This study analyzes data on 356 participating households in 1988, 433 participants in 1989, and a comparison group of 1170 nonparticipants in 1988 and 1466 in 1989. Previous evaluations of Bonneville`s earlier weatherization programs provide an historic context for analyzing program dynamics.
Goreac, Dan; Serea, Oana Silvia
2012-01-01
Using the linear programming approach to stochastic control introduced by Buckdahn, Goreac, and Quincampoix, and by Goreac and Serea, we provide a semigroup property for some set of probability measures leading to dynamic programming principles for stochastic control problems. An abstract principle is provided for general bounded costs. Linearized versions are obtained under further (semi)continuity assumptions.
Karachanskaya, Elena
2012-01-01
Investigate the stochastic dynamic non-linear system with the Wiener and the Poisson perturbations. For such systems we construct the program control with probability one, which allows this system to move on the given trajectory. In this case the control program is solution of the algebraic system of linear equations. Considered algorithm is based on the first integral theory for stochastic differential equations system.
Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R
2013-01-01
This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.
A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon
Energy Technology Data Exchange (ETDEWEB)
D`Azevedo, E.F.; Romine, C.H.
1994-12-01
This report describes the use of shared memory emulation with DOLIB (Distributed Object Library) to simplify parallel programming on the Intel Paragon. A molecular dynamics application is used as an example to illustrate the use of the DOLIB shared memory library. SOTON-PAR, a parallel molecular dynamics code with explicit message-passing using a Lennard-Jones 6-12 potential, is rewritten using DOLIB primitives. The resulting code has no explicit message primitives and resembles a serial code. The new code can perform dynamic load balancing and achieves better performance than the original parallel code with explicit message-passing.
Brown, I. Foster
2008-01-01
Learning to question is essential for determining pathways of conservation and development in southwestern Amazonia during a time of rapid global environmental change. Teaching such an approach in graduate science programs in regional universities can be done using play-acting and simulation exercises. Multiple working hypotheses help students…
Bin Qin
2014-01-01
Relationships between fuzzy relations and fuzzy topologies are deeply researched. The concept of fuzzy approximating spaces is introduced and decision conditions that a fuzzy topological space is a fuzzy approximating space are obtained.
Rasin, A
1994-01-01
We discuss the idea of approximate flavor symmetries. Relations between approximate flavor symmetries and natural flavor conservation and democracy models is explored. Implications for neutrino physics are also discussed.
Approximate iterative algorithms
Almudevar, Anthony Louis
2014-01-01
Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and convergence rates, and for the optimal design of such algorithms. Techniques of functional analysis are used to derive analytical relationships between approximation methods and convergence properties for general classes of algorithms. This work provides the necessary background in functional analysis a
Energy Technology Data Exchange (ETDEWEB)
Sayyar-Rodsari, Bijan; Schweiger, Carl; Hartman, Eric
2007-10-07
The difficult problems being tackled in the accelerator community are those that are nonlinear, substantially unmodeled, and vary over time. Such problems are ideal candidates for model-based optimization and control if representative models of the problem can be developed that capture the necessary mathematical relations and remain valid throughout the operation region of the system, and through variations in system dynamics. The goal of this proposal is to develop the methodology and the algorithms for building high-fidelity mathematical representations of complex nonlinear systems via constrained training of combined first-principles and neural network models.
Indian Academy of Sciences (India)
N Bhargava Ram; Vaibhav S Prabhudesai; E Krishnakumar
2012-01-01
The dynamics of the formation and decay of negative ion resonance of A1 symmetry at 8.5 eV electron energy in the dissociative electron attachment (DEA) process in H2O and D2O are investigated using the velocity slice imaging technique. While the highest energy hydride ions formed by DEA show angular distributions characteristic to the A1 symmetry, those formed with low-kinetic energy show considerably different angular distributions indicating changes in the orientation of the dissociating bond due to bending mode vibrations. Our observations are quite different from the recently reported measurements, but consistent with the fully quantum calculations.
Static and Dynamic Coupling and Cohesion Measures in Object Oriented Programming
Directory of Open Access Journals (Sweden)
Vasudha Dixit, Dr. Rajeev Vishwkarma
2013-10-01
Full Text Available A large numbers of metrics have been proposed for measuring properties of object-oriented software such as size, inheritance, cohesion and coupling. The coupling metrics presented in this paper exploring the difference between inheritance and interface programming. This paper presents a measurement to measure coupling between object (CBO, number of associations between classes (NASSocC, number of dependencies in metric (NDepIN and number of dependenciesout metric (NDepOut in object oriented programming for both static and dynamic analysis. Java programs is used for implementation.In this paper we want to show which concept is good to use and beneficial for software developer.
Dynamic capacity adjustment for virtual-path based networks using neuro-dynamic programming
Şahin, Cem
2003-01-01
Cataloged from PDF version of article. Dynamic capacity adjustment is the process of updating the capacity reservation of a virtual path via signalling in the network. There are two important issues to be considered: bandwidth (resource) utilization and signaling traffic. Changing the capacity too frequently will lead to efficient usage of resources but has a disadvantage of increasing signaling traffic among the network elements. On the other hand, if the capacity is adjust...
Approximation of distributed delays
Lu, Hao; Eberard, Damien; Simon, Jean-Pierre
2010-01-01
We address in this paper the approximation problem of distributed delays. Such elements are convolution operators with kernel having bounded support, and appear in the control of time-delay systems. From the rich literature on this topic, we propose a general methodology to achieve such an approximation. For this, we enclose the approximation problem in the graph topology, and work with the norm defined over the convolution Banach algebra. The class of rational approximates is described, and a constructive approximation is proposed. Analysis in time and frequency domains is provided. This methodology is illustrated on the stabilization control problem, for which simulations results show the effectiveness of the proposed methodology.
Encoding four gene expression programs in the activation dynamics of a single transcription factor.
Hansen, Anders S; O'Shea, Erin K
2016-04-01
Cellular signaling response pathways often exhibit a bow-tie topology [1,2]: multiple upstream stress signals converge on a single shared transcription factor, which is thought to induce different downstream gene expression programs (Figure 1A). However, if several different signals activate the same transcription factor, can each signal then induce a specific gene expression response? A growing body of literature supports a temporal coding theory where information about environmental signals can be encoded, at least partially, in the temporal dynamics of the shared transcription factor [1,2]. For example, in the case of the budding yeast transcription factor Msn2, different stresses induce distinct Msn2 activation dynamics: Msn2 shows pulsatile nuclear activation with dose-dependent frequency under glucose limitation, but sustained nuclear activation with dose-dependent amplitude under oxidative stress [3]. These dynamic patterns can then lead to differential gene expression responses [3-5], but it is not known how much specificity can be obtained. Thus, a major question of this temporal coding theory is how many gene response programs or cellular functions can be robustly encoded by dynamic control of a single transcription factor. Here we provide the first direct evidence that, simply by regulating the activation dynamics of a single transcription factor, it is possible to preferentially induce four distinct gene expression programs. PMID:27046808
Welte, R; Kretzschmar, M; Leidl, R; Van den Hoek, A; Jager, JC; Postma, MJ
2000-01-01
Background: Models commonly used for the economic assessment of chamydial screening programs do not consider population effects. Goal: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general practitioner-b
Institute of Scientific and Technical Information of China (English)
Ze-qing Liu; Shin Min Kang
2007-01-01
In this paper we establish the existence,uniqueness and iterative approxinlation of solutions for two classes of functional equations arising in dynamic programming of multistage decision Processes.The resultspresented here extend,and unify the corresponding results due to Bellman,Bhakta and Choudhury,Bhakta and Mitra,Liu and others.
Directory of Open Access Journals (Sweden)
Jingtao Shi
2013-01-01
Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
Jingtao Shi; Zhiyong Yu
2013-01-01
This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
Dynamic Programming Principle for Stochastic Control Problems driven by General L\\'{e}vy Noise
Goldys, Ben; Wu, Wei
2016-01-01
We extend the proof of the dynamic programming principle (DPP) for standard stochastic optimal control problems driven by general L\\'{e}vy noises. Under appropriate assumptions, it is shown that the DPP still holds when the state process fails to have any moments at all.
Bayraktar, Erhan; Yao, Song
2012-01-01
We analyze a zero-sum stochastic differential game between two competing players who can choose unbounded controls. The payoffs of the game are defined through backward stochastic differential equations. We prove that each player's priority value satisfies a weak dynamic programming principle and thus solves the associated fully non-linear partial differential equation in the viscosity sense.
DEFF Research Database (Denmark)
Davidsen, Claus; Cardenal, Silvio Javier Pereira; Liu, Suxia;
2015-01-01
of stochastic dynamic programming, to optimize water resources management in the Ziya River basin. Natural runoff from the upper basin was estimated with a rainfall-runoff model autocalibrated using in situ measured discharge. The runoff serial correlation was described by a Markov chain and used as input...
Modeling Dynamic Programming Problems over Sequences and Trees with Inverse Coupled Rewrite Systems
Directory of Open Access Journals (Sweden)
Robert Giegerich
2014-03-01
Full Text Available Dynamic programming is a classical algorithmic paradigm, which often allows the evaluation of a search space of exponential size in polynomial time. Recursive problem decomposition, tabulation of intermediate results for re-use, and Bellman’s Principle of Optimality are its well-understood ingredients. However, algorithms often lack abstraction and are difficult to implement, tedious to debug, and delicate to modify. The present article proposes a generic framework for specifying dynamic programming problems. This framework can handle all kinds of sequential inputs, as well as tree-structured data. Biosequence analysis, document processing, molecular structure analysis, comparison of objects assembled in a hierarchic fashion, and generally, all domains come under consideration where strings and ordered, rooted trees serve as natural data representations. The new approach introduces inverse coupled rewrite systems. They describe the solutions of combinatorial optimization problems as the inverse image of a term rewrite relation that reduces problem solutions to problem inputs. This specification leads to concise yet translucent specifications of dynamic programming algorithms. Their actual implementation may be challenging, but eventually, as we hope, it can be produced automatically. The present article demonstrates the scope of this new approach by describing a diverse set of dynamic programming problems which arise in the domain of computational biology, with examples in biosequence and molecular structure analysis.
Sparse approximation with bases
2015-01-01
This book systematically presents recent fundamental results on greedy approximation with respect to bases. Motivated by numerous applications, the last decade has seen great successes in studying nonlinear sparse approximation. Recent findings have established that greedy-type algorithms are suitable methods of nonlinear approximation in both sparse approximation with respect to bases and sparse approximation with respect to redundant systems. These insights, combined with some previous fundamental results, form the basis for constructing the theory of greedy approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical framework for greedy approximation and its applications. The book addresses the needs of researchers working in numerical mathematics, harmonic analysis, and functional analysis. It quickly takes the reader from classical results to the latest frontier, but is written at the level of a graduate course and do...
Schoen, Martin
1989-01-01
A program structure for efficient vectorization of molecular dynamics FORTRAN programs on CRAY vector processing computers is described. Though coded for a very simple pure atomic fluid in a cubic cell with periodic boundary conditions the program can easily be modified to handle more complicated systems. A detailed analysis shows that the present program is faster by 36% for N = 256 particles and faster by more than a factor of 3 for N = 2048 compared with a fully vectorized molecular dynamics program written for the CYBER 205 vector processing machine. In comparison with a link cell MD program also written for a CRAY the program described here runs three times faster for a large particle number N = 6912. This factor increases with decreasing N to 6.3 for N = 1372. The speedup is achieved by i) long vectors in inner loops wherever possible; ii) limiting the number of arithmetic operations in inevitably short loops as much as possible; iii) appropriate library routines; iv) integer index vector neighbour lists.
Nie, Xianghui; Huang, Guo H; Li, Yongping
2009-11-01
This study integrates the concepts of interval numbers and fuzzy sets into optimization analysis by dynamic programming as a means of accounting for system uncertainty. The developed interval fuzzy robust dynamic programming (IFRDP) model improves upon previous interval dynamic programming methods. It allows highly uncertain information to be effectively communicated into the optimization process through introducing the concept of fuzzy boundary interval and providing an interval-parameter fuzzy robust programming method for an embedded linear programming problem. Consequently, robustness of the optimization process and solution can be enhanced. The modeling approach is applied to a hypothetical problem for the planning of waste-flow allocation and treatment/disposal facility expansion within a municipal solid waste (MSW) management system. Interval solutions for capacity expansion of waste management facilities and relevant waste-flow allocation are generated and interpreted to provide useful decision alternatives. The results indicate that robust and useful solutions can be obtained, and the proposed IFRDP approach is applicable to practical problems that are associated with highly complex and uncertain information. PMID:19947113
Zhang, Shen; Wang, Hongwei; Kang, Wei; Zhang, Ping; He, X. T.
