Structured analysis and modeling of complex systems

Science.gov (United States)

Strome, David R.; Dalrymple, Mathieu A.

1992-01-01

The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.

Systems Engineering Metrics: Organizational Complexity and Product Quality Modeling

Science.gov (United States)

Mog, Robert A.

1997-01-01

Innovative organizational complexity and product quality models applicable to performance metrics for NASA-MSFC's Systems Analysis and Integration Laboratory (SAIL) missions and objectives are presented. An intensive research effort focuses on the synergistic combination of stochastic process modeling, nodal and spatial decomposition techniques, organizational and computational complexity, systems science and metrics, chaos, and proprietary statistical tools for accelerated risk assessment. This is followed by the development of a preliminary model, which is uniquely applicable and robust for quantitative purposes. Exercise of the preliminary model using a generic system hierarchy and the AXAF-I architectural hierarchy is provided. The Kendall test for positive dependence provides an initial verification and validation of the model. Finally, the research and development of the innovation is revisited, prior to peer review. This research and development effort results in near-term, measurable SAIL organizational and product quality methodologies, enhanced organizational risk assessment and evolutionary modeling results, and 91 improved statistical quantification of SAIL productivity interests.

Socio-Environmental Resilience and Complex Urban Systems Modeling

Science.gov (United States)

Deal, Brian; Petri, Aaron; Pan, Haozhi; Goldenberg, Romain; Kalantari, Zahra; Cvetkovic, Vladimir

2017-04-01

The increasing pressure of climate change has inspired two normative agendas; socio-technical transitions and socio-ecological resilience, both sharing a complex-systems epistemology (Gillard et al. 2016). Socio-technical solutions include a continuous, massive data gathering exercise now underway in urban places under the guise of developing a 'smart'(er) city. This has led to the creation of data-rich environments where large data sets have become central to monitoring and forming a response to anomalies. Some have argued that these kinds of data sets can help in planning for resilient cities (Norberg and Cumming 2008; Batty 2013). In this paper, we focus on a more nuanced, ecologically based, socio-environmental perspective of resilience planning that is often given less consideration. Here, we broadly discuss (and model) the tightly linked, mutually influenced, social and biophysical subsystems that are critical for understanding urban resilience. We argue for the need to incorporate these sub system linkages into the resilience planning lexicon through the integration of systems models and planning support systems. We make our case by first providing a context for urban resilience from a socio-ecological and planning perspective. We highlight the data needs for this type of resilient planning and compare it to currently collected data streams in various smart city efforts. This helps to define an approach for operationalizing socio-environmental resilience planning using robust systems models and planning support systems. For this, we draw from our experiences in coupling a spatio-temporal land use model (the Landuse Evolution and impact Assessment Model (LEAM)) with water quality and quantity models in Stockholm Sweden. We describe the coupling of these systems models using a robust Planning Support System (PSS) structural framework. We use the coupled model simulations and PSS to analyze the connection between urban land use transformation (social) and water

Model-based safety architecture framework for complex systems

NARCIS (Netherlands)

Schuitemaker, Katja; Rajabali Nejad, Mohammadreza; Braakhuis, J.G.; Podofillini, Luca; Sudret, Bruno; Stojadinovic, Bozidar; Zio, Enrico; Kröger, Wolfgang

2015-01-01

The shift to transparency and rising need of the general public for safety, together with the increasing complexity and interdisciplinarity of modern safety-critical Systems of Systems (SoS) have resulted in a Model-Based Safety Architecture Framework (MBSAF) for capturing and sharing architectural

On sampling and modeling complex systems

International Nuclear Information System (INIS)

Marsili, Matteo; Mastromatteo, Iacopo; Roudi, Yasser

2013-01-01

The study of complex systems is limited by the fact that only a few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the system behavior. In addition, empirical data typically undersample the space of possible states. We study a generic framework where a complex system is seen as a system of many interacting degrees of freedom, which are known only in part, that optimize a given function. We show that the underlying distribution with respect to the known variables has the Boltzmann form, with a temperature that depends on the number of unknown variables. In particular, when the influence of the unknown degrees of freedom on the known variables is not too irregular, the temperature decreases as the number of variables increases. This suggests that models can be predictable only when the number of relevant variables is less than a critical threshold. Concerning sampling, we argue that the information that a sample contains on the behavior of the system is quantified by the entropy of the frequency with which different states occur. This allows us to characterize the properties of maximally informative samples: within a simple approximation, the most informative frequency size distributions have power law behavior and Zipf’s law emerges at the crossover between the under sampled regime and the regime where the sample contains enough statistics to make inferences on the behavior of the system. These ideas are illustrated in some applications, showing that they can be used to identify relevant variables or to select the most informative representations of data, e.g. in data clustering. (paper)

Nostradamus 2014 prediction, modeling and analysis of complex systems

CERN Document Server

Suganthan, Ponnuthurai; Chen, Guanrong; Snasel, Vaclav; Abraham, Ajith; Rössler, Otto

2014-01-01

The prediction of behavior of complex systems, analysis and modeling of its structure is a vitally important problem in engineering, economy and generally in science today. Examples of such systems can be seen in the world around us (including our bodies) and of course in almost every scientific discipline including such “exotic” domains as the earth’s atmosphere, turbulent fluids, economics (exchange rate and stock markets), population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such complex dynamics, which often exhibit strange behavior, and to use it in research or industrial applications, it is paramount to create its models. For this purpose there exists a rich spectrum of methods, from classical such as ARMA models or Box Jenkins method to modern ones like evolutionary computation, neural networks, fuzzy logic, geometry, deterministic chaos amongst others. This proceedings book is a collection of accepted ...

Advances in dynamic network modeling in complex transportation systems

CERN Document Server

Ukkusuri, Satish V

2013-01-01

This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.

Science.gov (United States)

Transtrum, Mark K; Qiu, Peng

2016-05-01

The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.

FRAM Modelling Complex Socio-technical Systems

CERN Document Server

Hollnagel, Erik

2012-01-01

There has not yet been a comprehensive method that goes behind 'human error' and beyond the failure concept, and various complicated accidents have accentuated the need for it. The Functional Resonance Analysis Method (FRAM) fulfils that need. This book presents a detailed and tested method that can be used to model how complex and dynamic socio-technical systems work, and understand both why things sometimes go wrong but also why they normally succeed.

New approaches in agent-based modeling of complex financial systems

Science.gov (United States)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

System Testability Analysis for Complex Electronic Devices Based on Multisignal Model

International Nuclear Information System (INIS)

Long, B; Tian, S L; Huang, J G

2006-01-01

It is necessary to consider the system testability problems for electronic devices during their early design phase because modern electronic devices become smaller and more compositive while their function and structure are more complex. Multisignal model, combining advantage of structure model and dependency model, is used to describe the fault dependency relationship for the complex electronic devices, and the main testability indexes (including optimal test program, fault detection rate, fault isolation rate, etc.) to evaluate testability and corresponding algorithms are given. The system testability analysis process is illustrated for USB-GPIB interface circuit with TEAMS toolbox. The experiment results show that the modelling method is simple, the computation speed is rapid and this method has important significance to improve diagnostic capability for complex electronic devices

Capturing complexity in work disability research: application of system dynamics modeling methodology.

Science.gov (United States)

Jetha, Arif; Pransky, Glenn; Hettinger, Lawrence J

2016-01-01

Work disability (WD) is characterized by variable and occasionally undesirable outcomes. The underlying determinants of WD outcomes include patterns of dynamic relationships among health, personal, organizational and regulatory factors that have been challenging to characterize, and inadequately represented by contemporary WD models. System dynamics modeling (SDM) methodology applies a sociotechnical systems thinking lens to view WD systems as comprising a range of influential factors linked by feedback relationships. SDM can potentially overcome limitations in contemporary WD models by uncovering causal feedback relationships, and conceptualizing dynamic system behaviors. It employs a collaborative and stakeholder-based model building methodology to create a visual depiction of the system as a whole. SDM can also enable researchers to run dynamic simulations to provide evidence of anticipated or unanticipated outcomes that could result from policy and programmatic intervention. SDM may advance rehabilitation research by providing greater insights into the structure and dynamics of WD systems while helping to understand inherent complexity. Challenges related to data availability, determining validity, and the extensive time and technical skill requirements for model building may limit SDM's use in the field and should be considered. Contemporary work disability (WD) models provide limited insight into complexity associated with WD processes. System dynamics modeling (SDM) has the potential to capture complexity through a stakeholder-based approach that generates a simulation model consisting of multiple feedback loops. SDM may enable WD researchers and practitioners to understand the structure and behavior of the WD system as a whole, and inform development of improved strategies to manage straightforward and complex WD cases.

Semiotic aspects of control and modeling relations in complex systems

Energy Technology Data Exchange (ETDEWEB)

Joslyn, C.

1996-08-01

A conceptual analysis of the semiotic nature of control is provided with the goal of elucidating its nature in complex systems. Control is identified as a canonical form of semiotic relation of a system to its environment. As a form of constraint between a system and its environment, its necessary and sufficient conditions are established, and the stabilities resulting from control are distinguished from other forms of stability. These result from the presence of semantic coding relations, and thus the class of control systems is hypothesized to be equivalent to that of semiotic systems. Control systems are contrasted with models, which, while they have the same measurement functions as control systems, do not necessarily require semantic relations because of the lack of the requirement of an interpreter. A hybrid construction of models in control systems is detailed. Towards the goal of considering the nature of control in complex systems, the possible relations among collections of control systems are considered. Powers arguments on conflict among control systems and the possible nature of control in social systems are reviewed, and reconsidered based on our observations about hierarchical control. Finally, we discuss the necessary semantic functions which must be present in complex systems for control in this sense to be present at all.

MATHEMATICAL MODELS OF PROCESSES AND SYSTEMS OF TECHNICAL OPERATION FOR ONBOARD COMPLEXES AND FUNCTIONAL SYSTEMS OF AVIONICS

Directory of Open Access Journals (Sweden)

Sergey Viktorovich Kuznetsov

2017-01-01

Full Text Available Modern aircraft are equipped with complicated systems and complexes of avionics. Aircraft and its avionics tech- nical operation process is observed as a process with changing of operation states. Mathematical models of avionics pro- cesses and systems of technical operation are represented as Markov chains, Markov and semi-Markov processes. The pur- pose is to develop the graph-models of avionics technical operation processes, describing their work in flight, as well as during maintenance on the ground in the various systems of technical operation. The graph-models of processes and sys- tems of on-board complexes and functional avionics systems in flight are proposed. They are based on the state tables. The models are specified for the various technical operation systems: the system with control of the reliability level, the system with parameters control and the system with resource control. The events, which cause the avionics complexes and func- tional systems change their technical state, are failures and faults of built-in test equipment. Avionics system of technical operation with reliability level control is applicable for objects with constant or slowly varying in time failure rate. Avion- ics system of technical operation with resource control is mainly used for objects with increasing over time failure rate. Avionics system of technical operation with parameters control is used for objects with increasing over time failure rate and with generalized parameters, which can provide forecasting and assign the borders of before-fail technical states. The pro- posed formal graphical approach avionics complexes and systems models designing is the basis for models and complex systems and facilities construction, both for a single aircraft and for an airline aircraft fleet, or even for the entire aircraft fleet of some specific type. The ultimate graph-models for avionics in various systems of technical operation permit the beginning of

Bourbaki's structure theory in the problem of complex systems simulation models synthesis and model-oriented programming

Science.gov (United States)

Brodsky, Yu. I.

2015-01-01

The work is devoted to the application of Bourbaki's structure theory to substantiate the synthesis of simulation models of complex multicomponent systems, where every component may be a complex system itself. An application of the Bourbaki's structure theory offers a new approach to the design and computer implementation of simulation models of complex multicomponent systems—model synthesis and model-oriented programming. It differs from the traditional object-oriented approach. The central concept of this new approach and at the same time, the basic building block for the construction of more complex structures is the concept of models-components. A model-component endowed with a more complicated structure than, for example, the object in the object-oriented analysis. This structure provides to the model-component an independent behavior-the ability of standard responds to standard requests of its internal and external environment. At the same time, the computer implementation of model-component's behavior is invariant under the integration of models-components into complexes. This fact allows one firstly to construct fractal models of any complexity, and secondly to implement a computational process of such constructions uniformly-by a single universal program. In addition, the proposed paradigm allows one to exclude imperative programming and to generate computer code with a high degree of parallelism.

Agent-Based and Macroscopic Modeling of the Complex Socio-Economic Systems

Directory of Open Access Journals (Sweden)

Aleksejus Kononovičius

2013-08-01

Full Text Available Purpose – The focus of this contribution is the correspondence between collective behavior and inter-individual interactions in the complex socio-economic systems. Currently there is a wide selection of papers proposing various models for the both collective behavior and inter-individual interactions in the complex socio-economic systems. Yet the papers directly relating these two concepts are still quite rare. By studying this correspondence we discuss a cutting edge approach to the modeling of complex socio-economic systems. Design/methodology/approach – The collective behavior is often modeled using stochastic and ordinary calculus, while the inter-individual interactions are modeled using agent-based models. In order to obtain the ideal model, one should start from these frameworks and build a bridge to reach another. This is a formidable task, if we consider the top-down approach, namely starting from the collective behavior and moving towards inter-individual interactions. The bottom-up approach also fails, if complex inter-individual interaction models are considered, yet in this case we can start with simple models and increase the complexity as needed. Findings – The bottom-up approach, considering simple agent-based herding model as a model for the inter-individual interactions, allows us to derive certain macroscopic models of the complex socio-economic systems from the agent-based perspective. This provides interesting insights into the collective behavior patterns observed in the complex socio-economic systems. Research limitations/implications –The simplicity of the agent-based herding model might be considered to be somewhat limiting. Yet this simplicity implies that the model is highly universal. It reproduces universal features of social behavior and also can be further extended to fit different socio-economic scenarios. Practical implications – Insights provided in this contribution might be used to modify existing

Green IT engineering concepts, models, complex systems architectures

CERN Document Server

Kondratenko, Yuriy; Kacprzyk, Janusz

2017-01-01

This volume provides a comprehensive state of the art overview of a series of advanced trends and concepts that have recently been proposed in the area of green information technologies engineering as well as of design and development methodologies for models and complex systems architectures and their intelligent components. The contributions included in the volume have their roots in the authors’ presentations, and vivid discussions that have followed the presentations, at a series of workshop and seminars held within the international TEMPUS-project GreenCo project in United Kingdom, Italy, Portugal, Sweden and the Ukraine, during 2013-2015 and at the 1st - 5th Workshops on Green and Safe Computing (GreenSCom) held in Russia, Slovakia and the Ukraine. The book presents a systematic exposition of research on principles, models, components and complex systems and a description of industry- and society-oriented aspects of the green IT engineering. A chapter-oriented structure has been adopted for this book ...

Chaos from simple models to complex systems

CERN Document Server

Cencini, Massimo; Vulpiani, Angelo

2010-01-01

Chaos: from simple models to complex systems aims to guide science and engineering students through chaos and nonlinear dynamics from classical examples to the most recent fields of research. The first part, intended for undergraduate and graduate students, is a gentle and self-contained introduction to the concepts and main tools for the characterization of deterministic chaotic systems, with emphasis to statistical approaches. The second part can be used as a reference by researchers as it focuses on more advanced topics including the characterization of chaos with tools of information theor

Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale

Science.gov (United States)

Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue

2018-03-01

Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.

A Framework for Modeling and Analyzing Complex Distributed Systems

National Research Council Canada - National Science Library

Lynch, Nancy A; Shvartsman, Alex Allister

2005-01-01

Report developed under STTR contract for topic AF04-T023. This Phase I project developed a modeling language and laid a foundation for computational support tools for specifying, analyzing, and verifying complex distributed system designs...

A computational framework for modeling targets as complex adaptive systems

Science.gov (United States)

Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

2017-05-01

Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

Sandpile model for relaxation in complex systems

International Nuclear Information System (INIS)

Vazquez, A.; Sotolongo-Costa, O.; Brouers, F.

1997-10-01

The relaxation in complex systems is, in general, nonexponential. After an initial rapid decay the system relaxes slowly following a long time tail. In the present paper a sandpile moderation of the relaxation in complex systems is analysed. Complexity is introduced by a process of avalanches in the Bethe lattice and a feedback mechanism which leads to slower decay with increasing time. In this way, some features of relaxation in complex systems: long time tails relaxation, aging, and fractal distribution of characteristic times, are obtained by simple computer simulations. (author)

Mathematical modeling of complexing in the scandium-salicylic acid-isoamyl alcohol system

International Nuclear Information System (INIS)

Evseev, A.M.; Smirnova, N.S.; Fadeeva, V.I.; Tikhomirova, T.I.; Kir'yanov, Yu.A.

1984-01-01

Mathematical modeling of an equilibrium multicomponent physicochemical system for extraction of Sc salicylate complexes by isoamyl alcohol was conducted. To calculate the equilibrium concentrations of Sc complexes different with respect to the content and composition, the system of nonlinear algebraic mass balance equations was solved. Experimental data on the extraction of Sc salicylates by isoamyl alcohol versus the pH of the solution at a constant Sc concentration and different concentration of salicylate-ions were used for construction of the mathematical model. The stability constants of ScHSal 2+ , Sc(HSal) 3 , ScOH(HSal) 2 , ScoH(HSal) 2 complexes were calculated

MODELS AND METHODS OF SAFETY-ORIENTED PROJECT MANAGEMENT OF DEVELOPMENT OF COMPLEX SYSTEMS: METHODOLOGICAL APPROACH

Directory of Open Access Journals (Sweden)

Олег Богданович ЗАЧКО

2016-03-01

Full Text Available The methods and models of safety-oriented project management of the development of complex systems are proposed resulting from the convergence of existing approaches in project management in contrast to the mechanism of value-oriented management. A cognitive model of safety oriented project management of the development of complex systems is developed, which provides a synergistic effect that is to move the system from the original (pre condition in an optimal one from the viewpoint of life safety - post-project state. The approach of assessment the project complexity is proposed, which consists in taking into account the seasonal component of a time characteristic of life cycles of complex organizational and technical systems with occupancy. This enabled to take into account the seasonal component in simulation models of life cycle of the product operation in complex organizational and technical system, modeling the critical points of operation of systems with occupancy, which forms a new methodology for safety-oriented management of projects, programs and portfolios of projects with the formalization of the elements of complexity.

Modeling Power Systems as Complex Adaptive Systems

Energy Technology Data Exchange (ETDEWEB)

Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

2004-12-30

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

Science.gov (United States)

Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

2016-03-10

Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and

On the general procedure for modelling complex ecological systems

International Nuclear Information System (INIS)

He Shanyu.

1987-12-01

In this paper, the principle of a general procedure for modelling complex ecological systems, i.e. the Adaptive Superposition Procedure (ASP) is shortly stated. The result of application of ASP in a national project for ecological regionalization is also described. (author). 3 refs

Modelling small-angle scattering data from complex protein-lipid systems

DEFF Research Database (Denmark)

Kynde, Søren Andreas Røssell

This thesis consists of two parts. The rst part is divided into five chapters. Chapter 1 gives a general introduction to the bio-molecular systems that have been studied. These are membrane proteins and their lipid environments in the form of phospholipid nanodiscs. Membrane proteins...... the techniques very well suited for the study of the nanodisc system. Chapter 3 explains two different modelling approaches that can be used in the analysis of small-angle scattering data from lipid-protein complexes. These are the continuous approach where the system of interest is modelled as a few regular...... combine the bene ts of each of the methods and give unique structural information about relevant bio-molecular complexes in solution. Chapter 4 describes the work behind a proposal of a small-angle neutron scattering instrument for the European Spallation Source under construction in Lund. The instrument...

Modeling Stochastic Complexity in Complex Adaptive Systems: Non-Kolmogorov Probability and the Process Algebra Approach.

Science.gov (United States)

Sulis, William H

2017-10-01

Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.

The semiotics of control and modeling relations in complex systems.

Science.gov (United States)

Joslyn, C

2001-01-01

We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

Science.gov (United States)

Koch, Patrick Nathan

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.

Modeling complexity in engineered infrastructure system: Water distribution network as an example

Science.gov (United States)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

Logic-based hierarchies for modeling behavior of complex dynamic systems with applications

International Nuclear Information System (INIS)

Hu, Y.S.; Modarres, M.

2000-01-01

Most complex systems are best represented in the form of a hierarchy. The Goal Tree Success Tree and Master Logic Diagram (GTST-MLD) are proven powerful hierarchic methods to represent complex snap-shot of plant knowledge. To represent dynamic behaviors of complex systems, fuzzy logic is applied to replace binary logic to extend the power of GTST-MLD. Such a fuzzy-logic-based hierarchy is called Dynamic Master Logic Diagram (DMLD). This chapter discusses comparison of the use of GTST-DMLD when applied as a modeling tool for systems whose relationships are modeled by either physical, binary logical or fuzzy logical relationships. This is shown by applying GTST-DMLD to the Direct Containment Heating (DCH) phenomenon at pressurized water reactors which is an important safety issue being addressed by the nuclear industry. (orig.)

Modelling methodology for engineering of complex sociotechnical systems

CSIR Research Space (South Africa)

Oosthuizen, R

2014-10-01

Full Text Available Different systems engineering techniques and approaches are applied to design and develop complex sociotechnical systems for complex problems. In a complex sociotechnical system cognitive and social humans use information technology to make sense...

Development of structural model of adaptive training complex in ergatic systems for professional use

Science.gov (United States)

Obukhov, A. D.; Dedov, D. L.; Arkhipov, A. E.

2018-03-01

The article considers the structural model of the adaptive training complex (ATC), which reflects the interrelations between the hardware, software and mathematical model of ATC and describes the processes in this subject area. The description of the main components of software and hardware complex, their interaction and functioning within the common system are given. Also the article scrutinizers a brief description of mathematical models of personnel activity, a technical system and influences, the interactions of which formalize the regularities of ATC functioning. The studies of main objects of training complexes and connections between them will make it possible to realize practical implementation of ATC in ergatic systems for professional use.

Modelling and simulation of electrical energy systems through a complex systems approach using agent-based models

Energy Technology Data Exchange (ETDEWEB)

Kremers, Enrique

2013-10-01

Complexity science aims to better understand the processes of both natural and man-made systems which are composed of many interacting entities at different scales. A disaggregated approach is proposed for simulating electricity systems, by using agent-based models coupled to continuous ones. The approach can help in acquiring a better understanding of the operation of the system itself, e.g. on emergent phenomena or scale effects; as well as in the improvement and design of future smart grids.

Modelling and simulation of complex sociotechnical systems: envisioning and analysing work environments

Science.gov (United States)

Hettinger, Lawrence J.; Kirlik, Alex; Goh, Yang Miang; Buckle, Peter

2015-01-01

Accurate comprehension and analysis of complex sociotechnical systems is a daunting task. Empirically examining, or simply envisioning the structure and behaviour of such systems challenges traditional analytic and experimental approaches as well as our everyday cognitive capabilities. Computer-based models and simulations afford potentially useful means of accomplishing sociotechnical system design and analysis objectives. From a design perspective, they can provide a basis for a common mental model among stakeholders, thereby facilitating accurate comprehension of factors impacting system performance and potential effects of system modifications. From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches. This paper describes issues involved in the design and use of such models and simulations and describes a proposed path forward to their development and implementation. Practitioner Summary: The size and complexity of real-world sociotechnical systems can present significant barriers to their design, comprehension and empirical analysis. This article describes the potential advantages of computer-based models and simulations for understanding factors that impact sociotechnical system design and operation, particularly with respect to process and occupational safety. PMID:25761227

Predicting the future completing models of observed complex systems

CERN Document Server

Abarbanel, Henry

2013-01-01

Predicting the Future: Completing Models of Observed Complex Systems provides a general framework for the discussion of model building and validation across a broad spectrum of disciplines. This is accomplished through the development of an exact path integral for use in transferring information from observations to a model of the observed system. Through many illustrative examples drawn from models in neuroscience, fluid dynamics, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is investigated. Using highly instructive examples, the problems of data assimilation and the means to treat them are clearly illustrated. This book will be useful for students and practitioners of physics, neuroscience, regulatory networks, meteorology and climate science, network dynamics, fluid dynamics, and o...

Models, methods and software tools for building complex adaptive traffic systems

International Nuclear Information System (INIS)

Alyushin, S.A.

2011-01-01

The paper studies the modern methods and tools to simulate the behavior of complex adaptive systems (CAS), the existing systems of traffic modeling in simulators and their characteristics; proposes requirements for assessing the suitability of the system to simulate the CAS behavior in simulators. The author has developed a model of adaptive agent representation and its functioning environment to meet certain requirements set above, and has presented methods of agents' interactions and methods of conflict resolution in simulated traffic situations. A simulation system realizing computer modeling for simulating the behavior of CAS in traffic situations has been created [ru

Small System dynamics models for big issues : Triple jump towards real-world complexity

NARCIS (Netherlands)

Pruyt, E.

2013-01-01

System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and analysis facilitates the (re)design of systems and design of

Recommended Research Directions for Improving the Validation of Complex Systems Models.

Energy Technology Data Exchange (ETDEWEB)

Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Finley, Patrick D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flanagan, Tatiana Paz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tsao, Jeffrey Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

Improved validation for models of complex systems has been a primary focus over the past year for the Resilience in Complex Systems Research Challenge. This document describes a set of research directions that are the result of distilling those ideas into three categories of research -- epistemic uncertainty, strong tests, and value of information. The content of this document can be used to transmit valuable information to future research activities, update the Resilience in Complex Systems Research Challenge's roadmap, inform the upcoming FY18 Laboratory Directed Research and Development (LDRD) call and research proposals, and facilitate collaborations between Sandia and external organizations. The recommended research directions can provide topics for collaborative research, development of proposals, workshops, and other opportunities.