2016-04-01
An extended first-principles molecular dynamics (FPMD) method based on Kohn-Sham scheme is proposed to elevate the temperature limit of the FPMD method in the calculation of dense plasmas. The extended method treats the wave functions of high energy electrons as plane waves analytically and thus expands the application of the FPMD method to the region of hot dense plasmas without suffering from the formidable computational costs. In addition, the extended method inherits the high accuracy of the Kohn-Sham scheme and keeps the information of electronic structures. This gives an edge to the extended method in the calculation of mixtures of plasmas composed of heterogeneous ions, high-Z dense plasmas, lowering of ionization potentials, X-ray absorption/emission spectra, and opacities, which are of particular interest to astrophysics, inertial confinement fusion engineering, and laboratory astrophysics.
Energy Technology Data Exchange (ETDEWEB)
None
1977-05-01
The mathematical models and computer program comprising the SPP Dynamic Simulation are described. The SPP Dynamic Simulation is a computerized model representing the time-varying performance characteristics of the SPP. The model incorporates all the principal components of the pilot plant. Time-dependent direct normal solar insulation, as corrupted by simulated cloud passages, is transformed into absorbed radiant power by actions of the heliostat field and enclosed receiver cavity. The absorbed power then drives the steam generator model to produce superheated steam for the turbine and/or thermal storage subsystems. The thermal storage subsystem can, in turn, also produce steam for the turbine. The turbine using the steam flow energy produces the mechanical shaft power necessary for the generator to convert it to electrical power. This electrical power is subsequently transmitted to a transmission grid system. Exhaust steam from the turbine is condensed, reheated, deaerated, and pressurized by pumps for return as feedwater to the thermal storage and/or steam generator. A master control/instrumentation system is utilized to coordinate the various plant operations. The master controller reacts to plant operator demands and control settings to effect the desired output response. The SPP Dynamic Simulation Computer program is written in FORTRAN language. Various input options (e.g., insolation values, load demands, initial pressures/temperatures/flows) are permitted. Plant performance may be monitored via computer printout or computer generated plots. The remainder of this document describes the detailed pilot plant dynamic model, the basis for this simulation, and the utilization of this simulation to obtain analytical plant performance results.
Harper, William B.; Shaltens, Richard K.
1993-01-01
Closed Brayton cycle power conversion systems are readily adaptable to any heat source contemplated for space application. The inert gas working fluid can be used directly in gas-cooled reactors and coupled to a variety of heat sources (reactor, isotope or solar) by a heat exchanger. This point is demonstrated by the incorporation in the NASA 2 kWe Solar Dynamic (SD) Space Power Ground Test Demonstration (GTD) Program of the turboalternator-compressor and recuperator from the Brayton Isotope Power System (BIPS) program. This paper will review the goals and status of the SD GTD Program, initiated in April 1992. The performance of the BIPS isotope-heated system will be compared to the solar-heated GTD system incorporating the BIPS components and the applicability of the GTD test bed to dynamics space nuclear power R&D will be discussed.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Christensen, Tue; Andersen, Kim Allan; Klose, Andreas
2013-01-01
This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....
Sutrisno; Widowati; Solikhin
2016-06-01
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.
Institute of Scientific and Technical Information of China (English)
YueShihong; ZhangKecun
2002-01-01
In a dot product space with the reproducing kernel (r. k. S. ) ,a fuzzy system with the estimation approximation errors is proposed ,which overcomes the defect that the existing fuzzy control system is difficult to estimate the errors of approximation for a desired function,and keeps the characteristics of fuzzy system as an inference approach. The structure of the new fuzzy approximator benefits a course got by other means.
Approximation techniques for engineers
Komzsik, Louis
2006-01-01
Presenting numerous examples, algorithms, and industrial applications, Approximation Techniques for Engineers is your complete guide to the major techniques used in modern engineering practice. Whether you need approximations for discrete data of continuous functions, or you''re looking for approximate solutions to engineering problems, everything you need is nestled between the covers of this book. Now you can benefit from Louis Komzsik''s years of industrial experience to gain a working knowledge of a vast array of approximation techniques through this complete and self-contained resource.
Raso, Luciano; Dorchies, David; Malaterre, Pierre-Olivier
2015-04-01
We developed an Objective Oriented Programming (OOP) tool for optimal management of complex water systems by use of Stochastic Dual Dynamic Programming (SDDP). OOP is a powerful programming paradigm. OOP minimizes code redundancies, making code modification and maintenance very effective. This is especially welcome in research, in which, often, code must be modified to meet new requirements that were not initially considered. SDDP is an advanced method for optimal operation of complex dynamic systems under uncertainty. SDDP can deal with large and complex systems, such as a multi-reservoir system. The objective of this tool is making SDDP usable for Water Management Analysts. Thanks to this tool, the Analyst can bypass the SDDP programming complexity, and his/her task is simplified to the definition of system elements, topology and objectives, and experiments characteristics. In this tool, the main classes are: Experiment, System, Element, and Objective. Experiments are run on a system. A system is made of many elements interconnected among them. Class Element is made of the following sub-classes: (stochastic) hydrological scenario, (deterministic) water demand scenario, reservoir, river reach, off-take, and irrigation basin. Objectives are used in the optimization procedure to find the optimal operational rules, for a given system and experiment. OOP flexibility allows the Water Management Analyst to extend easily existing classes in order to answer his/her specific research questions. The tool is implemented in Python, and will be initially tested on two applications: the Senegal River water system, in West Africa, and the Seine River, in France.
Bellman, Richard
2003-01-01
An introduction to the mathematical theory of multistage decision processes, this text takes a ""functional equation"" approach to the discovery of optimum policies. Written by a leading developer of such policies, it presents a series of methods, uniqueness and existence theorems, and examples for solving the relevant equations. The text examines existence and uniqueness theorems, the optimal inventory equation, bottleneck problems in multistage production processes, a new formalism in the calculus of variation, strategies behind multistage games, and Markovian decision processes. Each chapte
SMDP基于性能势的神经元动态规划%Performance Potential-based Neuro-dynamic Programming for SMDPs
Institute of Scientific and Technical Information of China (English)
唐昊; 袁继彬; 陆阳; 程文娟
2005-01-01
An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimization of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamic programming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performance error bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, a numerical example is provided.
Fast approximate convex decomposition using relative concavity
Ghosh, Mukulika
2013-02-01
Approximate convex decomposition (ACD) is a technique that partitions an input object into approximately convex components. Decomposition into approximately convex pieces is both more efficient to compute than exact convex decomposition and can also generate a more manageable number of components. It can be used as a basis of divide-and-conquer algorithms for applications such as collision detection, skeleton extraction and mesh generation. In this paper, we propose a new method called Fast Approximate Convex Decomposition (FACD) that improves the quality of the decomposition and reduces the cost of computing it for both 2D and 3D models. In particular, we propose a new strategy for evaluating potential cuts that aims to reduce the relative concavity, rather than absolute concavity. As shown in our results, this leads to more natural and smaller decompositions that include components for small but important features such as toes or fingers while not decomposing larger components, such as the torso, that may have concavities due to surface texture. Second, instead of decomposing a component into two pieces at each step, as in the original ACD, we propose a new strategy that uses a dynamic programming approach to select a set of n c non-crossing (independent) cuts that can be simultaneously applied to decompose the component into n c+1 components. This reduces the depth of recursion and, together with a more efficient method for computing the concavity measure, leads to significant gains in efficiency. We provide comparative results for 2D and 3D models illustrating the improvements obtained by FACD over ACD and we compare with the segmentation methods in the Princeton Shape Benchmark by Chen et al. (2009) [31]. © 2012 Elsevier Ltd. All rights reserved.
Expectation Consistent Approximate Inference
DEFF Research Database (Denmark)
Opper, Manfred; Winther, Ole
2005-01-01
We propose a novel framework for approximations to intractable probabilistic models which is based on a free energy formulation. The approximation can be understood from replacing an average over the original intractable distribution with a tractable one. It requires two tractable probability dis...
Institute of Scientific and Technical Information of China (English)
LIU Xiao; WANG Cheng-en
2005-01-01
This paper addresses a single item dynamic lot-sizing model with inventory capacity and out-sourcing. The goal is to minimize the total costs of production, setup, inventory holding and out-sourcing. Two versions of an out-sourcing model with time-varying costs are considered: stock out case and conservation case. Zero Inventory Order property has been found and some new properties are obtained in an optimal solution. Dynamic programming algorithms are developed to solve the problem in strongly polynomial time respectively. Furthermore, some numerical results demonstrate that the approach proposed is efficient and applicable.
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
An Approach for Dynamic Optimization of Prevention Program Implementation in Stochastic Environments
Kang, Yuncheol; Prabhu, Vittal
The science of preventing youth problems has significantly advanced in developing evidence-based prevention program (EBP) by using randomized clinical trials. Effective EBP can reduce delinquency, aggression, violence, bullying and substance abuse among youth. Unfortunately the outcomes of EBP implemented in natural settings usually tend to be lower than in clinical trials, which has motivated the need to study EBP implementations. In this paper we propose to model EBP implementations in natural settings as stochastic dynamic processes. Specifically, we propose Markov Decision Process (MDP) for modeling and dynamic optimization of such EBP implementations. We illustrate these concepts using simple numerical examples and discuss potential challenges in using such approaches in practice.
Ordered cones and approximation
Keimel, Klaus
1992-01-01
This book presents a unified approach to Korovkin-type approximation theorems. It includes classical material on the approximation of real-valuedfunctions as well as recent and new results on set-valued functions and stochastic processes, and on weighted approximation. The results are notonly of qualitative nature, but include quantitative bounds on the order of approximation. The book is addressed to researchers in functional analysis and approximation theory as well as to those that want to applythese methods in other fields. It is largely self- contained, but the readershould have a solid background in abstract functional analysis. The unified approach is based on a new notion of locally convex ordered cones that are not embeddable in vector spaces but allow Hahn-Banach type separation and extension theorems. This concept seems to be of independent interest.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1993-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All the...... calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Agrawal, Divya
Dual-beam ELF/VLF wave generation experiments performed at the High-frequency Active Auroral Research Program (HAARP) HF transmitter in Gakona, Alaska are critically compared with the predictions of a newly developed ionospheric high frequency (HF) heating model that accounts for the simultaneous propagation and absorption of multiple HF beams. The dual-beam HF heating experiments presented herein consist of two HF beams transmitting simultaneously: one amplitude modulated (AM) HF beam modulates the conductivity of the lower ionosphere in the extremely low frequency (ELF, 30 Hz to 3 kHz) and/or very low frequency (VLF, 3 kHz to 30 kHz) band while a second HF beam broadcasts a continuous waveform (CW) signal, modifying the efficiency of ELF/VLF conductivity modulation and thereby the efficiency of ELF/VLF wave generation. Ground-based experimental observations are used together with the predictions of the theoretical model to identify the property of the received ELF/VLF wave that is most sensitive to the effects of multi-beam HF heating, and that property is determined to be the ELF/VLF signal magnitude. The dependence of the generated ELF/VLF wave magnitude on several HF transmission parameters (HF power, HF frequency, and modulation waveform) is then experimentally measured and analyzed within the context of the multi-beam HF heating model. For all cases studied, the received ELF/VLF wave magnitude as a function of transmission parameter is analyzed to identify the dependence on the ambient D-region electron density (Ne) and/or electron temperature ( Te), in turn identifying the HF transmission parameters that provide significant independent information regarding the ambient conditions of the D-region ionosphere. A theoretical analysis is performed to determine the conditions under which the effects of Ne and Te can be decoupled, and the results of this analysis are applied to identify an electron density profile that can reproduce the unusually high level of ELF
Water-cooled end-point boundary temperature control of hot strip via dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Samaras, N.S. [Danieli Automation, Pittsburgh, PA (United States); Simaan, M.A. [Univ. of Pittsburgh, PA (United States). Dept. of Electrical Engineering
1998-11-01
In this paper, an end-point boundary temperature control approach for runout table cooling used in hot strip mills is presented. The system relies on a linearized model for describing heat radiated to the environment and heat transferred to cooling water. At first, a conventional feedforward control design to control the temperature at the end-point boundary, the only measurable controlled parameter, is presented. Subsequently, a modified control scheme which uses dynamic programming to minimize the temperature error at the end-point boundary is discussed in detail. System performance analysis via simulation is presented for both control schemes. Simulation results show that temperature error minimization by dynamic programming improves system performance.
Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao
2013-07-01
This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.
Optimum Repartition of Transport Capacities in the Logistic System using Dynamic Programming
Directory of Open Access Journals (Sweden)
Gheorghe BĂŞANU
2011-08-01
Full Text Available Transportations take an essential role in logistics, interconnecting the majority of processes and operations within logistic system. The efficient use of transportation capacity is a priority whose achievement can diminish logistic costs. This objective is today difficult to achieve due to increasing complexity of transportation monitoring and coordination. This complexity is determined by transportation number and diversity, by the volume and diversity of orders, by increasing the targets to be supplied.Dynamic programming represents a highly useful tool for logistic managers, considering that its specific techniques and methods are oriented toward solving problems related to resource optimum allocation and utilization.The present paper presents briefly a series of theoretical elements of dynamic programming applied in logistics, based on which it is shown a mathematic model to determine the optimum policy for transport capacity repartition for the area attached to a logistic centre, through three distribution centres.
Pilkey, W. D.; Wang, B. P.; Yoo, Y.; Clark, B.
1973-01-01
A description and applications of a computer capability for determining the ultimate optimal behavior of a dynamically loaded structural-mechanical system are presented. This capability provides characteristics of the theoretically best, or limiting, design concept according to response criteria dictated by design requirements. Equations of motion of the system in first or second order form include incompletely specified elements whose characteristics are determined in the optimization of one or more performance indices subject to the response criteria in the form of constraints. The system is subject to deterministic transient inputs, and the computer capability is designed to operate with a large linear programming on-the-shelf software package which performs the desired optimization. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of dynamics problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.
Institute of Scientific and Technical Information of China (English)
HEWei; YANGSuqiong; YUANBaozong; LINBiqin
2004-01-01
Shortest path search has important practical applications and is related to optimization problem.This paper discusses a new algorithm time-synchronous heuristic dynamic programming search, which combined the pruning and global optimization of DP (Dynamic programming) and the partial search of heuristic strategy and found the shortest path in time O(n/kd) (k, d ≥ 1). Furthermore, the algorithm can be applied to find the K shortest paths between a pair of given nodes or all paths less than a given length within the same steps. Finally this algorithm was applied to the shortest path search on the real map and user could use spoken dialog to query shortcut in realtime, 90% of the system responses are correct.
Approximation concepts for efficient structural synthesis
Schmit, L. A., Jr.; Miura, H.
1976-01-01
It is shown that efficient structural synthesis capabilities can be created by using approximation concepts to mesh finite element structural analysis methods with nonlinear mathematical programming techniques. The history of the application of mathematical programming techniques to structural design optimization problems is reviewed. Several rather general approximation concepts are described along with the technical foundations of the ACCESS 1 computer program, which implements several approximation concepts. A substantial collection of structural design problems involving truss and idealized wing structures is presented. It is concluded that since the basic ideas employed in creating the ACCESS 1 program are rather general, its successful development supports the contention that the introduction of approximation concepts will lead to the emergence of a new generation of practical and efficient, large scale, structural synthesis capabilities in which finite element analysis methods and mathematical programming algorithms will play a central role.
Perry, B., III; Goetz, R. C.; Kroll, R. I.; Miller, R. D.
1979-01-01
This paper describes and illustrates the capabilities of the DYLOFLEX Computer Program System. DYLOFLEX is an integrated system of computer programs for calculating dynamic loads of flexible airplanes with active control systems. A brief discussion of the engineering formulation for each of the nine DYLOFLEX programs is described. The capabilities of the system are illustrated by the analyses of two example configurations.
Drennan, Arthur Paul
1994-01-01
This thesis develops a dynamic program, the SEASPARROW Coordinated Assignment Model (SCAM), that determines the optimal coordinated assignment policy for the SEASPARROW missile in a shipboard self defense weapon configuration consisting of the NATO SEASPARROW Missile System, the Rolling Airframe Missile and the Phalanx Close-In Weapon System. Threat scenarios are described by the type of' anti-ship cruise missile, the number of threat missiles, the total duration of the arrival window and the...
A Generalized Speckle Tracking Algorithm for Ultrasonic Strain Imaging Using Dynamic Programming
Jiang, Jingfeng; Hall, Timothy J.
2009-01-01
This study developed an improved motion estimation algorithm for ultrasonic strain imaging that employs a dynamic programming technique. In this paper, we model the motion estimation task as an optimization problem. Since tissue motion under external mechanical stimuli often should be reasonably continuous, a set of cost functions combining correlation and various levels of motion continuity constraint were used to regularize the motion estimation. To solve the optimization problem with a rea...
A Linear Dynamic Programming Approach to Irrigation System Management with Depleting Groundwater
Stoecker, A. L.; A. Seidmann; Lloyd, G S
1985-01-01
A model for measuring the economic benefits of irrigation system development over a depleting aquifer is presented, along with related methodology for detailed long-range farm planning. The paper considers management issues, such as distribution system configuration, drilling policy, area developed for irrigation, and crop production. A Linear Dynamic Programming (LDP) method is developed and applied to derive optimal temporal investments in the use of stock resources and long-term cropping p...
A Dynamic Programming Algorithm on Project-Gang Investment Decision-Making
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The investment decision-making of Project-Gang, the projects that are associated with one another on economy and technique, is studied. In order to find out the best Scheme that can make the maximum profit, a dynamic programming algorithm on the investment decision-making of Project-Gang is brought forward, and this algorithm can find out the best Scheme of distributing the m resources to the n Items in the time of O(m2n).
Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
Newberg, Lee A.
2008-01-01
Motivation: A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward–backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values f...
α-Coupled Fixed Points and Their Application in Dynamic Programming
Directory of Open Access Journals (Sweden)
J. Harjani
2014-01-01
Full Text Available We introduce the definition of α-coupled fixed point in the space of the bounded functions on a set S and we present a result about the existence and uniqueness of such points. Moreover, as an application of our result, we study the problem of existence and uniqueness of solutions for a class of systems of functional equations arising in dynamic programming.
Zhen Wu; Zongyuan Huang
2010-01-01
This paper is concerned with a kind of corporate international optimal portfolio and consumption choice problems, in which the investor can invest her or his wealth either in a domestic bond (bank account) or in an oversea real project with production. The bank pays a lower interest rate for deposit and takes a higher rate for any loan. First, we show that Bellman's dynamic programming principle still holds in our setting; second, in terms of the foregoing principle, we obtain the investor's ...
Dynamic Programming Principle for Stochastic Recursive Optimal Control Problem under G-framework
Hu, Mingshang; Ji, Shaolin
2014-01-01
In this paper, we study a stochastic recursive optimal control problem in which the cost functional is described by the solution of a backward stochastic differential equation driven by G-Brownian motion. Under standard assumptions, we establish the dynamic programming principle and the related fully nonlinear HJB equation in the framework of G-expectation. Finally, we show that the value function is the viscosity solution of the obtained HJB equation.
Vintage Capital in the AK growth model: a Dynamic Programming approach. Extended version.
Fabbri, Giorgio; Gozzi, Fausto
2006-01-01
This paper deals with an endogenous growth model with vintage capital and, more precisely, with the AK model proposed in [18]. In endogenous growth models the introduction of vintage capital allows to explain some growth facts but strongly increases the mathematical difficulties. So far, in this approach, the model is studied by the Maximum Principle; here we develop the Dynamic Programming approach to the same problem by obtaining sharper results and we provide more insight about the economi...
Dynamic Programming for controlled Markov families: abstractly and over Martingale Measures
Gordan Zitkovic
2013-01-01
We describe an abstract control-theoretic framework in which the validity of the dynamic programming principle can be established in continuous time by a verification of a small number of structural properties. As an application we treat several cases of interest, most notably the lower-hedging and utility-maximization problems of financial mathematics both of which are naturally posed over ``sets of martingale measures''.
Infnite-Horizon Deterministic Dynamic Programming in Discrete Time: A Monotone Convergence Principle
Takashi Kamihigashi; Masayuki Yao
2015-01-01
We consider infinite-horizon deterministic dynamic programming problems in discrete time. We show that the value function is always a fixed point of a modified version of the Bellman operator. We also show that value iteration monotonically converges to the value function if the initial function is dominated by the value function, is mapped upward by the modified Bellman operator, and satisfies a transversality-like condition. These results require no assumption except for the general framewo...
On the dynamic programming principle for controlled diffusion processes in a cylindrical region
Dmitry B. Rokhlin
2012-01-01
We prove the dynamic programming principle for a class of diffusion processes controlled up to the time of exit from a cylindrical region $[0,T)\\times G$. It is assumed that the functional to be maximized is in the Lagrange form with nonnegative integrand. Besides this we only adopt the standard assumptions, ensuring the existence of a unique strong solution of a stochastic differential equation for the state process.
Discrete time McKean-Vlasov control problem: a dynamic programming approach
Pham, Huyên; Wei, Xiaoli
2015-01-01
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean-Vlasov control problem.
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
A dynamic programming algorithm for the space allocation and aisle positioning problem
Peter Bodnar; Jens Lysgaard
2014-01-01
The space allocation and aisle positioning problem (SAAPP) in a material handling system with gravity flow racks is the problem of minimizing the total number of replenishments over a period subject to practical constraints related to the need for aisles granting safe and easy access to storage locations. In this paper, we develop an exact dynamic programming algorithm for the SAAPP. The computational study shows that our exact algorithm can be used to find optimal solutions for numerous SAAP...
The Impact of Crop Price on Nitrous Oxide Emissions: A Dynamic Programming Approach
Cai, Ruohong; Zhang, Xin; Kanter, David
2014-01-01
The use of N fertilizer in agriculture is a major source of Nitrous Oxide, an important greenhouse gases. Market-based instruments, such as incentives or taxes, may help reduce Nitrous Oxide emission by changing Nitrogen application rate. Using a dynamic programming approach, we found that changing corn price or fertilizer price have effects on both farm profit and Nitrogen application rate. However, farm profit and Nitrogen rate always change in the same direction when affected by either inp...
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xinguo;
2014-01-01
Optimal management of conjunctive use of surface water and groundwater has been attempted with different algorithms in the literature. In this study, a hydro-economic modelling approach to optimize conjunctive use of scarce surface water and groundwater resources under uncertainty is presented....... A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due...... to head-dependent pumping costs. These dynamic pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment...
The Karlqvist approximation revisited
Tannous, C.
2015-01-01
The Karlqvist approximation signaling the historical beginning of magnetic recording head theory is reviewed and compared to various approaches progressing from Green, Fourier, Conformal mapping that obeys the Sommerfeld edge condition at angular points and leads to exact results.
Approximations in Inspection Planning
DEFF Research Database (Denmark)
Engelund, S.; Sørensen, John Dalsgaard; Faber, M. H.;
2000-01-01
Planning of inspections of civil engineering structures may be performed within the framework of Bayesian decision analysis. The effort involved in a full Bayesian decision analysis is relatively large. Therefore, the actual inspection planning is usually performed using a number of approximations....... One of the more important of these approximations is the assumption that all inspections will reveal no defects. Using this approximation the optimal inspection plan may be determined on the basis of conditional probabilities, i.e. the probability of failure given no defects have been found...... by the inspection. In this paper the quality of this approximation is investigated. The inspection planning is formulated both as a full Bayesian decision problem and on the basis of the assumption that the inspection will reveal no defects....
Directory of Open Access Journals (Sweden)
Malvina Baica
1985-01-01
Full Text Available The author uses a new modification of Jacobi-Perron Algorithm which holds for complex fields of any degree (abbr. ACF, and defines it as Generalized Euclidean Algorithm (abbr. GEA to approximate irrationals.