Use of probabilistic relational model (PRM) for dependability analysis of complex systems

OpenAIRE

Medina-Oliva , Gabriela; Weber , Philippe; Levrat , Eric; Iung , Benoît

2010-01-01

International audience; This paper proposes a methodology to develop a aided decision-making tool for assessing the dependability and performances (i.e. reliability) of an industrial system. This tool is built on a model based on a new formalism, called the probabilistic relational model (PRM) which is adapted to deal with large and complex systems. The model is formalized from functional, dysfunctional and informational studies of the technical industrial systems. An application of this meth...

A modeling process to understand complex system architectures

Science.gov (United States)

Robinson, Santiago Balestrini

2009-12-01

In recent decades, several tools have been developed by the armed forces, and their contractors, to test the capability of a force. These campaign level analysis tools, often times characterized as constructive simulations are generally expensive to create and execute, and at best they are extremely difficult to verify and validate. This central observation, that the analysts are relying more and more on constructive simulations to predict the performance of future networks of systems, leads to the two central objectives of this thesis: (1) to enable the quantitative comparison of architectures in terms of their ability to satisfy a capability without resorting to constructive simulations, and (2) when constructive simulations must be created, to quantitatively determine how to spend the modeling effort amongst the different system classes. The first objective led to Hypothesis A, the first main hypotheses, which states that by studying the relationships between the entities that compose an architecture, one can infer how well it will perform a given capability. The method used to test the hypothesis is based on two assumptions: (1) the capability can be defined as a cycle of functions, and that it (2) must be possible to estimate the probability that a function-based relationship occurs between any two types of entities. If these two requirements are met, then by creating random functional networks, different architectures can be compared in terms of their ability to satisfy a capability. In order to test this hypothesis, a novel process for creating representative functional networks of large-scale system architectures was developed. The process, named the Digraph Modeling for Architectures (DiMA), was tested by comparing its results to those of complex constructive simulations. Results indicate that if the inputs assigned to DiMA are correct (in the tests they were based on time-averaged data obtained from the ABM), DiMA is able to identify which of any two

A novel approach for modelling complex maintenance systems using discrete event simulation

International Nuclear Information System (INIS)

Alrabghi, Abdullah; Tiwari, Ashutosh

2016-01-01

Existing approaches for modelling maintenance rely on oversimplified assumptions which prevent them from reflecting the complexity found in industrial systems. In this paper, we propose a novel approach that enables the modelling of non-identical multi-unit systems without restrictive assumptions on the number of units or their maintenance characteristics. Modelling complex interactions between maintenance strategies and their effects on assets in the system is achieved by accessing event queues in Discrete Event Simulation (DES). The approach utilises the wide success DES has achieved in manufacturing by allowing integration with models that are closely related to maintenance such as production and spare parts systems. Additional advantages of using DES include rapid modelling and visual interactive simulation. The proposed approach is demonstrated in a simulation based optimisation study of a published case. The current research is one of the first to optimise maintenance strategies simultaneously with their parameters while considering production dynamics and spare parts management. The findings of this research provide insights for non-conflicting objectives in maintenance systems. In addition, the proposed approach can be used to facilitate the simulation and optimisation of industrial maintenance systems. - Highlights: • This research is one of the first to optimise maintenance strategies simultaneously. • New insights for non-conflicting objectives in maintenance systems. • The approach can be used to optimise industrial maintenance systems.

A Model-Based Approach to Engineering Behavior of Complex Aerospace Systems

Science.gov (United States)

Ingham, Michel; Day, John; Donahue, Kenneth; Kadesch, Alex; Kennedy, Andrew; Khan, Mohammed Omair; Post, Ethan; Standley, Shaun

2012-01-01

One of the most challenging yet poorly defined aspects of engineering a complex aerospace system is behavior engineering, including definition, specification, design, implementation, and verification and validation of the system's behaviors. This is especially true for behaviors of highly autonomous and intelligent systems. Behavior engineering is more of an art than a science. As a process it is generally ad-hoc, poorly specified, and inconsistently applied from one project to the next. It uses largely informal representations, and results in system behavior being documented in a wide variety of disparate documents. To address this problem, JPL has undertaken a pilot project to apply its institutional capabilities in Model-Based Systems Engineering to the challenge of specifying complex spacecraft system behavior. This paper describes the results of the work in progress on this project. In particular, we discuss our approach to modeling spacecraft behavior including 1) requirements and design flowdown from system-level to subsystem-level, 2) patterns for behavior decomposition, 3) allocation of behaviors to physical elements in the system, and 4) patterns for capturing V&V activities associated with behavioral requirements. We provide examples of interesting behavior specification patterns, and discuss findings from the pilot project.

Multi-agent and complex systems

CERN Document Server

Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki

2017-01-01

This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.

Using multi-criteria analysis of simulation models to understand complex biological systems

Science.gov (United States)

Maureen C. Kennedy; E. David. Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Equation-free model reduction for complex dynamical systems

International Nuclear Information System (INIS)

Le Maitre, O. P.; Mathelin, L.; Le Maitre, O. P.

2010-01-01

This paper presents a reduced model strategy for simulation of complex physical systems. A classical reduced basis is first constructed relying on proper orthogonal decomposition of the system. Then, unlike the alternative approaches, such as Galerkin projection schemes for instance, an equation-free reduced model is constructed. It consists in the determination of an explicit transformation, or mapping, for the evolution over a coarse time-step of the projection coefficients of the system state on the reduced basis. The mapping is expressed as an explicit polynomial transformation of the projection coefficients and is computed once and for all in a pre-processing stage using the detailed model equation of the system. The reduced system can then be advanced in time by successive applications of the mapping. The CPU cost of the method lies essentially in the mapping approximation which is performed offline, in a parallel fashion, and only once. Subsequent application of the mapping to perform a time-integration is carried out at a low cost thanks to its explicit character. Application of the method is considered for the 2-D flow around a circular cylinder. We investigate the effectiveness of the reduced model in rendering the dynamics for both asymptotic state and transient stages. It is shown that the method leads to a stable and accurate time-integration for only a fraction of the cost of a detailed simulation, provided that the mapping is properly approximated and the reduced basis remains relevant for the dynamics investigated. (authors)

NHL and RCGA Based Multi-Relational Fuzzy Cognitive Map Modeling for Complex Systems

Directory of Open Access Journals (Sweden)

Zhen Peng

2015-11-01

Full Text Available In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL and Real Code Genetic Algorithm (RCGA. The multi-relational FCM fits to model the complex system with multi-dimensions and multi-granularities. The auto construct algorithm can learn the multi-relational FCM from multi-relational data resources to eliminate human intervention. The Multi-Relational Data Mining (MRDM algorithm integrates multi-instance oriented NHL and RCGA of FCM. NHL is extended to mine the causal relationships between coarse-granularity concept and its fined-granularity concepts driven by multi-instances in the multi-relational system. RCGA is used to establish high-quality high-level FCM driven by data. The multi-relational FCM and the integrating algorithm have been applied in complex system of Mutagenesis. The experiment demonstrates not only that they get better classification accuracy, but it also shows the causal relationships among the concepts of the system.

Functional modelling for integration of human-software-hardware in complex physical systems

International Nuclear Information System (INIS)

Modarres, M.

1996-01-01

A framework describing the properties of complex physical systems composed of human-software-hardware interactions in terms of their functions is described. It is argued that such a framework is domain-general, so that functional primitives present a language that is more general than most other modeling methods such as mathematical simulation. The characteristics and types of functional models are described. Examples of uses of the framework in modeling physical systems composed of human-software-hardware (hereby we refer to them as only physical systems) are presented. It is concluded that a function-centered model of a physical system provides a capability for generating a high-level simulation of the system for intelligent diagnostic, control or other similar applications

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

International Nuclear Information System (INIS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-01-01

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli

2015-06-12

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.

A Model of Human Decision Making in Complex Systems and its Use for Design of System Control Strategies

DEFF Research Database (Denmark)

Rasmussen, Jens; Lind, Morten

The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending on their perc...... representation of system properties in a multilevel flow model is described to provide a basis for an integrated control system design.......The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending...... on their perception of the system's immediate control requirements. These levels correspond to the abstraction hierarchy including system purpose, functions, and physical details, which is generally used to describe a formal design process. In emergency situations the task of the operator is to design a suitable...

Systems Approach to Tourism: A Methodology for Defining Complex Tourism System

Directory of Open Access Journals (Sweden)

Jere Jakulin Tadeja

2017-08-01

Full Text Available Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

Science.gov (United States)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation & Uncertainty Quantification

Energy Technology Data Exchange (ETDEWEB)

Tsao, Jeffrey Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kleban, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Curtis M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Mark A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flanagan, Tatiana Paz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gabert, Kasimir Georg [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lave, Matthew Samuel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Chen, Wei [Northwestern Univ., Evanston, IL (United States); DeLaurentis, Daniel [Purdue Univ., West Lafayette, IN (United States); Hubler, Alfred [Univ. of Illinois, Urbana, IL (United States); Oberkampf, Bill [WLO Consulting, Austin, TX (United States)

2016-08-01

This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?

Urban systems complexity in sustainability and health: an interdisciplinary modelling study

Directory of Open Access Journals (Sweden)

Nici Zimmermann, PhD

2018-05-01

Full Text Available Background: Improving urban health and sustainability raises complex questions that are best addressed through interdisciplinary and even transdisciplinary approaches, in which scientific research and analysis and stakeholder engagement have important roles. In this study we report pilot work in Nairobi (Kenya and London (UK that uses innovative methods to integrate qualitative and quantitative modelling to provide evidence to support policy development for health and sustainability in these cities. Methods: We used two primary modelling methods, system dynamics and microsimulation, and sought to understand the value of these tools in combination to support policy decisions. System dynamics was used to establish an aggregated and non-linear causal map of the interconnections between diverse variables, and thus to gain insight into the policies and specific processes that need to be examined in further depth. System dynamics was a key tool for city-level stakeholder engagement. In part informed by the outcome of the system dynamics process, microsimulation was then used to quantify local effects on health of selected policy options. The results were mapped using geographic information systems methods. Findings: The combination of system dynamics and microsimulation models provided a framework that enhanced collective knowledge about the interrelationships of policy decisions, funding, public awareness, and environmental and health effects. Our initial participatory system dynamics work on air pollution in Nairobi found that a combination of policies that focus on households and outdoor air could reduce household air pollution by about 50%, leaving it still above WHO-recommended levels. Yet, the investments in monitoring and health impact assessment have the potential to trigger reinforcing mechanisms that create synergies among existing policies and increase the return on investment. Preliminary 106-year microsimulation runs of the effects of PM2

Multifaceted Modelling of Complex Business Enterprises.

Science.gov (United States)

Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin; Ma, Lin; Lassen, David

2015-01-01

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control.

Multifaceted Modelling of Complex Business Enterprises

Science.gov (United States)

2015-01-01

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591

Modeling and simulation of complex systems a framework for efficient agent-based modeling and simulation

CERN Document Server

Siegfried, Robert

2014-01-01

Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the "General Reference Model for Agent-based Modeling and Simulation" (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models -from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hard

Stephen Jay Kline on systems, or physics, complex systems, and the gap between.

Energy Technology Data Exchange (ETDEWEB)

Campbell, Philip LaRoche

2011-06-01

At the end of his life, Stephen Jay Kline, longtime professor of mechanical engineering at Stanford University, completed a book on how to address complex systems. The title of the book is 'Conceptual Foundations of Multi-Disciplinary Thinking' (1995), but the topic of the book is systems. Kline first establishes certain limits that are characteristic of our conscious minds. Kline then establishes a complexity measure for systems and uses that complexity measure to develop a hierarchy of systems. Kline then argues that our minds, due to their characteristic limitations, are unable to model the complex systems in that hierarchy. Computers are of no help to us here. Our attempts at modeling these complex systems are based on the way we successfully model some simple systems, in particular, 'inert, naturally-occurring' objects and processes, such as what is the focus of physics. But complex systems overwhelm such attempts. As a result, the best we can do in working with these complex systems is to use a heuristic, what Kline calls the 'Guideline for Complex Systems.' Kline documents the problems that have developed due to 'oversimple' system models and from the inappropriate application of a system model from one domain to another. One prominent such problem is the Procrustean attempt to make the disciplines that deal with complex systems be 'physics-like.' Physics deals with simple systems, not complex ones, using Kline's complexity measure. The models that physics has developed are inappropriate for complex systems. Kline documents a number of the wasteful and dangerous fallacies of this type.