Dynamic trunk stabilization: a conceptual back injury prevention program for volleyball athletes.
Smith, Chad E; Nyland, John; Caudill, Paul; Brosky, Joseph; Caborn, David N M
2008-11-01
The sport of volleyball creates considerable dynamic trunk stability demands. Back injury occurs all too frequently in volleyball, particularly among female athletes. The purpose of this clinical commentary is to review functional anatomy, muscle coactivation strategies, assessment of trunk muscle performance, and the characteristics of effective exercises for the trunk or core. From this information, a conceptual progressive 3-phase volleyball-specific training program is presented to improve dynamic trunk stability and to potentially reduce the incidence of back injury among volleyball athletes. Phase 1 addresses low-velocity motor control, kinesthetic awareness, and endurance, with the clinician providing cues to teach achievement of biomechanically neutral spine alignment. Phase 2 focuses on progressively higher velocity dynamic multiplanar endurance, coordination, and strength-power challenges integrating upper and lower extremity movements, while maintaining neutral spine alignment. Phase 3 integrates volleyball-specific skill simulations by breaking down composite movement patterns into their component parts, with differing dynamic trunk stability requirements, while maintaining neutral spine alignment. Prospective research is needed to validate the efficacy of this program. PMID:18978452
Approximation Behooves Calibration
DEFF Research Database (Denmark)
da Silva Ribeiro, André Manuel; Poulsen, Rolf
2013-01-01
Calibration based on an expansion approximation for option prices in the Heston stochastic volatility model gives stable, accurate, and fast results for S&P500-index option data over the period 2005–2009.......Calibration based on an expansion approximation for option prices in the Heston stochastic volatility model gives stable, accurate, and fast results for S&P500-index option data over the period 2005–2009....
Gautschi, Walter; Rassias, Themistocles M
2011-01-01
Approximation theory and numerical analysis are central to the creation of accurate computer simulations and mathematical models. Research in these areas can influence the computational techniques used in a variety of mathematical and computational sciences. This collection of contributed chapters, dedicated to renowned mathematician Gradimir V. Milovanovia, represent the recent work of experts in the fields of approximation theory and numerical analysis. These invited contributions describe new trends in these important areas of research including theoretic developments, new computational alg
Institute of Scientific and Technical Information of China (English)
JAHAN A; ABDOLSHAH M
2007-01-01
At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows: ① Minimizing deviation of customer's requirements. ② Maximizing the profit. ③ Minimizing the frequencies of changes in formula production. ④ Minimizing the inventory of final products. ⑤ Balancing the production sections with regard to rate in production. ⑥ Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that's how it is solved.
Alsolami, Fawaz
2013-01-01
This paper is devoted to the study of algorithms for sequential optimization of approximate inhibitory rules relative to the length, coverage and number of misclassifications. Theses algorithms are based on extensions of dynamic programming approach. The results of experiments for decision tables from UCI Machine Learning Repository are discussed. © 2013 Springer-Verlag.
International Nuclear Information System (INIS)
This report documents the results of the main projects undertaken under the Environmental and Dynamic Equipment Qualification Research Program (EDQP) sponsored by the U.S. Nuclear Regulatory Commission (NRC) under FIN A6322. Lasting from fiscal year 1983 to 1987, the program dealt with environmental and dynamic (including seismic) equipment qualification issues for mechanical and electromechanical components and systems used in nuclear power plants. The research results have since been used by both the NRC and industry. The program included seven major research projects that addressed the following issues: (a) containment purge and vent valves performing under design basis loss of coolant accident loads, (b) containment piping penetrations and isolation valves performing under seismic loadings and design basis and severe accident containment wall displacements, (c) shaft seals for primary coolant pumps performing under station blackout conditions, (d) electrical cabinet internals responding to in-structure generated motion (rattling), and (e) in situ piping and valves responding to seismic loadings. Another project investigating whether certain containment isolation valves will close under design basis conditions was also started under this program. This report includes eight main section, each of which provides a brief description of one of the projects, a summary of the findings, and an overview of the application of the results. A bibliography lists the journal articles, papers, and reports that document the research
Weeks, Cindy Lou
1986-01-01
Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.
Wright, Robert; Abraham, Edo; Parpas, Panos; Stoianov, Ivan
2015-12-01
The operation of water distribution networks (WDN) with a dynamic topology is a recently pioneered approach for the advanced management of District Metered Areas (DMAs) that integrates novel developments in hydraulic modeling, monitoring, optimization, and control. A common practice for leakage management is the sectorization of WDNs into small zones, called DMAs, by permanently closing isolation valves. This facilitates water companies to identify bursts and estimate leakage levels by measuring the inlet flow for each DMA. However, by permanently closing valves, a number of problems have been created including reduced resilience to failure and suboptimal pressure management. By introducing a dynamic topology to these zones, these disadvantages can be eliminated while still retaining the DMA structure for leakage monitoring. In this paper, a novel optimization method based on sequential convex programming (SCP) is outlined for the control of a dynamic topology with the objective of reducing average zone pressure (AZP). A key attribute for control optimization is reliable convergence. To achieve this, the SCP method we propose guarantees that each optimization step is strictly feasible, resulting in improved convergence properties. By using a null space algorithm for hydraulic analyses, the computations required are also significantly reduced. The optimized control is actuated on a real WDN operated with a dynamic topology. This unique experimental program incorporates a number of technologies set up with the objective of investigating pioneering developments in WDN management. Preliminary results indicate AZP reductions for a dynamic topology of up to 6.5% over optimally controlled fixed topology DMAs. This article was corrected on 12 JAN 2016. See the end of the full text for details.
Low Rank Approximation in $G_0W_0$ Approximation
Shao, Meiyue; Yang, Chao; Liu, Fang; da Jornada, Felipe H; Deslippe, Jack; Louie, Steven G
2016-01-01
The single particle energies obtained in a Kohn--Sham density functional theory (DFT) calculation are generally known to be poor approximations to electron excitation energies that are measured in transport, tunneling and spectroscopic experiments such as photo-emission spectroscopy. The correction to these energies can be obtained from the poles of a single particle Green's function derived from a many-body perturbation theory. From a computational perspective, the accuracy and efficiency of such an approach depends on how a self energy term that properly accounts for dynamic screening of electrons is approximated. The $G_0W_0$ approximation is a widely used technique in which the self energy is expressed as the convolution of a non-interacting Green's function ($G_0$) and a screened Coulomb interaction ($W_0$) in the frequency domain. The computational cost associated with such a convolution is high due to the high complexity of evaluating $W_0$ at multiple frequencies. In this paper, we discuss how the cos...
A computer code for beam optics calculation--third order approximation
Institute of Scientific and Technical Information of China (English)
L(U) Jianqin; LI Jinhai
2006-01-01
To calculate the beam transport in the ion optical systems accurately, a beam dynamics computer program of third order approximation is developed. Many conventional optical elements are incorporated in the program. Particle distributions of uniform type or Gaussian type in the ( x, y, z ) 3D ellipses can be selected by the users. The optimization procedures are provided to make the calculations reasonable and fast. The calculated results can be graphically displayed on the computer monitor.
User's manual for CNVUFAC, the general dynamics heat-transfer radiation view factor program
Energy Technology Data Exchange (ETDEWEB)
Wong, R. L.
1976-06-25
CNVUFAC, the General Dynamics heat-transfer radiation veiw factor program, has been adapted for use on the LLL CDC 7600 computer system. The input and output have been modified, and a node incrementing logic was included to make the code compatible with the TRUMP thermal analyzer and related codes. The program performs the multiple integration necessary to evaluate the geometric black-body radiaton node to node view factors. Card image output that contains node number and view factor information is generated for input into the related program GRAY. Program GRAY is then used to include the effects of gray-body emissivities and multiple reflections, generating the effective gray-body view factors usable in TRUMP. CNVUFAC uses an elemental area summation scheme to evaluate the multiple integrals. The program permits shadowing and self-shadowing. The basic configuration shapes that can be considered are cylinders, cones, spheres, ellipsoids, flat plates, disks, toroids, and polynomials of revolution. Portions of these shapes can also be considered.
International Nuclear Information System (INIS)
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 pi 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 pi 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 the decision
Approximate and Incomplete Factorizations
Chan, T.F.; Vorst, H.A. van der
2001-01-01
In this chapter, we give a brief overview of a particular class of preconditioners known as incomplete factorizations. They can be thought of as approximating the exact LU factorization of a given matrix A (e.g. computed via Gaussian elimination) by disallowing certain ll-ins. As opposed to other PD
White, Martin
2014-01-01
This year marks the 100th anniversary of the birth of Yakov Zel'dovich. Amongst his many legacies is the Zel'dovich approximation for the growth of large-scale structure, which remains one of the most successful and insightful analytic models of structure formation. We use the Zel'dovich approximation to compute the two-point function of the matter and biased tracers, and compare to the results of N-body simulations and other Lagrangian perturbation theories. We show that Lagrangian perturbation theories converge well and that the Zel'dovich approximation provides a good fit to the N-body results except for the quadrupole moment of the halo correlation function. We extend the calculation of halo bias to 3rd order and also consider non-local biasing schemes, none of which remove the discrepancy. We argue that a part of the discrepancy owes to an incorrect prediction of inter-halo velocity correlations. We use the Zel'dovich approximation to compute the ingredients of the Gaussian streaming model and show that ...
DEFF Research Database (Denmark)
Madsen, Rasmus Elsborg
2005-01-01
The Dirichlet compound multinomial (DCM), which has recently been shown to be well suited for modeling for word burstiness in documents, is here investigated. A number of conceptual explanations that account for these recent results, are provided. An exponential family approximation of the DCM that...
A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism
Directory of Open Access Journals (Sweden)
Farhad Ghassemi Tari
2016-01-01
Full Text Available The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.
Optimal bipedal interactions with dynamic terrain: synthesis and analysis via nonlinear programming
Hubicki, Christian; Goldman, Daniel; Ames, Aaron
In terrestrial locomotion, gait dynamics and motor control behaviors are tuned to interact efficiently and stably with the dynamics of the terrain (i.e. terradynamics). This controlled interaction must be particularly thoughtful in bipeds, as their reduced contact points render them highly susceptible to falls. While bipedalism under rigid terrain assumptions is well-studied, insights for two-legged locomotion on soft terrain, such as sand and dirt, are comparatively sparse. We seek an understanding of how biological bipeds stably and economically negotiate granular media, with an eye toward imbuing those abilities in bipedal robots. We present a trajectory optimization method for controlled systems subject to granular intrusion. By formulating a large-scale nonlinear program (NLP) with reduced-order resistive force theory (RFT) models and jamming cone dynamics, the optimized motions are informed and shaped by the dynamics of the terrain. Using a variant of direct collocation methods, we can express all optimization objectives and constraints in closed-form, resulting in rapid solving by standard NLP solvers, such as IPOPT. We employ this tool to analyze emergent features of bipedal locomotion in granular media, with an eye toward robotic implementation.
A Dynamic Programming Approach to Finite-horizon Coherent Quantum LQG Control
Vladimirov, Igor G
2011-01-01
The paper considers the coherent quantum Linear Quadratic Gaussian (CQLQG) control problem for time-varying quantum plants governed by linear quantum stochastic differential equations over a bounded time interval. A controller is sought among quantum linear systems satisfying physical realizability (PR) conditions. The latter describe the dynamic equivalence of the system to an open quantum harmonic oscillator and relate its state-space matrices to the free Hamiltonian, coupling and scattering operators of the oscillator. Using the Hamiltonian parameterization of PR controllers, the CQLQG problem is recast into an optimal control problem for a deterministic system governed by a differential Lyapunov equation. The state of this subsidiary system is the symmetric part of the quantum covariance matrix of the plant-controller state vector. The resulting covariance control problem is treated using dynamic programming and Pontryagin's minimum principle. The associated Hamilton-Jacobi-Bellman equation for the minimu...
A data base and analysis program for shuttle main engine dynamic pressure measurements
Coffin, T.
1986-01-01
A dynamic pressure data base management system is described for measurements obtained from space shuttle main engine (SSME) hot firing tests. The data were provided in terms of engine power level and rms pressure time histories, and power spectra of the dynamic pressure measurements at selected times during each test. Test measurements and engine locations are defined along with a discussion of data acquisition and reduction procedures. A description of the data base management analysis system is provided and subroutines developed for obtaining selected measurement means, variances, ranges and other statistics of interest are discussed. A summary of pressure spectra obtained at SSME rated power level is provided for reference. Application of the singular value decomposition technique to spectrum interpolation is discussed and isoplots of interpolated spectra are presented to indicate measurement trends with engine power level. Program listings of the data base management and spectrum interpolation software are given. Appendices are included to document all data base measurements.
Approximation algorithms for the fixed-topology phylogenetic number problem
Energy Technology Data Exchange (ETDEWEB)
Cryan, M.; Goldberg, L.A. [Univ. of Warwick, Coventry (United Kingdom). Dept. of Computer Science; Phillips, C.A. [Sandia National Labs., Albuquerque, NM (United States)
1997-04-01
In the {ell}-phylogeny problem, one wishes to construct an evolutionary tree for a set of species represented by characters, in which each state of each character induces no more than {ell} connected components. The authors consider the fixed-topology version of this problem for fixed-topologies of arbitrary degree. This version of the problem is known to be NP-complete for {ell} {ge} 3 even for degree-3 trees in which no state labels more than {ell} + 1 leaves (and therefore there is a trivial {ell} + 1 phylogeny). They give a 2-approximation algorithm for all {ell} {ge} 3 for arbitrary input topologies and they given an optimal approximation algorithm that constructs a 4-phylogeny when a 3-phylogeny exists. Dynamic programming techniques, which are typically used in fixed-topology problems, cannot be applied to {ell}-phylogeny problems. The 2-approximation algorithm is the first application of linear programming to approximation algorithms for phylogeny problems. They extend their results to a related problem in which characters are polymorphic.
Dall'Anese, Emiliano; Dhople, Sairaj; Giannakis, Georgios B.
2014-01-01
This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of network-wide constrained optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual epsilon-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference...
Optimization and analysis of decision trees and rules: Dynamic programming approach
Alkhalid, Abdulaziz
2013-08-01
This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.
Bellman, Richard
2015-01-01
Rapid advances in the physical and biological sciences and in related technologies have brought about equally farreaching changes in mathematical research. Focusing on control theory, invariant imbedding, dynamic programming, and quasilinearization, Mr. Bellman explores with ease and clarity the mathematical research problems arising from scientific questions in engineering, physics, biology, and medicine. Special attention is paid in these essays to the use of the digital computer in obtaining the numerical solution of numerical problems, its influence in the formulation of new and old scient
The Repeated School-to-Work Transition: Evidence from a Dynamic Programming Model
DEFF Research Database (Denmark)
Nielsen, Helena Skyt
In continental Europe, high school graduates often interrupt their educational career before entering further education. This behavior incurs substantial cost on the youths and on society in particular. The focus of this paper is the choice between school and joining the labor force, which is faced...... by youths after high school graduation. It is assumed that the decision is taken year by year, and it is analyzed in a discrete choice dynamic programming model. In this forward-looking behavioral model, it is shown that a small bonus would remove interruptions of the educational careers just after high...... school....
Dynamic Simulations of Nonlinear Multi-Domain Systems Based on Genetic Programming and Bond Graphs
Institute of Scientific and Technical Information of China (English)
DI Wenhui; SUN Bo; XU Lixin
2009-01-01
A dynamic simulation method for non-linear systems based on genetic programming (GP) and bond graphs (BG) was developed to improve the design of nonlinear multi-domain energy conversion sys-tems. The genetic operators enable the embryo bond graph to evolve towards the target graph according to the fitness function. Better simulation requires analysis of the optimization of the eigenvalue and the filter circuit evolution. The open topological design and space search ability of this method not only gives a more optimized convergence for the operation, but also reduces the generation time for the new circuit graph for the design of nonlinear multi-domain systems.
Prestack traveltime approximations
Alkhalifah, Tariq Ali
2011-01-01
Most prestack traveltime relations we tend work with are based on homogeneous (or semi-homogenous, possibly effective) media approximations. This includes the multi-focusing or double square-root (DSR) and the common reflection stack (CRS) equations. Using the DSR equation, I analyze the associated eikonal form in the general source-receiver domain. Like its wave-equation counterpart, it suffers from a critical singularity for horizontally traveling waves. As a result, I derive expansion based solutions of this eikonal based on polynomial expansions in terms of the reflection and dip angles in a generally inhomogenous background medium. These approximate solutions are free of singularities and can be used to estimate travetimes for small to moderate offsets (or reflection angles) in a generally inhomogeneous medium. A Marmousi example demonstrates the usefulness of the approach. © 2011 Society of Exploration Geophysicists.
Human dynamics of spending: Longitudinal study of a coalition loyalty program
Yi, Il Gu; Jeong, Hyang Min; Choi, Woosuk; Jang, Seungkwon; Lee, Heejin; Kim, Beom Jun
2014-09-01
Large-scale data of a coalition loyalty program is analyzed in terms of the temporal dynamics of customers' behaviors. We report that the two main activities of a loyalty program, earning and redemption of points, exhibit very different behaviors. It is also found that as customers become older from their early 20's, both male and female customers increase their earning and redemption activities until they arrive at the turning points, beyond which both activities decrease. The positions of turning points as well as the maximum earned and redeemed points are found to differ for males and females. On top of these temporal behaviors, we identify that there exists a learning effect and customers learn how to earn and redeem points as their experiences accumulate in time.
Vectorization of molecular dynamics Fortran programs using the cyber 205 vector processing computer
Vogelsang, R.; Schoen, M.; Hoheisel, C.
1983-11-01
A concept of vectorization of molecular dynamics Fortran programs for the use of the Cyber 205 machine is presented. It is shown that for calculations with larger particle systems the program runs faster on the 205 than on the Cray-1 by about a factor of two. Against conventional computers like the Cyber 175 an acceleration by a factor 10-15 is expected. A bit control vector is used instead of a neighbour list, which in principal provides calculations up to 6912 particles for the memory capacity of the Cyber 205. However, because the application of the bit vector requires computation times which grow proportional to N2, the CPU time for particle numbers of more than 2048 becomes prohibitively large.
K-TIF: a two-fluid computer program for downcomer flow dynamics. [PWR
Energy Technology Data Exchange (ETDEWEB)
Amsden, A.A.; Harlow, F.H.
1977-10-01
The K-TIF computer program has been developed for numerical solution of the time-varying dynamics of steam and water in a pressurized water reactor downcomer. The current status of physical and mathematical modeling is presented in detail. The report also contains a complete description of the numerical solution technique, a full description and listing of the computer program, instructions for its use, with a sample printout for a specific test problem. A series of calculations, performed with no change in the modeling parameters, shows consistent agreement with the experimental trends over a wide range of conditions, which gives confidence to the calculations as a basis for investigating the complicated physics of steam-water flows in the downcomer.
DEFF Research Database (Denmark)
Hu, Rui; Hu, Weihao; Li, Pengfei;
2016-01-01
to its stable limits. Once the blackout happens, a well-designed restoration strategy is significant. This paper focuses on how to ameliorate the power system restoration procedures to adapt the high wind power penetration and how to take full advantages of the wind power plants during the...... and relatively low cost. Thus, many countries are increasing the wind power penetration in their power system step by step, such as Denmark, Spain and Germany. The incremental wind power penetration brings a lot of new issues in operation and programming. The power system sometimes will operate close...... restoration. In this paper, the possibility to exploit the stochastic wind power during restoration was discussed, and a Dynamic Programming (DP) method was proposed to make wind power contribute in the restoration rationally as far as possible. In this paper, the method is tested and verified by a modified...
Addressing gender dynamics and engaging men in HIV programs: lessons learned from Horizons research.
Pulerwitz, Julie; Michaelis, Annie; Verma, Ravi; Weiss, Ellen
2010-01-01
In the field of human immunodeficiency virus (HIV) prevention, there has been increasing interest in the role that gender plays in HIV and violence risk, and in successfully engaging men in the response. This article highlights findings from more than 10 studies in Asia, Africa, and Latin America--conducted from 1997 through 2007 as part of the Horizons program--that have contributed to understanding the relationship between gender and men's behaviors, developing useful measurement tools for gender norms, and designing and evaluating the impact of gender-focused program strategies. Studies showed significant associations between support for inequitable norms and risk, such as more partner violence and less condom use. Programmatic lessons learned ranged from insights into appropriate media messages, to strategies to engage men in critically reflecting upon gender inequality, to the qualities of successful program facilitators. The portfolio of work reveals the potential and importance of directly addressing gender dynamics in HIV- and violence-prevention programs for both men and women. PMID:20297757
Institute of Scientific and Technical Information of China (English)
黄震春; 李三立
2002-01-01
Memory gap has become an essential factor influencing the peak performance of high-speed CPU-based systems. To fill this gap, enlarging cache capacity has been a traditional method based on static program locality principle. However, the order of instructions stored in I-Cache before being sent to Data Processing Unit (DPU) is a kind of useful information that has not ever been utilized before. So an architecture containing an Instruction Processing Unit (IPU) in parallel with the ordinary DPU is proposed. The IPU can prefetch,analyze and preprocess a large amount of instructions otherwise lying in the I-Cache untouched.It is more efficient than the conventional prefetch buffer that can only store several instructions for previewing. By IPU, Load Instructions can be preprocessed while the DPU is executing on data simultaneously. It is termed as "Instruction Processing Unit with LOokahead Cache"(IPULOC for short) in which the idea of dynamic program locality is presented. This paper describes the principle of IPULOC and illustrates the quantitative parameters for evaluation.Tools for simulating the IPULOC have been developed. The simulation result shows that it can improve program locality during program execution, and hence can improve the cache hit ratio correspondingly without further enlarging the on-chip cache that occupies a large portion of chip area.
Baldwin, Robin Lynn Brunty
2013-01-01
The purpose of this study was to evaluate the dynamics of a successful planned giving program utilizing shared leadership at Historically Black Colleges and Universities (HBCUs). This information will assist the leadership in determining if and how a successful planned giving program can be established for HBCUs. It is possible for planned gifts…
MacGillivray, Laurie; Goode, Gretchen S.
2016-01-01
Researchers of after-school tutoring primarily focus on educational outcomes with little attention to the social dynamics of such programs. In our qualitative case study, we examined the nature of interactions among tutors in a tutoring program at a homeless shelter for families. Employing Bourdieu's concepts of "social capital" and…
Stockpile strategy for China's emergency oil reserve: A dynamic programming approach
International Nuclear Information System (INIS)
China is currently accelerating construction of its strategic petroleum reserves. How should China fill the SPR in a cost-effective manner in the short-run? How might this affect world oil prices? Using a dynamic programming model to answer these questions, the objective of this paper is to minimize the stockpiling costs, including consumer surplus as well as crude acquisition and holding costs. The crude oil acquisition price in the model is determined by global equilibrium between supply and demand. Demand, in turn, depends on world market conditions including China's stockpile filling rate. Our empirical study under different market conditions shows that China's optimal stockpile acquisition rate varies from 9 to 19 million barrels per month, and the optimal stockpiling drives up the world oil price by 3–7%. The endogenous price increase accounts for 52% of total stockpiling costs in the base case. When the market is tighter or the demand function is more inelastic, the stockpiling affects the market more significantly and pushes prices even higher. Alternatively, in a disruption, drawdown from the stockpile can effectively dampen soaring prices, though the shortage is likely to leave the price higher than before the disruption. - Highlights: • China's SPR policies are examined by dynamic programming. • The optimal stockpile acquisition rate varies from 9 to 19 million barrels per month. • The optimal stockpiling drives up world oil price by 3–7%
Ground test program for a full-size solar dynamic heat receiver
Sedgwick, L. M.; Kaufmann, K. J.; McLallin, K. L.; Kerslake, T. W.