Fuzzy Modeling and Synchronization of a New Hyperchaotic Complex System with Uncertainties

Directory of Open Access Journals (Sweden)

Hadi Delavari

2015-07-01

Full Text Available In this paper, the synchronization of a new hyperchaotic complex system based on T-S fuzzy model is proposed. First the considered hyperchaotic system is represented by T-S fuzzy model equivalently. Then by using the parallel distributed compensation (PDC method and by applying linear system theory and exact linearization (EL technique, a fuzzy controller is designed to realize the synchronization. Finally, simulation results are carried out to demonstrate the performance of our proposed control scheme, and also the robustness of the designed fuzzy controller to uncertainties.

Modelling of the quenching process in complex superconducting magnet systems

International Nuclear Information System (INIS)

Hagedorn, D.; Rodriguez-Mateos, F.

1992-01-01

This paper reports that the superconducting twin bore dipole magnet for the proposed Large Hadron Collider (LHC) at CERN shows a complex winding structure consisting of eight compact layers each of them electromagnetically and thermally coupled with the others. This magnet is only one part of an electrical circuit; test and operation conditions are characterized by different circuits. In order to study the quenching process in this complex system, design adequate protection schemes, and provide a basis for the dimensioning of protection devices such as heaters, current breakers and dump resistors, a general simulation tool called QUABER has been developed using the analog system analysis program SABER. A complete set of electro-thermal models has been crated for the propagation of normal regions. Any network extension or modification is easy to implement without rewriting the whole set of differential equations

Complexity, Modeling, and Natural Resource Management

Directory of Open Access Journals (Sweden)

Paul Cilliers

2013-09-01

Full Text Available This paper contends that natural resource management (NRM issues are, by their very nature, complex and that both scientists and managers in this broad field will benefit from a theoretical understanding of complex systems. It starts off by presenting the core features of a view of complexity that not only deals with the limits to our understanding, but also points toward a responsible and motivating position. Everything we do involves explicit or implicit modeling, and as we can never have comprehensive access to any complex system, we need to be aware both of what we leave out as we model and of the implications of the choice of our modeling framework. One vantage point is never sufficient, as complexity necessarily implies that multiple (independent conceptualizations are needed to engage the system adequately. We use two South African cases as examples of complex systems - restricting the case narratives mainly to the biophysical domain associated with NRM issues - that make the point that even the behavior of the biophysical subsystems themselves are already complex. From the insights into complex systems discussed in the first part of the paper and the lessons emerging from the way these cases have been dealt with in reality, we extract five interrelated generic principles for practicing science and management in complex NRM environments. These principles are then further elucidated using four further South African case studies - organized as two contrasting pairs - and now focusing on the more difficult organizational and social side, comparing the human organizational endeavors in managing such systems.

Determination of timescales of nitrate contamination by groundwater age models in a complex aquifer system

Science.gov (United States)

Koh, E. H.; Lee, E.; Kaown, D.; Lee, K. K.; Green, C. T.

2017-12-01

Timing and magnitudes of nitrate contamination are determined by various factors like contaminant loading, recharge characteristics and geologic system. Information of an elapsed time since recharged water traveling to a certain outlet location, which is defined as groundwater age, can provide indirect interpretation related to the hydrologic characteristics of the aquifer system. There are three major methods (apparent ages, lumped parameter model, and numerical model) to date groundwater ages, which differently characterize groundwater mixing resulted by various groundwater flow pathways in a heterogeneous aquifer system. Therefore, in this study, we compared the three age models in a complex aquifer system by using observed age tracer data and reconstructed history of nitrate contamination by long-term source loading. The 3H-3He and CFC-12 apparent ages, which did not consider the groundwater mixing, estimated the most delayed response time and a highest period of the nitrate loading had not reached yet. However, the lumped parameter model could generate more recent loading response than the apparent ages and the peak loading period influenced the water quality. The numerical model could delineate various groundwater mixing components and its different impacts on nitrate dynamics in the complex aquifer system. The different age estimation methods lead to variations in the estimated contaminant loading history, in which the discrepancy in the age estimation was dominantly observed in the complex aquifer system.

Increase of Organization in Complex Systems

OpenAIRE

Georgiev, Georgi Yordanov; Daly, Michael; Gombos, Erin; Vinod, Amrit; Hoonjan, Gajinder

2013-01-01

Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system -...

Complex Adaptive Systems of Systems (CASOS) engineering environment.

Energy Technology Data Exchange (ETDEWEB)

Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

2012-02-01

Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

Critical appraisal of first-generation renal tumor complexity scoring systems: Creation of a second-generation model of tumor complexity.

Science.gov (United States)

Tobert, Conrad M; Shoemaker, Allen; Kahnoski, Richard J; Lane, Brian R

2015-04-01

To investigate whether a combination of variables from each nephrometry system improves performance. There are 3 first-generation systems that quantify tumor complexity: R.E.N.A.L. nephrometry score (RNS), preoperative aspects and dimensions used for an anatomical (PADUA) classification (PC), and centrality index (CI). Although each has been subjected to validation and comparative analysis, to our knowledge, no work has been done to combine variables from each method to optimize their performance. Scores were assigned to each of 276 patients undergoing partial nephrectomy (PN) or radical nephrectomy (RN). Individual components of all 3 systems were evaluated in multivariable logistic regression analysis of surgery type (PN vs. RN) and combined into a "second-generation model." In multivariable analysis, each scoring system was a significant predictor of PN vs. RN (Psystems, CI was most highly correlated with surgery type (area under the curve [AUC] = 0.91), followed by RNS (AUC = 0.90) and PC (AUC = 0.88). Each individual component of these scoring systems was also a predictor of surgery type (Psystem (RNS), location along the lateral rim (PC), and centrality (CI). A novel model in which these 4 variables were rescaled outperformed each first-generation system (AUC = 0.91). Optimization of first-generation models of renal tumor complexity results in a novel scoring system, which strongly predicts surgery type. This second-generation model should aid comprehension, but future work is still needed to establish the most clinically useful model. Copyright © 2015 Elsevier Inc. All rights reserved.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Science.gov (United States)

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Directory of Open Access Journals (Sweden)

Zhong Yi Wan

Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more

The Modeling and Complexity of Dynamical Systems by Means of Computation and Information Theories

Directory of Open Access Journals (Sweden)

Robert Logozar

2011-12-01

Full Text Available We present the modeling of dynamical systems and finding of their complexity indicators by the use of concepts from computation and information theories, within the framework of J. P. Crutchfield's theory of  ε-machines. A short formal outline of the  ε-machines is given. In this approach, dynamical systems are analyzed directly from the time series that is received from a properly adjusted measuring instrument. The binary strings are parsed through the parse tree, within which morphologically and probabilistically unique subtrees or morphs are recognized as system states. The outline and precise interrelation of the information-theoretic entropies and complexities emanating from the model is given. The paper serves also as a theoretical foundation for the future presentation of the DSA program that implements the  ε-machines modeling up to the stochastic finite automata level.

Complex systems modeling by cellular automata

NARCIS (Netherlands)

Kroc, J.; Sloot, P.M.A.; Rabuñal Dopico, J.R.; Dorado de la Calle, J.; Pazos Sierra, A.

2009-01-01

In recent years, the notion of complex systems proved to be a very useful concept to define, describe, and study various natural phenomena observed in a vast number of scientific disciplines. Examples of scientific disciplines that highly benefit from this concept range from physics, mathematics,

Automated sensitivity analysis: New tools for modeling complex dynamic systems

International Nuclear Information System (INIS)

Pin, F.G.

1987-01-01

Sensitivity analysis is an established methodology used by researchers in almost every field to gain essential insight in design and modeling studies and in performance assessments of complex systems. Conventional sensitivity analysis methodologies, however, have not enjoyed the widespread use they deserve considering the wealth of information they can provide, partly because of their prohibitive cost or the large initial analytical investment they require. Automated systems have recently been developed at ORNL to eliminate these drawbacks. Compilers such as GRESS and EXAP now allow automatic and cost effective calculation of sensitivities in FORTRAN computer codes. In this paper, these and other related tools are described and their impact and applicability in the general areas of modeling, performance assessment and decision making for radioactive waste isolation problems are discussed

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

DEFF Research Database (Denmark)

Eby, M.; Weaver, A. J.; Alexander, K.

2013-01-01

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20...

Research Area 3: Mathematics (3.1 Modeling of Complex Systems)

Science.gov (United States)

2017-10-31

Title: RESEARCH AREA 3: MATHEMATICS (3.1 Modeling of Complex Systems). Proposal should be directed to Dr. John Lavery Report Term: 0-Other Email ...Paolo Rosso Email : prosso@dsic.upv.es values of the profile characteristics taken by the users), intersection (they represent the relationship between...accuracy, especially when adding fully connected layers at the end of the network. This work has resulted in the writing of a manuscript for the Journal

Model-based identification and use of task complexity factors of human integrated systems

International Nuclear Information System (INIS)

Ham, Dong-Han; Park, Jinkyun; Jung, Wondea

2012-01-01

Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.

Predictive Surface Complexation Modeling

Energy Technology Data Exchange (ETDEWEB)

Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

2016-11-29

Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO₂ and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

Science.gov (United States)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function

Operating of mobile machine units system using the model of multicomponent complex movement

OpenAIRE

A. Lebedev; R. Kaidalov; N. Artiomov; M. Shulyak; M. Podrigalo; D. Abramov; D. Klets

2015-01-01

To solve the problems of mobile machine units system operating it is proposed using complex multi-component (composite) movement physical models. Implementation of the proposed method is possible by creating of automatic operating systems of fuel supply to the engines using linear accelerometers. Some examples to illustrate the proposed method are offered.

Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity

Science.gov (United States)

Juckem, Paul F.; Clark, Brian R.; Feinstein, Daniel T.

2017-05-04

The U.S. Geological Survey, National Water-Quality Assessment seeks to map estimated intrinsic susceptibility of the glacial aquifer system of the conterminous United States. Improved understanding of the hydrogeologic characteristics that explain spatial patterns of intrinsic susceptibility, commonly inferred from estimates of groundwater age distributions, is sought so that methods used for the estimation process are properly equipped. An important step beyond identifying relevant hydrogeologic datasets, such as glacial geology maps, is to evaluate how incorporation of these resources into process-based models using differing levels of detail could affect resulting simulations of groundwater age distributions and, thus, estimates of intrinsic susceptibility.This report describes the construction and calibration of three groundwater-flow models of northeastern Wisconsin that were developed with differing levels of complexity to provide a framework for subsequent evaluations of the effects of process-based model complexity on estimations of groundwater age distributions for withdrawal wells and streams. Preliminary assessments, which focused on the effects of model complexity on simulated water levels and base flows in the glacial aquifer system, illustrate that simulation of vertical gradients using multiple model layers improves simulated heads more in low-permeability units than in high-permeability units. Moreover, simulation of heterogeneous hydraulic conductivity fields in coarse-grained and some fine-grained glacial materials produced a larger improvement in simulated water levels in the glacial aquifer system compared with simulation of uniform hydraulic conductivity within zones. The relation between base flows and model complexity was less clear; however, the relation generally seemed to follow a similar pattern as water levels. Although increased model complexity resulted in improved calibrations, future application of the models using simulated particle

The maintenance management framework models and methods for complex systems maintenance

CERN Document Server

Crespo Márquez, Adolfo

2010-01-01

“The Maintenance Management Framework” describes and reviews the concept, process and framework of modern maintenance management of complex systems; concentrating specifically on modern modelling tools (deterministic and empirical) for maintenance planning and scheduling. It will be bought by engineers and professionals involved in maintenance management, maintenance engineering, operations management, quality, etc. as well as graduate students and researchers in this field.

Sutherland models for complex reflection groups

International Nuclear Information System (INIS)

Crampe, N.; Young, C.A.S.

2008-01-01

There are known to be integrable Sutherland models associated to every real root system, or, which is almost equivalent, to every real reflection group. Real reflection groups are special cases of complex reflection groups. In this paper we associate certain integrable Sutherland models to the classical family of complex reflection groups. Internal degrees of freedom are introduced, defining dynamical spin chains, and the freezing limit taken to obtain static chains of Haldane-Shastry type. By considering the relation of these models to the usual BC N case, we are led to systems with both real and complex reflection groups as symmetries. We demonstrate their integrability by means of new Dunkl operators, associated to wreath products of dihedral groups

Control of complex systems

CERN Document Server

Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo

2001-01-01

The world of artificial systems is reaching complexity levels that es­ cape human understanding. Surface traffic, electricity distribution, air­ planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi­ neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re­ search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu­ ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...

The Kuramoto model in complex networks

Science.gov (United States)

Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen

2016-01-01

Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

OPERATING OF MOBILE MACHINE UNITS SYSTEM USING THE MODEL OF MULTICOMPONENT COMPLEX MOVEMENT

Directory of Open Access Journals (Sweden)

A. Lebedev

2015-07-01

Full Text Available To solve the problems of mobile machine units system operating it is proposed using complex multi-component (composite movement physical models. Implementation of the proposed method is possible by creating of automatic operating systems of fuel supply to the engines using linear accelerometers. Some examples to illustrate the proposed method are offered.

Integrated modeling tool for performance engineering of complex computer systems

Science.gov (United States)

Wright, Gary; Ball, Duane; Hoyt, Susan; Steele, Oscar

1989-01-01

This report summarizes Advanced System Technologies' accomplishments on the Phase 2 SBIR contract NAS7-995. The technical objectives of the report are: (1) to develop an evaluation version of a graphical, integrated modeling language according to the specification resulting from the Phase 2 research; and (2) to determine the degree to which the language meets its objectives by evaluating ease of use, utility of two sets of performance predictions, and the power of the language constructs. The technical approach followed to meet these objectives was to design, develop, and test an evaluation prototype of a graphical, performance prediction tool. The utility of the prototype was then evaluated by applying it to a variety of test cases found in the literature and in AST case histories. Numerous models were constructed and successfully tested. The major conclusion of this Phase 2 SBIR research and development effort is that complex, real-time computer systems can be specified in a non-procedural manner using combinations of icons, windows, menus, and dialogs. Such a specification technique provides an interface that system designers and architects find natural and easy to use. In addition, PEDESTAL's multiview approach provides system engineers with the capability to perform the trade-offs necessary to produce a design that meets timing performance requirements. Sample system designs analyzed during the development effort showed that models could be constructed in a fraction of the time required by non-visual system design capture tools.

The evolution model of Uppsala in light of the complex adaptive systems approach

Directory of Open Access Journals (Sweden)

Rennaly Alves da Silva

2013-11-01

Full Text Available The behavioral approach to the internationalization of companies explains that the movements toward external markets occur in accordance with the increasing commitment of resources to mitigate the effects of uncertainty and reduce the perception of risk. Evidence indicates that the theories and practices developed in the domestic market may not be able to explain the reality of companies that operate in international markets. Thus, the Paradigm of Complexity presents itself as a comprehensive alternative to realize the relationships within organizations and markets. Accordingly, the aim of this theoretical paper is to analyze the evolution of the Uppsala Model between years 1975 and 2010 with the understanding of the companies in the process of internationalization as Complex Adaptive Systems, in accordance with the Model Kelly and Allison (1998. Four propositions are presented that show the links between the approaches. The most surprising is the perception that the conceptual evolution of the Uppsala Model seems to accompany the evolution of complexity levels, presented in Model Kelly and Allison.

Using environmental tracers in modeling flow in a complex shallow aquifer system

DEFF Research Database (Denmark)

Troldborg, Lars; Jensen, Karsten Høgh; Engesgaard, Peter Knudegaard

2008-01-01

shapes and sizes without being similar to the assumed age distributions used in the analytical approach. The shape of age distribution to some extent depends on sampling size and on whether the system is modeled in a transient or in a steady state, but shape and size were largely driven......Using environmental tracers in groundwater dating partly relies on the assumption that groundwater age distribution can be described analytically. To investigate the applicability of age dating in complex multiaquifer systems, a methodology for simulating well specific groundwater age distribution...... was developed. Using a groundwater model and particle tracking we modeled age distributions at screen locations. By enveloping modeled age distributions and estimated recharge concentrations, environmental tracer breakthroughs were simulated for specific screens. Simulated age distributions are of irregular...

New Modeling of Steady-State Modes of Complex Electrical Grids of Power Systems

Directory of Open Access Journals (Sweden)

Akhmetbayev Arman

2018-01-01

Full Text Available Classical methods for modeling the steady-state modes of complex electrical networks and systems are based on the application of nonlinear node equations. Nonlinear equations are solved by iterative methods, which are connected by known difficulties. To a certain extent, these difficulties can be weakened by applying topological methods. In this paper, we outline the theoretical foundations for the formation of the inverse form of nodal stress equations based on the topology of electrical networks and systems. A new topological method for calculating the distribution coefficients of node currents is proposed based on all possible trees of a directed graph of a complex electrical network. A complex program for calculating current distribution coefficients and forming steady-state parameters in the MATLAB environment has been developed.

Interacting with complex systems. Models and games for a sustainable economy

Energy Technology Data Exchange (ETDEWEB)

De Vries, H.J.M.

2010-09-15

In the last decades the science-policy interface has become more important and more complex too. In this report we search for novel ways to extend or reframe the economic and environmental theories and models upon which policy recommendations are, or should be, based. The methods and applications of Complex System Science, in particular, have been explored and are found to be still fragmented. But they certainly can and should form the basis for introducing behavioural and innovation dynamics which make these theories and models more like what happens in the real world. In combination with interactive simulation and games, of which some examples are discussed in this report, science can in a post-modern context contribute more effectively to the strategic decision making in government and other institutions regarding sustainable development. This will direly be needed in view of the new and global challenges facing us.

Model-Based Development and Evaluation of Control for Complex Multi-Domain Systems

DEFF Research Database (Denmark)

Grujic, Ivan; Nilsson, Rene

A Cyber-Physical System (CPS) incorporates sensing, actuating, computing and communicative capabilities, which are often combined to control the system. The development of CPSs poses a challenge, since the complexity of the physical system dynamics must be taken into account when designing...... Unmanned Aerial Vehicle (UAV) has been constructed and used to develop an attitude controller based on Model Predictive Control (MPC). The MPC controller has been compared to an existing open source Proportional Integral Derivative (PID) attitude controller. This thesis contributes to the discipline...

Agent-based model with asymmetric trading and herding for complex financial systems.

Science.gov (United States)

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex

Third International Conference on Complex Systems

CERN Document Server

Minai, Ali A; Unifying Themes in Complex Systems

2006-01-01

In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains over 35 papers selected from those presented at the conference on topics including: self-organization in biology, ecological systems, language, economic modeling, ecological systems, artificial life, robotics, and complexity and art. ALI MINAI is an Affiliate of the New England Complex Systems Institute and an Associate Professor in the Department of Electrical and Computer Engine...

Teleconnections in complex human-Earth system models

Science.gov (United States)

Calvin, K. V.; Edmonds, J.

2017-12-01

Human systems and physical Earth systems are closely coupled and interact in complex ways that are sometimes surprising. This presentation discusses a few examples of system interactions. We consider the coupled energy-water-land-economy systems. We show how reductions in fossil fuel emissions are inversely coupled to land rents, food prices and deforestation. We discuss how water shortages in one part of the world is propagated to other distant parts of the world. We discuss the sensitivity of international trade patterns to energy and land systems technology and markets, and the potentially unanticipated results that can emerge.

Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Directory of Open Access Journals (Sweden)

Aloah J Pope

2015-08-01

Full Text Available Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.

SUPERCOMPUTER SIMULATION OF CRITICAL PHENOMENA IN COMPLEX SOCIAL SYSTEMS

Directory of Open Access Journals (Sweden)

Petrus M.A. Sloot

2014-09-01

Full Text Available The paper describes a problem of computer simulation of critical phenomena in complex social systems on a petascale computing systems in frames of complex networks approach. The three-layer system of nested models of complex networks is proposed including aggregated analytical model to identify critical phenomena, detailed model of individualized network dynamics and model to adjust a topological structure of a complex network. The scalable parallel algorithm covering all layers of complex networks simulation is proposed. Performance of the algorithm is studied on different supercomputing systems. The issues of software and information infrastructure of complex networks simulation are discussed including organization of distributed calculations, crawling the data in social networks and results visualization. The applications of developed methods and technologies are considered including simulation of criminal networks disruption, fast rumors spreading in social networks, evolution of financial networks and epidemics spreading.

The utility of Earth system Models of Intermediate Complexity

NARCIS (Netherlands)

Weber, S.L.

2010-01-01

Intermediate-complexity models are models which describe the dynamics of the atmosphere and/or ocean in less detail than conventional General Circulation Models (GCMs). At the same time, they go beyond the approach taken by atmospheric Energy Balance Models (EBMs) or ocean box models by

Modeling and Performance Considerations for Automated Fault Isolation in Complex Systems

Science.gov (United States)

Ferrell, Bob; Oostdyk, Rebecca

2010-01-01

The purpose of this paper is to document the modeling considerations and performance metrics that were examined in the development of a large-scale Fault Detection, Isolation and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FDIR team members developed a set of operational requirements for the models that would be used for fault isolation and worked closely with the vendor of the software tools selected for fault isolation to ensure that the software was able to meet the requirements. Once the requirements were established, example models of sufficient complexity were used to test the performance of the software. The results of the performance testing demonstrated the need for enhancements to the software in order to meet the demands of the full-scale ground and vehicle FDIR system. The paper highlights the importance of the development of operational requirements and preliminary performance testing as a strategy for identifying deficiencies in highly scalable systems and rectifying those deficiencies before they imperil the success of the project

Is Model-Based Development a Favorable Approach for Complex and Safety-Critical Computer Systems on Commercial Aircraft?

Science.gov (United States)

Torres-Pomales, Wilfredo

2014-01-01

A system is safety-critical if its failure can endanger human life or cause significant damage to property or the environment. State-of-the-art computer systems on commercial aircraft are highly complex, software-intensive, functionally integrated, and network-centric systems of systems. Ensuring that such systems are safe and comply with existing safety regulations is costly and time-consuming as the level of rigor in the development process, especially the validation and verification activities, is determined by considerations of system complexity and safety criticality. A significant degree of care and deep insight into the operational principles of these systems is required to ensure adequate coverage of all design implications relevant to system safety. Model-based development methodologies, methods, tools, and techniques facilitate collaboration and enable the use of common design artifacts among groups dealing with different aspects of the development of a system. This paper examines the application of model-based development to complex and safety-critical aircraft computer systems. Benefits and detriments are identified and an overall assessment of the approach is given.

Complexity of Economical Systems

Directory of Open Access Journals (Sweden)

G. P. Pavlos

2015-01-01

Full Text Available In this study new theoretical concepts are described concerning the interpretation of economical complex dynamics. In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24]. In general, Economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. As a result the economic and financial variables such as foreign exchange rates, gross domestic product, interest rates, production, stock market prices and unemployment exhibit large-amplitude and aperiodic fluctuations evident in complex systems. Thus, the Economics can be considered as spatially distributed non-equilibrium complex system, for which new theoretical concepts, such as Tsallis non extensive statistical mechanics and strange dynamics, percolation, nonGaussian, multifractal and multiscale dynamics related to fractional Langevin equations can be used for modeling and understanding of the economical complexity locally or globally.

Complex Physical, Biophysical and Econophysical Systems

Science.gov (United States)

Dewar, Robert L.; Detering, Frank

1. Introduction to complex and econophysics systems: a navigation map / T. Aste and T. Di Matteo -- 2. An introduction to fractional diffusion / B. I. Henry, T.A.M. Langlands and P. Straka -- 3. Space plasmas and fusion plasmas as complex systems / R. O. Dendy -- 4. Bayesian data analysis / M. S. Wheatland -- 5. Inverse problems and complexity in earth system science / I. G. Enting -- 6. Applied fluid chaos: designing advection with periodically reoriented flows for micro to geophysical mixing and transport enhancement / G. Metcalfe -- 7. Approaches to modelling the dynamical activity of brain function based on the electroencephalogram / D. T. J. Liley and F. Frascoli -- 8. Jaynes' maximum entropy principle, Riemannian metrics and generalised least action bound / R. K. Niven and B. Andresen -- 9. Complexity, post-genomic biology and gene expression programs / R. B. H. Williams and O. J.-H. Luo -- 10. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek / M. J. Berryman and S. D. Angus.

Epidemic modeling in complex realities.

Science.gov (United States)

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

Science.gov (United States)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

Complex system modelling and control through intelligent soft computations

CERN Document Server

Azar, Ahmad

2015-01-01

The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, r...

Thermodynamic modeling of complex systems

DEFF Research Database (Denmark)

Liang, Xiaodong

after an oil spill. Engineering thermodynamics could be applied in the state-of-the-art sonar products through advanced artificial technology, if the speed of sound, solubility and density of oil-seawater systems could be satisfactorily modelled. The addition of methanol or glycols into unprocessed well...... is successfully applied to model the phase behaviour of water, chemical and hydrocarbon (oil) containing systems with newly developed pure component parameters for water and chemicals and characterization procedures for petroleum fluids. The performance of the PCSAFT EOS on liquid-liquid equilibria of water...... with hydrocarbons has been under debate for some vii years. An interactive step-wise procedure is proposed to fit the model parameters for small associating fluids by taking the liquid-liquid equilibrium data into account. It is still far away from a simple task to apply PC-SAFT in routine PVT simulations and phase...