Test hardware, facilities, and procedures were developed to conduct ground testing of a full-size, solar dynamic heat receiver in a partially simulated, low earth orbit environment. The heat receiver was designed to supply 102 kW of thermal energy to a helium and xenon gas mixture continuously over a 94 minute orbit, including up to 36 minutes of eclipse. The purpose of the test program was to quantify the receiver thermodynamic performance, its operating temperatures, and thermal response to changes in environmental and power module interface boundary conditions. The heat receiver was tested in a vacuum chamber using liquid nitrogen cold shrouds and an aperture cold plate. Special test equipment was designed to provide the required ranges in interface boundary conditions that typify those expected or required for operation as part of the solar dynamic power module on the Space Station Freedom. The support hardware includes an infrared quartz lamp heater with 30 independently controllable zones and a closed-Brayton cycle engine simulator to circulate and condition the helium-xenon gas mixture. The test article, test support hardware, facilities, and instrumentation developed to conduct the ground test program are all described.
A parallel dynamic programming algorithm for multi-reservoir system optimization
Li, Xiang; Wei, Jiahua; Li, Tiejian; Wang, Guangqian; Yeh, William W.-G.
2014-05-01
This paper develops a parallel dynamic programming algorithm to optimize the joint operation of a multi-reservoir system. First, a multi-dimensional dynamic programming (DP) model is formulated for a multi-reservoir system. Second, the DP algorithm is parallelized using a peer-to-peer parallel paradigm. The parallelization is based on the distributed memory architecture and the message passing interface (MPI) protocol. We consider both the distributed computing and distributed computer memory in the parallelization. The parallel paradigm aims at reducing the computation time as well as alleviating the computer memory requirement associated with running a multi-dimensional DP model. Next, we test the parallel DP algorithm on the classic, benchmark four-reservoir problem on a high-performance computing (HPC) system with up to 350 cores. Results indicate that the parallel DP algorithm exhibits good performance in parallel efficiency; the parallel DP algorithm is scalable and will not be restricted by the number of cores. Finally, the parallel DP algorithm is applied to a real-world, five-reservoir system in China. The results demonstrate the parallel efficiency and practical utility of the proposed methodology.
Ground test program for a full-size solar dynamic heat receiver
Sedgwick, L. M.; Kaufmann, K. J.; Mclallin, K. L.; Kerslake, T. W.
1991-01-01
Test hardware, facilities, and procedures were developed to conduct ground testing of a full-size, solar dynamic heat receiver in a partially simulated, low earth orbit environment. The heat receiver was designed to supply 102 kW of thermal energy to a helium and xenon gas mixture continuously over a 94 minute orbit, including up to 36 minutes of eclipse. The purpose of the test program was to quantify the receiver thermodynamic performance, its operating temperatures, and thermal response to changes in environmental and power module interface boundary conditions. The heat receiver was tested in a vacuum chamber using liquid nitrogen cold shrouds and an aperture cold plate. Special test equipment was designed to provide the required ranges in interface boundary conditions that typify those expected or required for operation as part of the solar dynamic power module on the Space Station Freedom. The support hardware includes an infrared quartz lamp heater with 30 independently controllable zones and a closed-Brayton cycle engine simulator to circulate and condition the helium-xenon gas mixture. The test article, test support hardware, facilities, and instrumentation developed to conduct the ground test program are all described.
Dynamic programming-based hot spot identification approach for pedestrian crashes.
Medury, Aditya; Grembek, Offer
2016-08-01
Network screening techniques are widely used by state agencies to identify locations with high collision concentration, also referred to as hot spots. However, most of the research in this regard has focused on identifying highway segments that are of concern to automobile collisions. In comparison, pedestrian hot spot detection has typically focused on analyzing pedestrian crashes in specific locations, such as at/near intersections, mid-blocks, and/or other crossings, as opposed to long stretches of roadway. In this context, the efficiency of the some of the widely used network screening methods has not been tested. Hence, in order to address this issue, a dynamic programming-based hot spot identification approach is proposed which provides efficient hot spot definitions for pedestrian crashes. The proposed approach is compared with the sliding window method and an intersection buffer-based approach. The results reveal that the dynamic programming method generates more hot spots with a higher number of crashes, while providing small hot spot segment lengths. In comparison, the sliding window method is shown to suffer from shortcomings due to a first-come-first-serve approach vis-à-vis hot spot identification and a fixed hot spot window length assumption. PMID:27209154
International Nuclear Information System (INIS)
This paper presents a novel and efficient approach through a hybrid integer coded differential evolution - dynamic programming (ICDEDP) scheme to solve the economic dispatch (ED) problem with multiple fuel options. A dynamic programming (DP) based simplified recursive algorithm is developed for optimal scheduling of the generating units in the ED problem. The proposed hybrid scheme is developed in such a way that an integer coded differential evolution (ICDE) is acting as a main optimizer to identify the optimal fuel options, and the DP is used to find the fitness of each agent in the population of the ICDE, which makes a quick decision to direct the search towards the optimal region. The hybrid ICDEDP decision vector consists of a sequence of integer numbers representing the fuel options of each unit to optimize quality of search and computation time. A gene swap operator is introduced in the proposed algorithm to improve its convergence characteristics. In order to show the efficiency and effectiveness, the proposed hybrid ICDEDP approach has been examined and tested with numerical results using the ten generation unit economic dispatch problem with multiple fuel options. The test result shows that the proposed hybrid ICDEDP algorithm has high quality solution, superior convergence characteristics and shorter computation time
Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing
Ono, Masahiro; Kuwata, Yoshiaki
2013-01-01
A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.
Jiang, Luan; Ling, Shan; Li, Qiang
2016-03-01
Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.
Dynamic programming-based hot spot identification approach for pedestrian crashes.
Medury, Aditya; Grembek, Offer
2016-08-01
Network screening techniques are widely used by state agencies to identify locations with high collision concentration, also referred to as hot spots. However, most of the research in this regard has focused on identifying highway segments that are of concern to automobile collisions. In comparison, pedestrian hot spot detection has typically focused on analyzing pedestrian crashes in specific locations, such as at/near intersections, mid-blocks, and/or other crossings, as opposed to long stretches of roadway. In this context, the efficiency of the some of the widely used network screening methods has not been tested. Hence, in order to address this issue, a dynamic programming-based hot spot identification approach is proposed which provides efficient hot spot definitions for pedestrian crashes. The proposed approach is compared with the sliding window method and an intersection buffer-based approach. The results reveal that the dynamic programming method generates more hot spots with a higher number of crashes, while providing small hot spot segment lengths. In comparison, the sliding window method is shown to suffer from shortcomings due to a first-come-first-serve approach vis-à-vis hot spot identification and a fixed hot spot window length assumption.
Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming
Institute of Scientific and Technical Information of China (English)
Ming BAI; Yan ZHUANG; Wei WANG
2009-01-01
An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points(GCPs) is presented.To decrease time complexity without losing matching precision,using a multilevel search scheme,the coarse matching is processed in typical disparity space image,while the fine matching is processed in disparity-offset space image.In the upper level,GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint.Under the supervision of the highly reliable GCPs,bidirec-tional dynamic programming framework is employed to solve the inconsistency in the optimization path.In the lower level,to reduce running time,disparity-offset space is proposed to efficiently achieve the dense disparity image.In addition,an adaptive dual support-weight strategy is presented to aggregate matching cost,which considers photometric and geomet-ric information.Further,post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm,where missing stereo information is substituted from surrounding re-gions.To demonstrate the effectiveness of the algorithm,we present the two groups of experimental results for four widely used standard stereo data sets,including discussion on performance and comparison with other methods,which show that the algorithm has not only a fast speed,but also significantly improves the efficiency of holistic optimization.
Energy Technology Data Exchange (ETDEWEB)
Chalasani, P.; Saias, I. [Los Alamos National Lab., NM (United States); Jha, S. [Carnegie Mellon Univ., Pittsburgh, PA (United States)
1996-04-08
As increasingly large volumes of sophisticated options (called derivative securities) are traded in world financial markets, determining a fair price for these options has become an important and difficult computational problem. Many valuation codes use the binomial pricing model, in which the stock price is driven by a random walk. In this model, the value of an n-period option on a stock is the expected time-discounted value of the future cash flow on an n-period stock price path. Path-dependent options are particularly difficult to value since the future cash flow depends on the entire stock price path rather than on just the final stock price. Currently such options are approximately priced by Monte carlo methods with error bounds that hold only with high probability and which are reduced by increasing the number of simulation runs. In this paper the authors show that pricing an arbitrary path-dependent option is {number_sign}-P hard. They show that certain types f path-dependent options can be valued exactly in polynomial time. Asian options are path-dependent options that are particularly hard to price, and for these they design deterministic polynomial-time approximate algorithms. They show that the value of a perpetual American put option (which can be computed in constant time) is in many cases a good approximation to the value of an otherwise identical n-period American put option. In contrast to Monte Carlo methods, the algorithms have guaranteed error bounds that are polynormally small (and in some cases exponentially small) in the maturity n. For the error analysis they derive large-deviation results for random walks that may be of independent interest.
Approximations to Euler's constant
International Nuclear Information System (INIS)
We study a problem of finding good approximations to Euler's constant γ=lim→∞ Sn, where Sn = Σk=Ln (1)/k-log(n+1), by linear forms in logarithms and harmonic numbers. In 1995, C. Elsner showed that slow convergence of the sequence Sn can be significantly improved if Sn is replaced by linear combinations of Sn with integer coefficients. In this paper, considering more general linear transformations of the sequence Sn we establish new accelerating convergence formulae for γ. Our estimates sharpen and generalize recent Elsner's, Rivoal's and author's results. (author)
Finite elements and approximation
Zienkiewicz, O C
2006-01-01
A powerful tool for the approximate solution of differential equations, the finite element is extensively used in industry and research. This book offers students of engineering and physics a comprehensive view of the principles involved, with numerous illustrative examples and exercises.Starting with continuum boundary value problems and the need for numerical discretization, the text examines finite difference methods, weighted residual methods in the context of continuous trial functions, and piecewise defined trial functions and the finite element method. Additional topics include higher o
Autonomous vehicle motion control, approximate maps, and fuzzy logic
Ruspini, Enrique H.
1993-01-01
Progress on research on the control of actions of autonomous mobile agents using fuzzy logic is presented. The innovations described encompass theoretical and applied developments. At the theoretical level, results of research leading to the combined utilization of conventional artificial planning techniques with fuzzy logic approaches for the control of local motion and perception actions are presented. Also formulations of dynamic programming approaches to optimal control in the context of the analysis of approximate models of the real world are examined. Also a new approach to goal conflict resolution that does not require specification of numerical values representing relative goal importance is reviewed. Applied developments include the introduction of the notion of approximate map. A fuzzy relational database structure for the representation of vague and imprecise information about the robot's environment is proposed. Also the central notions of control point and control structure are discussed.
Lattice quantum chromodynamics with approximately chiral fermions
Energy Technology Data Exchange (ETDEWEB)
Hierl, Dieter
2008-05-15
In this work we present Lattice QCD results obtained by approximately chiral fermions. We use the CI fermions in the quenched approximation to investigate the excited baryon spectrum and to search for the {theta}{sup +} pentaquark on the lattice. Furthermore we developed an algorithm for dynamical simulations using the FP action. Using FP fermions we calculate some LECs of chiral perturbation theory applying the epsilon expansion. (orig.)
Lattice quantum chromodynamics with approximately chiral fermions
International Nuclear Information System (INIS)
In this work we present Lattice QCD results obtained by approximately chiral fermions. We use the CI fermions in the quenched approximation to investigate the excited baryon spectrum and to search for the Θ+ pentaquark on the lattice. Furthermore we developed an algorithm for dynamical simulations using the FP action. Using FP fermions we calculate some LECs of chiral perturbation theory applying the epsilon expansion. (orig.)
Staying Thermal with Hartree Ensemble Approximations
Salle, M; Vink, Jeroen C
2000-01-01
Using Hartree ensemble approximations to compute the real time dynamics of scalar fields in 1+1 dimension, we find that with suitable initial conditions, approximate thermalization is achieved much faster than found in our previous work. At large times, depending on the interaction strength and temperature, the particle distribution slowly changes: the Bose-Einstein distribution of the particle densities develops classical features. We also discuss variations of our method which are numerically more efficient.
The Compact Approximation Property does not imply the Approximation Property
Willis, George A.
1992-01-01
It is shown how to construct, given a Banach space which does not have the approximation property, another Banach space which does not have the approximation property but which does have the compact approximation property.