Decentralized control of complex systems

CERN Document Server

Siljak, Dragoslav D

2011-01-01

Complex systems require fast control action in response to local input, and perturbations dictate the use of decentralized information and control structures. This much-cited reference book explores the approaches to synthesizing control laws under decentralized information structure constraints.Starting with a graph-theoretic framework for structural modeling of complex systems, the text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and t

Application of Complex Adaptive Systems in Portfolio Management

Science.gov (United States)

Su, Zheyuan

2017-01-01

Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…

Modeling Networks and Dynamics in Complex Systems: from Nano-Composites to Opinion Formation

Science.gov (United States)

Shi, Feng

Complex networks are ubiquitous in systems of physical, biological, social or technological origin. Components in those systems range from as large as cities in power grids, to as small as molecules in metabolic networks. Since the dawn of network science, significant attention has focused on the implications of dynamics in establishing network structure and the impact of structural properties on dynamics on those networks. The first part of the thesis follows this direction, studying the network formed by conductive nanorods in nano-materials, and focuses on the electrical response of the composite to the structure change of the network. New scaling laws for the shear-induced anisotropic percolation are introduced and a robust exponential tail of the current distribution across the network is identified. These results are relevant especially to "active" composite materials where materials are exposed to mechanical loading and strain deformations. However, in many real-world networks the evolution of the network topology is tied to the states of the vertices and vice versa. Networks that exhibit such a feedback are called adaptive or coevolutionary networks. The second part of the thesis examines two closely related variants of a simple, abstract model for coevolution of a network and the opinions of its members. As a representative model for adaptive networks, it displays the feature of self-organization of the system into a stable configuration due to the interplay between the network topology and the dynamics on the network. This simple model yields interesting dynamics and the slight change in the rewiring strategy results in qualitatively different behaviors of the system. In conclusion, the dissertation aims to develop new network models and tools which enable insights into the structure and dynamics of various systems, and seeks to advance network algorithms which provide approaches to coherently articulated questions in real-world complex systems such as

Complex groundwater flow systems as traveling agent models

Directory of Open Access Journals (Sweden)

Oliver López Corona

2014-10-01

Full Text Available Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow.

A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

Directory of Open Access Journals (Sweden)

Tinggui Chen

2013-01-01

Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

A new decision sciences for complex systems

OpenAIRE

Lempert, Robert J.

2002-01-01

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an...

Models of complex attitude systems

DEFF Research Database (Denmark)

Sørensen, Bjarne Taulo

search algorithms and structural equation models. The results suggest that evaluative judgments of the importance of production system attributes are generated in a schematic manner, driven by personal value orientations. The effect of personal value orientations was strong and largely unmediated...... that evaluative affect propagates through the system in such a way that the system becomes evaluatively consistent and operates as a schema for the generation of evaluative judgments. In the empirical part of the paper, the causal structure of an attitude system from which people derive their evaluations of pork......Existing research on public attitudes towards agricultural production systems is largely descriptive, abstracting from the processes through which members of the general public generate their evaluations of such systems. The present paper adopts a systems perspective on such evaluations...

Agent-based model with asymmetric trading and herding for complex financial systems.

Directory of Open Access Journals (Sweden)

Jun-Jie Chen

Full Text Available BACKGROUND: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. METHODS: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. RESULTS: With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. CONCLUSIONS: We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the

Local difference measures between complex networks for dynamical system model evaluation.

Science.gov (United States)

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

Science.gov (United States)

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour

From System Complexity to Emergent Properties

CERN Document Server

Aziz-Alaoui, M. A

2009-01-01

Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.

Analysis and control of complex dynamical systems robust bifurcation, dynamic attractors, and network complexity

CERN Document Server

Imura, Jun-ichi; Ueta, Tetsushi

2015-01-01

This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

Developing predictive systems models to address complexity and relevance for ecological risk assessment.

Science.gov (United States)

Forbes, Valery E; Calow, Peter

2013-07-01

Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have. Copyright © 2013 SETAC.

A new decision sciences for complex systems.

Science.gov (United States)

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

Polystochastic Models for Complexity

CERN Document Server

Iordache, Octavian

2010-01-01

This book is devoted to complexity understanding and management, considered as the main source of efficiency and prosperity for the next decades. Divided into six chapters, the book begins with a presentation of basic concepts as complexity, emergence and closure. The second chapter looks to methods and introduces polystochastic models, the wave equation, possibilities and entropy. The third chapter focusing on physical and chemical systems analyzes flow-sheet synthesis, cyclic operations of separation, drug delivery systems and entropy production. Biomimetic systems represent the main objective of the fourth chapter. Case studies refer to bio-inspired calculation methods, to the role of artificial genetic codes, neural networks and neural codes for evolutionary calculus and for evolvable circuits as biomimetic devices. The fifth chapter, taking its inspiration from systems sciences and cognitive sciences looks to engineering design, case base reasoning methods, failure analysis, and multi-agent manufacturing...

Integrated Modeling of Complex Optomechanical Systems

Science.gov (United States)

Andersen, Torben; Enmark, Anita

2011-09-01

Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.

Computer modeling of properties of complex molecular systems

Energy Technology Data Exchange (ETDEWEB)

Kulkova, E.Yu. [Moscow State University of Technology “STANKIN”, Vadkovsky per., 1, Moscow 101472 (Russian Federation); Khrenova, M.G.; Polyakov, I.V. [Lomonosov Moscow State University, Chemistry Department, Leninskie Gory 1/3, Moscow 119991 (Russian Federation); Nemukhin, A.V. [Lomonosov Moscow State University, Chemistry Department, Leninskie Gory 1/3, Moscow 119991 (Russian Federation); N.M. Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina 4, Moscow 119334 (Russian Federation)

2015-03-10

Large molecular aggregates present important examples of strongly nonhomogeneous systems. We apply combined quantum mechanics / molecular mechanics approaches that assume treatment of a part of the system by quantum-based methods and the rest of the system with conventional force fields. Herein we illustrate these computational approaches by two different examples: (1) large-scale molecular systems mimicking natural photosynthetic centers, and (2) components of prospective solar cells containing titan dioxide and organic dye molecules. We demonstrate that modern computational tools are capable to predict structures and spectra of such complex molecular aggregates.

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

Science.gov (United States)

Rungta, Neha; Brat, Guillaume; Clancey, William J.; Linde, Charlotte; Raimondi, Franco; Seah, Chin; Shafto, Michael

2013-01-01

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Agent-based model with multi-level herding for complex financial systems

Science.gov (United States)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

A model of human decision making in complex systems and its use for design of system control strategies

International Nuclear Information System (INIS)

Rasmussen, J.; Lind, M.

1982-04-01

The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending on their preception of the system's immediate control requirements. These levels correspond to the abstraction hierarchy including system purpose, functions, and physical details, which is generally used to describe a formal design process. In emergency situations the task of the operator is to design a suitabel control strategy for systems recovery, and the control systems designer should provide a man-machine interface, supporting the operator in identification of his task and in communication with the system at the level of abstraction corresponding to the immedite control requirement. A formalized representation of system properties in a multilevel flow model is described to provide a basis for an integrated control system design. (author)

A Modeling Framework for the Concurrent Design of Complex Space Systems

NARCIS (Netherlands)

Ridolfi, G.; Mooij, E.; Chiesa, S.

2010-01-01

The design of complex systems has become more and more articulated during the last decade, thus forcing radical modifications on the overall methodological approach. The authors developed a design methodology, which allows the user to design a particular category of complex systems usually called

A method for work modeling at complex systems: towards applying information systems in family health care units.

Science.gov (United States)

Jatobá, Alessandro; de Carvalho, Paulo Victor R; da Cunha, Amauri Marques

2012-01-01

Work in organizations requires a minimum level of consensus on the understanding of the practices performed. To adopt technological devices to support the activities in environments where work is complex, characterized by the interdependence among a large number of variables, understanding about how work is done not only takes an even greater importance, but also becomes a more difficult task. Therefore, this study aims to present a method for modeling of work in complex systems, which allows improving the knowledge about the way activities are performed where these activities do not simply happen by performing procedures. Uniting techniques of Cognitive Task Analysis with the concept of Work Process, this work seeks to provide a method capable of providing a detailed and accurate vision of how people perform their tasks, in order to apply information systems for supporting work in organizations.

Observation-Driven Configuration of Complex Software Systems

Science.gov (United States)

Sage, Aled

2010-06-01

The ever-increasing complexity of software systems makes them hard to comprehend, predict and tune due to emergent properties and non-deterministic behaviour. Complexity arises from the size of software systems and the wide variety of possible operating environments: the increasing choice of platforms and communication policies leads to ever more complex performance characteristics. In addition, software systems exhibit different behaviour under different workloads. Many software systems are designed to be configurable so that policies can be chosen to meet the needs of various stakeholders. For complex software systems it can be difficult to accurately predict the effects of a change and to know which configuration is most appropriate. This thesis demonstrates that it is useful to run automated experiments that measure a selection of system configurations. Experiments can find configurations that meet the stakeholders' needs, find interesting behavioural characteristics, and help produce predictive models of the system's behaviour. The design and use of ACT (Automated Configuration Tool) for running such experiments is described, in combination a number of search strategies for deciding on the configurations to measure. Design Of Experiments (DOE) is discussed, with emphasis on Taguchi Methods. These statistical methods have been used extensively in manufacturing, but have not previously been used for configuring software systems. The novel contribution here is an industrial case study, applying the combination of ACT and Taguchi Methods to DC-Directory, a product from Data Connection Ltd (DCL). The case study investigated the applicability of Taguchi Methods for configuring complex software systems. Taguchi Methods were found to be useful for modelling and configuring DC- Directory, making them a valuable addition to the techniques available to system administrators and developers.

MOIRA models and methodologies for assessing the effectiveness of countermeasures in complex aquatic systems contaminated by radionuclides

International Nuclear Information System (INIS)

Monte, L.; Haakanson, L.; Gallego Diaz, E.

1999-01-01

The present report is composed of a set of articles written by the partners of the MOIRA project (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas). The report describes models for predicting the behaviour of radionuclides in complex aquatic systems and the effects of countermeasures for their restoration [it

Extraction of quantifiable information from complex systems

CERN Document Server

Dahmen, Wolfgang; Griebel, Michael; Hackbusch, Wolfgang; Ritter, Klaus; Schneider, Reinhold; Schwab, Christoph; Yserentant, Harry

2014-01-01

In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance.  Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges.   Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as w...

Complexity and Control: Towards a Rigorous Behavioral Theory of Complex Dynamical Systems

Science.gov (United States)

Ivancevic, Vladimir G.; Reid, Darryn J.

We introduce our motive for writing this book on complexity and control with a popular "complexity myth," which seems to be quite wide spread among chaos and complexity theory fashionistas: quote>Low-dimensional systems usually exhibit complex behaviours (which we know fromMay's studies of the Logisticmap), while high-dimensional systems usually exhibit simple behaviours (which we know from synchronisation studies of the Kuramoto model)...quote> We admit that this naive view on complex (e.g., human) systems versus simple (e.g., physical) systems might seem compelling to various technocratic managers and politicians; indeed, the idea makes for appealing sound-bites. However, it is enough to see both in the equations and computer simulations of pendula of various degree - (i) a single pendulum, (ii) a double pendulum, and (iii) a triple pendulum - that this popular myth is plain nonsense. The only thing that we can learn from it is what every tyrant already knows: by using force as a strong means of control, it is possible to effectively synchronise even hundreds of millions of people, at least for a while.

Computational Modeling of Complex Protein Activity Networks

NARCIS (Netherlands)

Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

2017-01-01

Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

Graph Cellular Automata with Relation-Based Neighbourhoods of Cells for Complex Systems Modelling: A Case of Traffic Simulation

Directory of Open Access Journals (Sweden)

Krzysztof Małecki

2017-12-01

Full Text Available A complex system is a set of mutually interacting elements for which it is possible to construct a mathematical model. This article focuses on the cellular automata theory and the graph theory in order to compare various types of cellular automata and to analyse applications of graph structures together with cellular automata. It proposes a graph cellular automaton with a variable configuration of cells and relation-based neighbourhoods (r–GCA. The developed mechanism enables modelling of phenomena found in complex systems (e.g., transport networks, urban logistics, social networks taking into account the interaction between the existing objects. As an implementation example, modelling of moving vehicles has been made and r–GCA was compared to the other cellular automata models simulating the road traffic and used in the computer simulation process.

Large-scale computing techniques for complex system simulations

CERN Document Server

Dubitzky, Werner; Schott, Bernard

2012-01-01

Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and

Modeling Complex Chemical Systems: Problems and Solutions

Science.gov (United States)

van Dijk, Jan

2016-09-01

Non-equilibrium plasmas in complex gas mixtures are at the heart of numerous contemporary technologies. They typically contain dozens to hundreds of species, involved in hundreds to thousands of reactions. Chemists and physicists have always been interested in what are now called chemical reduction techniques (CRT's). The idea of such CRT's is that they reduce the number of species that need to be considered explicitly without compromising the validity of the model. This is usually achieved on the basis of an analysis of the reaction time scales of the system under study, which identifies species that are in partial equilibrium after a given time span. The first such CRT that has been widely used in plasma physics was developed in the 1960's and resulted in the concept of effective ionization and recombination rates. It was later generalized to systems in which multiple levels are effected by transport. In recent years there has been a renewed interest in tools for chemical reduction and reaction pathway analysis. An example of the latter is the PumpKin tool. Another trend is that techniques that have previously been developed in other fields of science are adapted as to be able to handle the plasma state of matter. Examples are the Intrinsic Low Dimension Manifold (ILDM) method and its derivatives, which originate from combustion engineering, and the general-purpose Principle Component Analysis (PCA) technique. In this contribution we will provide an overview of the most common reduction techniques, then critically assess the pros and cons of the methods that have gained most popularity in recent years. Examples will be provided for plasmas in argon and carbon dioxide.

Modelling and Simulating Complex Systems in Biology: introducing NetBioDyn : A Pedagogical and Intuitive Agent-Based Software

OpenAIRE

Ballet, Pascal; Rivière, Jérémy; Pothet, Alain; Théron, Michaël; Pichavant, Karine; Abautret, Frank; Fronville, Alexandra; Rodin, Vincent

2017-01-01

International audience; Modelling and teaching complex biological systems is a difficult process. Multi-Agent Based Simulations (MABS) have proved to be an appropriate approach both in research and education when dealing with such systems including emergent, self-organizing phenomena. This chapter presents NetBioDyn, an original software aimed at biologists (students, teachers, researchers) to easily build and simulate complex biological mechanisms observed in multicellular and molecular syst...

Strategies and Rubrics for Teaching Complex Systems Theory to Novices (Invited)

Science.gov (United States)

Fichter, L. S.

2010-12-01

Bifurcation. Self-similarity. Fractal. Sensitive dependent. Agents. Self-organized criticality. Avalanche behavior. Power laws. Strange attractors. Emergence. The language of complexity is fundamentally different from the language of equilibrium. If students do not know these phenomena, and what they tell us about the pulse of dynamic systems, complex systems will be opaque. A complex system is a group of agents. (individual interacting units, like birds in a flock, sand grains in a ripple, or individual friction units along a fault zone), existing far from equilibrium, interacting through positive and negative feedbacks, following simple rules, forming interdependent, dynamic, evolutionary networks. Complex systems produce behaviors that cannot be predicted deductively from knowledge of the behaviors of the individual components themselves; they must be experienced. What complexity theory demonstrates is that, by following simple rules, all the agents end up coordinating their behavior—self organizing—so that what emerges is not chaos, but meaningful patterns. How can we introduce Freshman, non-science, general education students to complex systems theories, in 3 to 5 classes; in a way they really get it, and can use the principles to understand real systems? Complex systems theories are not a series of unconnected or disconnected equations or models; they are developed as narratives that makes sense of how all the pieces and properties are interrelated. The principles of complex systems must be taught as deliberately and systematically as the equilibrium principles normally taught; as, say, the systematic training from pre-algebra and geometry to algebra. We have developed a sequence of logically connected narratives (strategies and rubrics) that introduce complex systems principles using models that can be simulated in a computer, in class, in real time. The learning progression has a series of 12 models (e.g. logistic system, bifurcation diagrams, genetic

DEVELOPING INDUSTRIAL ROBOT SIMULATION MODEL TUR10-K USING “UNIVERSAL MECHANISM” SOFTWARE COMPLEX

Directory of Open Access Journals (Sweden)

Vadim Vladimirovich Chirkov

2018-02-01

Full Text Available Manipulation robots are complex spatial mechanical systems having five or six degrees of freedom, and sometimes more. For this reason, modeling manipulative robots movement, even in the kinematic formulation, is a complex mathematical task. If one moves from kinematic modeling of motion to dynamic modeling then there must be taken into account the inertial properties of the modeling object. In this case, analytical constructing of such a complex object mathematical model as a manipulation robot becomes practically impossible. Therefore, special computer-aided design systems, called CAE-systems, are used for modeling complex mechanical systems. The purpose of the paper is simulation model construction of a complex mechanical system, such as the industrial robot TUR10-K, to obtain its dynamic characteristics. Developing such models makes it possible to reduce the complexity of designing complex systems process and to obtain the necessary characteristics. Purpose. Developing the simulation model of the industrial robot TUR10-K and obtaining dynamic characteristics of the mechanism. Methodology: the article is used a computer simulation method. Results: There is obtained the simulation model of the robot and its dynamic characteristics. Practical implications: the results can be used in the mechanical systems design and various simulation models.

From control to causation: Validating a 'complex systems model' of running-related injury development and prevention.

Science.gov (United States)

Hulme, A; Salmon, P M; Nielsen, R O; Read, G J M; Finch, C F

2017-11-01

There is a need for an ecological and complex systems approach for better understanding the development and prevention of running-related injury (RRI). In a previous article, we proposed a prototype model of the Australian recreational distance running system which was based on the Systems Theoretic Accident Mapping and Processes (STAMP) method. That model included the influence of political, organisational, managerial, and sociocultural determinants alongside individual-level factors in relation to RRI development. The purpose of this study was to validate that prototype model by drawing on the expertise of both systems thinking and distance running experts. This study used a modified Delphi technique involving a series of online surveys (December 2016- March 2017). The initial survey was divided into four sections containing a total of seven questions pertaining to different features associated with the prototype model. Consensus in opinion about the validity of the prototype model was reached when the number of experts who agreed or disagreed with survey statement was ≥75% of the total number of respondents. A total of two Delphi rounds was needed to validate the prototype model. Out of a total of 51 experts who were initially contacted, 50.9% (n = 26) completed the first round of the Delphi, and 92.3% (n = 24) of those in the first round participated in the second. Most of the 24 full participants considered themselves to be a running expert (66.7%), and approximately a third indicated their expertise as a systems thinker (33.3%). After the second round, 91.7% of the experts agreed that the prototype model was a valid description of the Australian distance running system. This is the first study to formally examine the development and prevention of RRI from an ecological and complex systems perspective. The validated model of the Australian distance running system facilitates theoretical advancement in terms of identifying practical system

Complex fluids in biological systems experiment, theory, and computation

CERN Document Server

2015-01-01

This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

Advances in complex societal, environmental and engineered systems

CERN Document Server

Essaaidi, Mohammad

2017-01-01

This book addresses recent technological progress that has led to an increased complexity in many natural and artificial systems. The resulting complexity research due to the emergence of new properties and spatio-temporal interactions among a large number of system elements - and between the system and its environment - is the primary focus of this text. This volume is divided into three parts: Part one focuses on societal and ecological systems, Part two deals with approaches for understanding, modeling, predicting and mastering socio-technical systems, and Part three includes real-life examples. Each chapter has its own special features; it is a self-contained contribution of distinguished experts working on different fields of science and technology relevant to the study of complex systems. Advances in Complex Systems of Contemporary Reality: Societal, Environmental and Engineered Systems will provide postgraduate students, researchers and managers with qualitative and quantitative methods for handling th...

Reliability assessment of complex electromechanical systems under epistemic uncertainty

International Nuclear Information System (INIS)

Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong

2016-01-01

The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.

Student Learning of Complex Earth Systems: A Model to Guide Development of Student Expertise in Problem-Solving

Science.gov (United States)

Holder, Lauren N.; Scherer, Hannah H.; Herbert, Bruce E.

2017-01-01

Engaging students in problem-solving concerning environmental issues in near-surface complex Earth systems involves developing student conceptualization of the Earth as a system and applying that scientific knowledge to the problems using practices that model those used by professionals. In this article, we review geoscience education research…

On spin and matrix models in the complex plane

International Nuclear Information System (INIS)

Damgaard, P.H.; Heller, U.M.

1993-01-01

We describe various aspects of statistical mechanics defined in the complex temperature or coupling-constant plane. Using exactly solvable models, we analyse such aspects as renormalization group flows in the complex plane, the distribution of partition function zeros, and the question of new coupling-constant symmetries of complex-plane spin models. The double-scaling form of matrix models is shown to be exactly equivalent to finite-size scaling of two-dimensional spin systems. This is used to show that the string susceptibility exponents derived from matrix models can be obtained numerically with very high accuracy from the scaling of finite-N partition function zeros in the complex plane. (orig.)

Engineering education as a complex system

Science.gov (United States)

Gattie, David K.; Kellam, Nadia N.; Schramski, John R.; Walther, Joachim

2011-12-01

This paper presents a theoretical basis for cultivating engineering education as a complex system that will prepare students to think critically and make decisions with regard to poorly understood, ill-structured issues. Integral to this theoretical basis is a solution space construct developed and presented as a benchmark for evaluating problem-solving orientations that emerge within students' thinking as they progress through an engineering curriculum. It is proposed that the traditional engineering education model, while analytically rigorous, is characterised by properties that, although necessary, are insufficient for preparing students to address complex issues of the twenty-first century. A Synthesis and Design Studio model for engineering education is proposed, which maintains the necessary rigor of analysis within a uniquely complex yet sufficiently structured learning environment.

SCIENTIFIC METHODOLOGICAL APPROACHES TO CREATION OF COMPLEX CONTROL SYSTEM MODEL FOR THE STREAMS OF BUILDING WASTE

Directory of Open Access Journals (Sweden)

Tskhovrebov Eduard Stanislavovich

2015-09-01

Full Text Available In 2011 in Russia a Strategy of Production Development of Construction Materials and Industrial Housing Construction for the period up to 2020 was approved as one of strategic documents in the sphere of construction. In the process of this strategy development all the needs of construction complex were taken into account in all the spheres of economy, including transport system. The strategy also underlined, that the construction industry is a great basis for use and application in secondary economic turnover of dangerous waste from different production branches. This gives possibility to produce construction products of recycled materials and at the same time to solve the problem of environmental protection. The article considers and analyzes scientific methodological approaches to creation of a model of a complex control system for the streams of building waste in frames of organizing uniform ecologically safe and economically effective complex system of waste treatment in country regions.

Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.

Science.gov (United States)

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions. © 2017 Society for the Study of Addiction.

Controller Design of Complex System Based on Nonlinear Strength

Directory of Open Access Journals (Sweden)

Rongjun Mu

2015-01-01

Full Text Available This paper presents a new idea of controller design for complex systems. The nonlinearity index method was first developed for error propagation of nonlinear system. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of the system model. The algorithm of nonlinearity index according to engineering application is first proposed in this paper. Applying this method on nonlinear systems is an effective way to measure the nonlinear strength of dynamics model over the full flight envelope. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of system model. According to the different nonlinear strength of dynamical model, the control system is designed. The simulation time of dynamical complex system is selected by the maximum value of dynamic nonlinearity indices. Take a missile as example; dynamical system and control characteristic of missile are simulated. The simulation results show that the method is correct and appropriate.

Complexity in electronic negotiation support systems.

Science.gov (United States)

Griessmair, Michele; Strunk, Guido; Vetschera, Rudolf; Koeszegi, Sabine T

2011-10-01

It is generally acknowledged that the medium influences the way we communicate and negotiation research directs considerable attention to the impact of different electronic communication modes on the negotiation process and outcomes. Complexity theories offer models and methods that allow the investigation of how pattern and temporal sequences unfold over time in negotiation interactions. By focusing on the dynamic and interactive quality of negotiations as well as the information, choice, and uncertainty contained in the negotiation process, the complexity perspective addresses several issues of central interest in classical negotiation research. In the present study we compare the complexity of the negotiation communication process among synchronous and asynchronous negotiations (IM vs. e-mail) as well as an electronic negotiation support system including a decision support system (DSS). For this purpose, transcripts of 145 negotiations have been coded and analyzed with the Shannon entropy and the grammar complexity. Our results show that negotiating asynchronically via e-mail as well as including a DSS significantly reduces the complexity of the negotiation process. Furthermore, a reduction of the complexity increases the probability of reaching an agreement.

Methodology for Measuring the Complexity of Enterprise Information Systems

Directory of Open Access Journals (Sweden)

Ilja Holub

2016-07-01

Full Text Available The complexity of enterprise information systems is currently a challenge faced not only by IT professionals and project managers, but also by the users of such systems. Current methodologies and frameworks used to design and implement information systems do not specifically deal with the issue of their complexity and, apart from few exceptions, do not at all attempt to simplify the complexity. This article presents the author's own methodology for managing complexity, which can be used to complement any other methodology and which helps limit the growth of complexity. It introduces its own definition and metric of complexity, which it defines as the sum of entities of the individual UML models of the given system, which are selected according to the MMDIS methodology so as to consistently describe all relevant content dimensions of the system. The main objective is to propose a methodology to manage information system complexity and to verify it in practice on a real-life SAP implementation project.

Modeling of complex gas distribution systems operating under any vacuum conditions: Simulations of the ITER divertor pumping system

International Nuclear Information System (INIS)

Vasileiadis, N.; Tatsios, G.; Misdanitis, S.; Valougeorgis, D.