Approximating metal-insulator transitions
Danieli, Carlo; Rayanov, Kristian; Pavlov, Boris; Martin, Gaven; Flach, Sergej
2015-12-01
We consider quantum wave propagation in one-dimensional quasiperiodic lattices. We propose an iterative construction of quasiperiodic potentials from sequences of potentials with increasing spatial period. At each finite iteration step, the eigenstates reflect the properties of the limiting quasiperiodic potential properties up to a controlled maximum system size. We then observe approximate Metal-Insulator Transitions (MIT) at the finite iteration steps. We also report evidence on mobility edges, which are at variance to the celebrated Aubry-André model. The dynamics near the MIT shows a critical slowing down of the ballistic group velocity in the metallic phase, similar to the divergence of the localization length in the insulating phase.
Wavelet Approximation in Data Assimilation
Tangborn, Andrew; Atlas, Robert (Technical Monitor)
2002-01-01
Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.
Bade, W. L.; Yos, J. M.
1975-01-01
A computer program for calculating quasi-one-dimensional gas flow in axisymmetric and two-dimensional nozzles and rectangular channels is presented. Flow is assumed to start from a state of thermochemical equilibrium at a high temperature in an upstream reservoir. The program provides solutions based on frozen chemistry, chemical equilibrium, and nonequilibrium flow with finite reaction rates. Electronic nonequilibrium effects can be included using a two-temperature model. An approximate laminar boundary layer calculation is given for the shear and heat flux on the nozzle wall. Boundary layer displacement effects on the inviscid flow are considered also. Chemical equilibrium and transport property calculations are provided by subroutines. The code contains precoded thermochemical, chemical kinetic, and transport cross section data for high-temperature air, CO2-N2-Ar mixtures, helium, and argon. It provides calculations of the stagnation conditions on axisymmetric or two-dimensional models, and of the conditions on the flat surface of a blunt wedge. The primary purpose of the code is to describe the flow conditions and test conditions in electric arc heated wind tunnels.
Approximate Bayesian inference for complex ecosystems
Michael P H Stumpf
2014-01-01
Mathematical models have been central to ecology for nearly a century. Simple models of population dynamics have allowed us to understand fundamental aspects underlying the dynamics and stability of ecological systems. What has remained a challenge, however, is to meaningfully interpret experimental or observational data in light of mathematical models. Here, we review recent developments, notably in the growing field of approximate Bayesian computation (ABC), that allow us to calibrate mathe...
Dual Control for Approximate Bayesian Reinforcement Learning
Klenske, Edgar D.; Hennig, Philipp
2015-01-01
Control of non-episodic, finite-horizon dynamical systems with uncertain dynamics poses a tough and elementary case of the exploration-exploitation trade-off. Bayesian reinforcement learning, reasoning about the effect of actions and future observations, offers a principled solution, but is intractable. We review, then extend an old approximate approach from control theory---where the problem is known as dual control---in the context of modern regression methods, specifically generalized line...
Time Stamps for Fixed-Point Approximation
DEFF Research Database (Denmark)
Damian, Daniela
2001-01-01
Time stamps were introduced in Shivers's PhD thesis for approximating the result of a control-flow analysis. We show them to be suitable for computing program analyses where the space of results (e.g., control-flow graphs) is large. We formalize time-stamping as a top-down, fixed......-point approximation algorithm which maintains a single copy of intermediate results. We then prove the correctness of this algorithm....
Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement
Srinivas, Niranjan
Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry. In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive. Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for
Dynamic programming for infinite horizon boundary control problems of PDE's with age structure
Faggian, Silvia
2008-01-01
We develop the dynamic programming approach for a family of infinite horizon boundary control problems with linear state equation and convex cost. We prove that the value function of the problem is the unique regular solution of the associated stationary Hamilton--Jacobi--Bellman equation and use this to prove existence and uniqueness of feedback controls. The idea of studying this kind of problem comes from economic applications, in particular from models of optimal investment with vintage capital. Such family of problems has already been studied in the finite horizon case by Faggian. The infinite horizon case is more difficult to treat and it is more interesting from the point of view of economic applications, where what mainly matters is the behavior of optimal trajectories and controls in the long run. The study of infinite horizon is here performed through a nontrivial limiting procedure from the corresponding finite horizon problem.
Chang, Ching-Chun; Liu, Yanjun; Nguyen, Son T.
2015-03-01
Data hiding is a technique that embeds information into digital cover data. This technique has been concentrated on the spatial uncompressed domain, and it is considered more challenging to perform in the compressed domain, i.e., vector quantization, JPEG, and block truncation coding (BTC). In this paper, we propose a new data hiding scheme for BTC-compressed images. In the proposed scheme, a dynamic programming strategy was used to search for the optimal solution of the bijective mapping function for LSB substitution. Then, according to the optimal solution, each mean value embeds three secret bits to obtain high hiding capacity with low distortion. The experimental results indicated that the proposed scheme obtained both higher hiding capacity and hiding efficiency than the other four existing schemes, while ensuring good visual quality of the stego-image. In addition, the proposed scheme achieved a low bit rate as original BTC algorithm.
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
Energy Technology Data Exchange (ETDEWEB)
Bokanowski, Olivier, E-mail: boka@math.jussieu.fr [Laboratoire Jacques-Louis Lions, Université Paris-Diderot (Paris 7) UFR de Mathématiques - Bât. Sophie Germain (France); Picarelli, Athena, E-mail: athena.picarelli@inria.fr [Projet Commands, INRIA Saclay & ENSTA ParisTech (France); Zidani, Hasnaa, E-mail: hasnaa.zidani@ensta.fr [Unité de Mathématiques appliquées (UMA), ENSTA ParisTech (France)
2015-02-15
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.
Directory of Open Access Journals (Sweden)
Zongyuan Huang
2010-01-01
Full Text Available This paper is concerned with a kind of corporate international optimal portfolio and consumption choice problems, in which the investor can invest her or his wealth either in a domestic bond (bank account or in an oversea real project with production. The bank pays a lower interest rate for deposit and takes a higher rate for any loan. First, we show that Bellman's dynamic programming principle still holds in our setting; second, in terms of the foregoing principle, we obtain the investor's optimal portfolio proportion for a general maximizing expected utility problem and give the corresponding economic analysis; third, for the special but nontrivial Constant Relative Risk Aversion (CRRA case, we get the investors optimal investment and consumption solution; last but not least, we give some numerical simulation results to illustrate the influence of volatility parameters on the optimal investment strategy.
Dynamic Programming for Re-Mapping Noisy Fixations in Translation Tasks
DEFF Research Database (Denmark)
Carl, Michael
2013-01-01
drifted center of the observed fixation onto the symbol directly below it. In this paper I extend this naïve fixation-to-symbol mapping by introducing background knowledge about the translation task. In a first step, the sequence of fixation-to- symbol mappings is extended into a lattice of several...... possible fixated symbols, including those on the line above and below the naïve fixation mapping. In a second step a dynamic programming algorithm applies a number of heuristics to find the best path through the lattice, based on the probable distance in characters, in words and in pixels between...... successive fixations and the symbol locations, so as to smooth the gazing path according to the background gazing model. A qualitative and quantitative evaluation shows that the algorithm increases the accuracy of the re-mapped symbol sequence....
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Rauff Lind Christensen, Tue; Klose, Andreas; Andersen, Kim Allan
The Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem (SSFCMCTP) is a problem with versatile applications. This problem is a generalization of the Single-Sink, Fixed-Charge Transportation Problem (SSFCTP), which has a fixed-charge, linear cost structure. However, in at least two...... important aspects of supplier selection, an important application of the SSFCTP, this does not reflect the real life situation. First, transportation costs faced by many companies are in fact piecewise linear. Secondly, when suppliers offer discounts, either incremental or all-unit discounts, such savings...... are neglected in the SSFCTP. The SSFCMCTP overcome this problem by incorporating a staircase cost structure in the cost function instead of the usual one used in SSFCTP. We present a dynamic programming algorithm for the resulting problem. To enhance the performance of the generic algorithm a number...
Directory of Open Access Journals (Sweden)
Diamantidis A. C.
2004-01-01
Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.
Parameter Matching Analysis of Hydraulic Hybrid Excavators Based on Dynamic Programming Algorithm
Directory of Open Access Journals (Sweden)
Wei Shen
2013-01-01
Full Text Available In order to meet the energy saving requirement of the excavator, hybrid excavators are becoming the hot spot for researchers. The initial problem is to match the parameter of each component, because the system is tending to be more complicated due to the introduction of the accumulator. In this paper, firstly, a new architecture is presented which is hydraulic hybrid excavator based on common pressure rail combined switched function (HHES. Secondly, the general principle of dynamic programming algorithm (DPA is explained. Then, the method by using DPA for parameter matching of HHES is described in detail. Furthermore, the DPA is translated into the M language for simulation. Finally, the calculation results are analyzed, and the optimal matching group is obtained.
GUI Based Computer Programs for Analyzing Dynamic Signals Detected from a Physical Earthquake Model
Directory of Open Access Journals (Sweden)
Chung-Ru Wang
2013-06-01
Full Text Available Many methods are available to be used as tools for data analysis, such as Fast Fourier Transform (FFT and Hilbert Huang Transform (HHT. However, the raw data need to be pre-processed before applying those methods. To deal with considerable raw data, it should be processed in a fast and efficient way. In this research, the dynamic signal data are obtained from physical earthquake models. To process the huge amount of data is always complicated and time consuming. Customized GUI programs to pre-process and post-process data has been designed to make the raw signal data express its physical meaning rapid by a combination of the manual and automatic process. The research uses animations to display the signal change in time that the signal detected can be shown by a graph which is close to physical phenomena and makes the physical data meaning become more obvious.
Q Value-Based Dynamic Programming with Boltzmann Distribution in Large Scale Road Network
Yu, Shanqing; Xu, Yelei; Mabu, Shingo; Mainali, Manoj Kanta; Shimada, Kaoru; Hirasawa, Kotaro
In this paper, a global optimal traffic assignment strategy, i.e., Q value-based Dynamic Programming with Boltzmann Distribution is applied to the Kitakyushu City traffic system. The main idea of the proposed traffic assignment strategy is to calculate the expected traveling time for each origin-destination pair and the probability of selecting the next section, then to generate a considerable number of route candidates for the drivers based on the calculated probability. In the simulation, how to select the temperature parameter and the number of the route candidates is discussed in detail. The comparison between the proposed method and the shortest path algorithms indicates that the proposed method could reduce the risk of the traffic congestion occurrence and save the traveling cost effectively. In addition, the computation time is given to reveal the feasibility of the proposed method in large scale networks.
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.
Gosavi, Abhijit
2014-08-01
In control systems theory, the Markov decision process (MDP) is a widely used optimization model involving selection of the optimal action in each state visited by a discrete-event system driven by Markov chains. The classical MDP model is suitable for an agent/decision-maker interested in maximizing expected revenues, but does not account for minimizing variability in the revenues. An MDP model in which the agent can maximize the revenues while simultaneously controlling the variance in the revenues is proposed. This work is rooted in machine learning/neural network concepts, where updating is based on system feedback and step sizes. First, a Bellman equation for the problem is proposed. Thereafter, convergent dynamic programming and reinforcement learning techniques for solving the MDP are provided along with encouraging numerical results on a small MDP and a preventive maintenance problem.
Noninvasive fetal QRS detection using an echo state network and dynamic programming.
Lukoševičius, Mantas; Marozas, Vaidotas
2014-08-01
We address a classical fetal QRS detection problem from abdominal ECG recordings with a data-driven statistical machine learning approach. Our goal is to have a powerful, yet conceptually clean, solution. There are two novel key components at the heart of our approach: an echo state recurrent neural network that is trained to indicate fetal QRS complexes, and several increasingly sophisticated versions of statistics-based dynamic programming algorithms, which are derived from and rooted in probability theory. We also employ a standard technique for preprocessing and removing maternal ECG complexes from the signals, but do not take this as the main focus of this work. The proposed approach is quite generic and can be extended to other types of signals and annotations. Open-source code is provided. PMID:25069892
Dynamic Programming Optimization of Multi-rate Multicast Video-Streaming Services
Directory of Open Access Journals (Sweden)
Nestor Michael Caños Tiglao
2010-06-01
Full Text Available In large scale IP Television (IPTV and Mobile TV distributions, the video signal is typically encoded and transmitted using several quality streams, over IP Multicast channels, to several groups of receivers, which are classified in terms of their reception rate. As the number of video streams is usually constrained by both the number of TV channels and the maximum capacity of the content distribution network, it is necessary to find the selection of video stream transmission rates that maximizes the overall user satisfaction. In order to efficiently solve this problem, this paper proposes the Dynamic Programming Multi-rate Optimization (DPMO algorithm. The latter was comparatively evaluated considering several user distributions, featuring different access rate patterns. The experimental results reveal that DPMO is significantly more efficient than exhaustive search, while presenting slightly higher execution times than the non-optimal Multi-rate Step Search (MSS algorithm.
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xingguo;
2015-01-01
Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth......-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water...... quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen...
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
International Nuclear Information System (INIS)
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach
Stochastic Dynamic Programming for Three-Echelon Inventory System of Limited Shelf Life Products
Directory of Open Access Journals (Sweden)
Galal Noha M.
2016-01-01
Full Text Available Coordination of inventory decisions within the supply chain is one of the major determinants of its competitiveness in the global market. Products with limited shelf life impose additional challenges in managing the inventory across the supply chain because of the additional wastage costs incurred in case of being stored beyond product’s useful life. This paper presents a stochastic dynamic programming model for inventory replenishment in a serial multi-echelon distribution supply chain. The model considers uncertain stationary discrete demand at the retailer and zero lead time. The objective is to minimize expected total costs across the supply chain echelons, while maintaining a preset service level. The results illustrate that a cost saving of around 17% is achievable due to coordinating inventory decisions across the supply chain.
A working-set framework for sequential convex approximation methods
DEFF Research Database (Denmark)
Stolpe, Mathias
2008-01-01
We present an active-set algorithmic framework intended as an extension to existing implementations of sequential convex approximation methods for solving nonlinear inequality constrained programs. The framework is independent of the choice of approximations and the stabilization technique used...
Interacting boson approximation
International Nuclear Information System (INIS)
Lectures notes on the Interacting Boson Approximation are given. Topics include: angular momentum tensors; properties of T/sub i//sup (n)/ matrices; T/sub i//sup (n)/ matrices as Clebsch-Gordan coefficients; construction of higher rank tensors; normalization: trace of products of two s-rank tensors; completeness relation; algebra of U(N); eigenvalue of the quadratic Casimir operator for U(3); general result for U(N); angular momentum content of U(3) representation; p-Boson model; Hamiltonian; quadrupole transitions; S,P Boson model; expectation value of dipole operator; S-D model: U(6); quadratic Casimir operator; an O(5) subgroup; an O(6) subgroup; properties of O(5) representations; quadratic Casimir operator; quadratic Casimir operator for U(6); decomposition via SU(5) chain; a special O(3) decomposition of SU(3); useful identities; a useful property of D/sub αβγ/(α,β,γ = 4-8) as coupling coefficients; explicit construction of T/sub x//sup (2)/ and d/sub αβγ/; D-coefficients; eigenstates of T3; and summary of T = 2 states
Prestack traveltime approximations
Alkhalifah, Tariq Ali
2012-05-01
Many of the explicit prestack traveltime relations used in practice are based on homogeneous (or semi-homogenous, possibly effective) media approximations. This includes the multifocusing, based on the double square-root (DSR) equation, and the common reflection stack (CRS) approaches. Using the DSR equation, I constructed the associated eikonal form in the general source-receiver domain. Like its wave-equation counterpart, it suffers from a critical singularity for horizontally traveling waves. As a result, I recasted the eikonal in terms of the reflection angle, and thus, derived expansion based solutions of this eikonal in terms of the difference between the source and receiver velocities in a generally inhomogenous background medium. The zero-order term solution, corresponding to ignoring the lateral velocity variation in estimating the prestack part, is free of singularities and can be used to estimate traveltimes for small to moderate offsets (or reflection angles) in a generally inhomogeneous medium. The higher-order terms include limitations for horizontally traveling waves, however, we can readily enforce stability constraints to avoid such singularities. In fact, another expansion over reflection angle can help us avoid these singularities by requiring the source and receiver velocities to be different. On the other hand, expansions in terms of reflection angles result in singularity free equations. For a homogenous background medium, as a test, the solutions are reasonably accurate to large reflection and dip angles. A Marmousi example demonstrated the usefulness and versatility of the formulation. © 2012 Society of Exploration Geophysicists.
Gupta, Deepak K; Fonck, Raymond R
2008-01-01
A new time-delay estimation (TDE) technique based on dynamic programming is developed, to measures the time-varying time-delay between two signals. Dynamic programming based TDE technique provides a frequency response 5 to 10 times higher than previously known TDE techniques, namely those based on time-lag cross-correlation or wavelet analysis. Effects of frequency spectrum, signal-to-noise ratio and amplitude of time-delay on response (represented as transfer function) of TDE technique is studied using simulated data signals. Transfer function for the technique decreases with increase in noise in signal; however it is independent of signal spectrum shape. Dynamic programming based TDE technique is applied to the Beam-Emission-Spectroscopy (BES) diagnostic data to measure poloidal velocity fluctuations, which led to the observation of theoretically predicted zonal flows in high-temperature tokamak plasmas.
Dynamic programming based time-delay estimation technique for analysis of time-varying time-delay
International Nuclear Information System (INIS)
A new time-delay estimation (TDE) technique based on dynamic programming is developed to measure the time-varying time-delay between two signals. The dynamic programming based TDE technique provides a frequency response five to ten times better than previously known TDE techniques, namely, those based on time-lag cross-correlation or wavelet analysis. Effects of frequency spectrum, signal-to-noise ratio, and amplitude of time-delay on response of the TDE technique (represented as transfer function) are studied using simulated data signals. The transfer function for the technique decreases with increase in noise in signal; however it is independent of signal spectrum shape. The dynamic programming based TDE technique is applied to the beam emission spectroscopy diagnostic data to measure poloidal velocity fluctuations, which led to the observation of theoretically predicted zonal flows in high-temperature tokamak plasmas.
A Fuzzy Programming approach for formation of Virtual Cells under dynamic and uncertain conditions
Directory of Open Access Journals (Sweden)
R.Jayachitra,
2010-06-01
Full Text Available Inspired by principles and advantages of the group technology (GT philosophy, part family formation for a virtual Cellular Manufacturing System (VCMS using Fuzzy logic is designed for dynamic and uncertain conditions. In real manufacturing systems, the input parameters such as part demand and the capacity are fuzzy in nature. In such cases, the fluctuations in part demand and the availability of manufacturing facilities in each period can be regarded as fuzzy. In a dynamic environment, the planning horizon can be divided into smaller time periods where each period and/or each part has different product mix and demand. A mathematical model for virtual cellular manufacturing system as binary-integer programming is proposed to minimize the total costs consisting of fixed machine costs, variable costs of all machines and the logical group movement costs. To verify the behavior of the proposed model, a comprehensive example is solved by a branch- and-bound (B&B method with the LINGO 12.0 software and the virtual cells(VC are formed by defuzzification using maximizing decision level λ (lambda-cut and the computational results are reported and compared with simulated annealing algorithm and rank order clustering algorithm .
Sabar, Nasser R; Ayob, Masri; Kendall, Graham; Qu, Rong
2015-02-01
Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a dynamic multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite. PMID:24951713
Li, Zhanjie; Zhang, Peipei; Lv, Jinyang; Cheng, Yufeng; Cui, Jianmin; Zhao, Huixian; Hu, Shengwu
2016-01-01
Rapeseed (Brassica napus L.) is an important oil crop worldwide and exhibits significant heterosis. Effective pollination control systems, which are closely linked to anther development, are a prerequisite for utilizing heterosis. The anther, which is the male organ in flowering plants, undergoes many metabolic processes during development. Although the gene expression patterns underlying pollen development are well studied in model plant Arabidopsis, the regulatory networks of genome-wide gene expression during rapeseed anther development is poorly understood, especially regarding metabolic regulations. In this study, we systematically analyzed metabolic processes occurring during anther development in rapeseed using ultrastructural observation and global transcriptome analysis. Anther ultrastructure exhibited that numerous cellular organelles abundant with metabolic materials, such as elaioplast, tapetosomes, plastids (containing starch deposits) etc. appeared, accompanied with anther structural alterations during anther development, suggesting many metabolic processes occurring. Global transcriptome analysis revealed dynamic changes in gene expression during anther development that corresponded to dynamic functional alterations between early and late anther developmental stages. The early stage anthers preferentially expressed genes involved in lipid metabolism that are related to pollen extine formation as well as elaioplast and tapetosome biosynthesis, whereas the late stage anthers expressed genes associated with carbohydrate metabolism to form pollen intine and to accumulate starch in mature pollen grains. Finally, a predictive gene regulatory module responsible for early pollen extine formation was generated. Taken together, this analysis provides a comprehensive understanding of dynamic gene expression programming of metabolic processes in the rapeseed anther, especially with respect to lipid and carbohydrate metabolism during pollen development. PMID
Li, Zhanjie; Zhang, Peipei; Lv, Jinyang; Cheng, Yufeng; Cui, Jianmin; Zhao, Huixian; Hu, Shengwu
2016-01-01
Rapeseed (Brassica napus L.) is an important oil crop worldwide and exhibits significant heterosis. Effective pollination control systems, which are closely linked to anther development, are a prerequisite for utilizing heterosis. The anther, which is the male organ in flowering plants, undergoes many metabolic processes during development. Although the gene expression patterns underlying pollen development are well studied in model plant Arabidopsis, the regulatory networks of genome-wide gene expression during rapeseed anther development is poorly understood, especially regarding metabolic regulations. In this study, we systematically analyzed metabolic processes occurring during anther development in rapeseed using ultrastructural observation and global transcriptome analysis. Anther ultrastructure exhibited that numerous cellular organelles abundant with metabolic materials, such as elaioplast, tapetosomes, plastids (containing starch deposits) etc. appeared, accompanied with anther structural alterations during anther development, suggesting many metabolic processes occurring. Global transcriptome analysis revealed dynamic changes in gene expression during anther development that corresponded to dynamic functional alterations between early and late anther developmental stages. The early stage anthers preferentially expressed genes involved in lipid metabolism that are related to pollen extine formation as well as elaioplast and tapetosome biosynthesis, whereas the late stage anthers expressed genes associated with carbohydrate metabolism to form pollen intine and to accumulate starch in mature pollen grains. Finally, a predictive gene regulatory module responsible for early pollen extine formation was generated. Taken together, this analysis provides a comprehensive understanding of dynamic gene expression programming of metabolic processes in the rapeseed anther, especially with respect to lipid and carbohydrate metabolism during pollen development. PMID
Huei Peng; Sun Fengchun; Zou Yuan; Liu Teng
2013-01-01
This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT). A control-oriented model of the powertrain and vehicle dynamics is built first. The energy management is formulated as a typical optimal control problem to trade off the fuel consumption and gear shifting frequency under admissible constraints. The Dynamic Programming (DP) and Pontryagin’s Minimum Principle (PMP) are applied to obtain the optimal soluti...
Ximing Wang; Hongwen He; Fengchun Sun; Jieli Zhang
2015-01-01
To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the op...
A dynamic food-chain model and program for predicting the consequences of nuclear accident
Institute of Scientific and Technical Information of China (English)
1998-01-01
A dynamic food-chain model and program, DYFOM-95, forpredicting the radiological consequences of nuclear accident hasbeen developed, which is not only suitable to the West food-chainbut also to Chinese food chain. The following processes, caused byaccident release which will make an impact on radionuclideconcentration in the edible parts of vegetable are considered: dryand wet deposition interception and initial retention,translocation, percolation, root uptake and tillage. Activityintake rate of animals, effects of processing and activity intakeof human through ingestion pathway are also considered incalculations. The effects of leaf area index LAI of vegetable areconsidered in dry deposition model. A method for calculating thecontribution of rain with different period and different intensityto total wet deposition is established. The program contains 1 maincode and 5 sub-codes to calculate dry and wet deposition on surfaceof vegetable and soil, translocation of nuclides in vegetable,nuclide concentration in the edible parts of vegetable and inanimal products and activity intake of human and so on.