2016-01-01

Highlights: • An integrated s/w for modeling complex rarefied gas distribution systems is presented. • Analysis is based on kinetic theory of gases. • Code effectiveness is demonstrated by simulating the ITER divertor pumping system. • The present s/w has the potential to support design work in large vacuum systems. - Abstract: An integrated software tool for modeling and simulation of complex gas distribution systems operating under any vacuum conditions is presented and validated. The algorithm structure includes (a) the input geometrical and operational data of the network, (b) the definition of the fundamental set of network loops and pseudoloops, (c) the formulation and solution of the mass and energy conservation equations, (d) the kinetic data base of the flow rates for channels of any length in the whole range of the Knudsen number, supporting, in an explicit manner, the solution of the conservation equations and (e) the network output data (mainly node pressures and channel flow rates/conductance). The code validity is benchmarked under rough vacuum conditions by comparison with hydrodynamic solutions in the slip regime. Then, its feasibility, effectiveness and potential are demonstrated by simulating the ITER torus vacuum system with the six direct pumps based on the 2012 design of the ITER divertor. Detailed results of the flow patterns and paths in the cassettes, in the gaps between the cassettes and along the divertor ring, as well as of the total throughput for various pumping scenarios and dome pressures are provided. A comparison with previous results available in the literature is included.

A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

Science.gov (United States)

Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

2005-01-01

This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

Documentation Driven Development for Complex Real-Time Systems

Science.gov (United States)

2004-12-01

This paper presents a novel approach for development of complex real - time systems , called the documentation-driven development (DDD) approach. This... time systems . DDD will also support automated software generation based on a computational model and some relevant techniques. DDD includes two main...stakeholders to be easily involved in development processes and, therefore, significantly improve the agility of software development for complex real

Linking Complexity and Sustainability Theories: Implications for Modeling Sustainability Transitions

Directory of Open Access Journals (Sweden)

Camaren Peter

2014-03-01

Full Text Available In this paper, we deploy a complexity theory as the foundation for integration of different theoretical approaches to sustainability and develop a rationale for a complexity-based framework for modeling transitions to sustainability. We propose a framework based on a comparison of complex systems’ properties that characterize the different theories that deal with transitions to sustainability. We argue that adopting a complexity theory based approach for modeling transitions requires going beyond deterministic frameworks; by adopting a probabilistic, integrative, inclusive and adaptive approach that can support transitions. We also illustrate how this complexity-based modeling framework can be implemented; i.e., how it can be used to select modeling techniques that address particular properties of complex systems that we need to understand in order to model transitions to sustainability. In doing so, we establish a complexity-based approach towards modeling sustainability transitions that caters for the broad range of complex systems’ properties that are required to model transitions to sustainability.

Modeling, Simulation and Analysis of Complex Networked Systems: A Program Plan for DOE Office of Advanced Scientific Computing Research

Energy Technology Data Exchange (ETDEWEB)

Brown, D L

2009-05-01

Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex

Modeling, Simulation and Analysis of Complex Networked Systems: A Program Plan for DOE Office of Advanced Scientific Computing Research

International Nuclear Information System (INIS)

Brown, D.L.

2009-01-01

Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex networked systems

Embracing uncertainty, managing complexity: applying complexity thinking principles to transformation efforts in healthcare systems.

Science.gov (United States)

Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney

2018-03-21

Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By

Metric for Calculation of System Complexity based on its Connections

Directory of Open Access Journals (Sweden)

João Ricardo Braga de Paiva

2017-02-01

Full Text Available This paper proposes a methodology based on system connections to calculate its complexity. Two study cases are proposed: the dining Chinese philosophers’ problem and the distribution center. Both studies are modeled using the theory of Discrete Event Systems and simulations in different contexts were performed in order to measure their complexities. The obtained results present i the static complexity as a limiting factor for the dynamic complexity, ii the lowest cost in terms of complexity for each unit of measure of the system performance and iii the output sensitivity to the input parameters. The associated complexity and performance measures aggregate knowledge about the system.

Automatic Emergence Detection in Complex Systems

Directory of Open Access Journals (Sweden)

Eugene Santos

2017-01-01

Full Text Available Complex systems consist of multiple interacting subsystems, whose nonlinear interactions can result in unanticipated (emergent system events. Extant systems analysis approaches fail to detect such emergent properties, since they analyze each subsystem separately and arrive at decisions typically through linear aggregations of individual analysis results. In this paper, we propose a quantitative definition of emergence for complex systems. We also propose a framework to detect emergent properties given observations of its subsystems. This framework, based on a probabilistic graphical model called Bayesian Knowledge Bases (BKBs, learns individual subsystem dynamics from data, probabilistically and structurally fuses said dynamics into a single complex system dynamics, and detects emergent properties. Fusion is the central element of our approach to account for situations when a common variable may have different probabilistic distributions in different subsystems. We evaluate our detection performance against a baseline approach (Bayesian Network ensemble on synthetic testbeds from UCI datasets. To do so, we also introduce a method to simulate and a metric to measure discrepancies that occur with shared/common variables. Experiments demonstrate that our framework outperforms the baseline. In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.

Between Complexity and Parsimony: Can Agent-Based Modelling Resolve the Trade-off

DEFF Research Database (Denmark)

Nielsen, Helle Ørsted; Malawska, Anna Katarzyna

2013-01-01

to BR- based policy studies would be to couple research on bounded ra-tionality with agent-based modeling. Agent-based models (ABMs) are computational models for simulating the behavior and interactions of any number of decision makers in a dynamic system. Agent-based models are better suited than...... are general equilibrium models for capturing behavior patterns of complex systems. ABMs may have the potential to represent complex systems without oversimplifying them. At the same time, research in bounded rationality and behavioral economics has already yielded many insights that could inform the modeling......While Herbert Simon espoused development of general models of behavior, he also strongly advo-cated that these models be based on realistic assumptions about humans and therefore reflect the complexity of human cognition and social systems (Simon 1997). Hence, the model of bounded rationality...

Complex systems and networks dynamics, controls and applications

CERN Document Server

Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

2016-01-01

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

Collectives and the design of complex systems

CERN Document Server

Wolpert, David

2004-01-01

Increasingly powerful computers are making possible distributed systems comprised of many adaptive and self-motivated computational agents. Such systems, when distinguished by system-level performance criteria, are known as "collectives." Collectives and the Design of Complex Systems lays the foundation for a science of collectives and describes how to design them for optimal performance. An introductory survey chapter is followed by descriptions of information-processing problems that can only be solved by the joint actions of large communities of computers, each running its own complex, decentralized machine-learning algorithm. Subsequent chapters analyze the dynamics and structures of collectives, as well as address economic, model-free, and control-theory approaches to designing complex systems. The work assumes a modest understanding of basic statistics and calculus. Topics and Features: Introduces the burgeoning science of collectives and its practical applications in a single useful volume Combines ap...

Modeling of kinetics of the inducible protein complexes of the SOS system in bacteria E. coli which realize TLS process

International Nuclear Information System (INIS)

Belov, O.V.

2008-01-01

The mathematical model describing kinetics of the inducible genes of the protein complexes, formed during SOS response in bacteria Escherichia coli is developed. Within the bounds of developed approaches the auxiliary mathematical model describing changes in concentrations of the dimers, which are the components of final protein complexes, is developed. The solutions of both models are based on the experimental data concerning expression of the basic genes of the SOS system in bacteria Escherichia coli

Can Models Capture the Complexity of the Systems Engineering Process?

Science.gov (United States)

Boppana, Krishna; Chow, Sam; de Weck, Olivier L.; Lafon, Christian; Lekkakos, Spyridon D.; Lyneis, James; Rinaldi, Matthew; Wang, Zhiyong; Wheeler, Paul; Zborovskiy, Marat; Wojcik, Leonard A.

Many large-scale, complex systems engineering (SE) programs have been problematic; a few examples are listed below (Bar-Yam, 2003 and Cullen, 2004), and many others have been late, well over budget, or have failed: Hilton/Marriott/American Airlines system for hotel reservations and flights; 1988-1992; 125 million; "scrapped"

State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

Science.gov (United States)

Pfister, Patrik L.; Stocker, Thomas F.

2017-10-01

Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

A complex systems approach to constructing better models for managing financial markets and the economy

Science.gov (United States)

Farmer, J. Doyne; Gallegati, M.; Hommes, C.; Kirman, A.; Ormerod, P.; Cincotti, S.; Sanchez, A.; Helbing, D.

2012-11-01

We outline a vision for an ambitious program to understand the economy and financial markets as a complex evolving system of coupled networks of interacting agents. This is a completely different vision from that currently used in most economic models. This view implies new challenges and opportunities for policy and managing economic crises. The dynamics of such models inherently involve sudden and sometimes dramatic changes of state. Further, the tools and approaches we use emphasize the analysis of crises rather than of calm periods. In this they respond directly to the calls of Governors Bernanke and Trichet for new approaches to macroeconomic modelling.

Generalized Combination Complex Synchronization for Fractional-Order Chaotic Complex Systems

Directory of Open Access Journals (Sweden)

Cuimei Jiang

2015-07-01

Full Text Available Based on two fractional-order chaotic complex drive systems and one fractional-order chaotic complex response system with different dimensions, we propose generalized combination complex synchronization. In this new synchronization scheme, there are two complex scaling matrices that are non-square matrices. On the basis of the stability theory of fractional-order linear systems, we design a general controller via active control. Additionally, by virtue of two complex scaling matrices, generalized combination complex synchronization between fractional-order chaotic complex systems and real systems is investigated. Finally, three typical examples are given to demonstrate the effectiveness and feasibility of the schemes.

Role of Reactive Mn Complexes in a Litter Decomposition Model System

Science.gov (United States)

Nico, P. S.; Keiluweit, M.; Bougoure, J.; Kleber, M.; Summering, J. A.; Maynard, J. J.; Johnson, M.; Pett-Ridge, J.

2012-12-01

The search for controls on litter decomposition rates and pathways has yet to return definitive characteristics that are both statistically robust and can be understood as part of a mechanistic or numerical model. Herein we focus on Mn, an element present in all litter that is likely an active chemical agent of decomposition. Berg and co-workers (2010) found a strong correlation between Mn concentration in litter and the magnitude of litter degradation in boreal forests, suggesting that litter decomposition proceeds more efficiently in the presence of Mn. Although there is much circumstantial evidence for the potential role of Mn in lignin decomposition, few reports exist on mechanistic details of this process. For the current work, we are guided by the hypothesis that the dependence of decomposition on Mn is due to Mn (III)-oxalate complexes act as a 'pretreatment' for structurally intact ligno-carbohydrate complexes (LCC) in fresh plant cell walls (e.g. in litter, root and wood). Manganese (III)-ligand complexes such as Mn (III)-oxalate are known to be potent oxidizers of many different organic and inorganic compounds. In the litter system, the unique property of these complexes may be that they are much smaller than exo-enzymes and therefore more easily able to penetrate LCC complexes in plant cell walls. By acting as 'diffusible oxidizers' and reacting with the organic matrix of the cell wall, these compounds can increase the porosity of fresh litter thereby facilitating access of more specific lignin- and cellulose decomposing enzymes. This possibility was investigated by reacting cell walls of single Zinnia elegans tracheary elements with Mn (III)-oxalate complexes in a continuous flow reactor. The uniformity of these individual plant cells allowed us to examine Mn (III)-induced changes in cell wall chemistry and ultrastructure on the micro-scale using fluorescence and electron microscopy as well as IR and X-ray spectromicroscopy. This presentation will

Challenges in the analysis of complex systems: introduction and overview

Science.gov (United States)

Hastings, Harold M.; Davidsen, Jörn; Leung, Henry

2017-12-01

One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

Science.gov (United States)

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

Model-based system engineering approach for the Euclid mission to manage scientific and technical complexity

Science.gov (United States)

Lorenzo Alvarez, Jose; Metselaar, Harold; Amiaux, Jerome; Saavedra Criado, Gonzalo; Gaspar Venancio, Luis M.; Salvignol, Jean-Christophe; Laureijs, René J.; Vavrek, Roland

2016-08-01

In the last years, the system engineering field is coming to terms with a paradigm change in the approach for complexity management. Different strategies have been proposed to cope with highly interrelated systems, system of systems and collaborative system engineering have been proposed and a significant effort is being invested into standardization and ontology definition. In particular, Model Based System Engineering (MBSE) intends to introduce methodologies for a systematic system definition, development, validation, deployment, operation and decommission, based on logical and visual relationship mapping, rather than traditional 'document based' information management. The practical implementation in real large-scale projects is not uniform across fields. In space science missions, the usage has been limited to subsystems or sample projects with modeling being performed 'a-posteriori' in many instances. The main hurdle for the introduction of MBSE practices in new projects is still the difficulty to demonstrate their added value to a project and whether their benefit is commensurate with the level of effort required to put them in place. In this paper we present the implemented Euclid system modeling activities, and an analysis of the benefits and limitations identified to support in particular requirement break-down and allocation, and verification planning at mission level.

Morphogenetic Engineering Toward Programmable Complex Systems

CERN Document Server

Sayama, Hiroki; Michel, Olivier

2012-01-01

Generally, spontaneous pattern formation phenomena are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both self-organized and architectural.   This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is placed on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies.   Altogether, the aim of this work is to provide a framework for and examples of a larger class of “self-architecturing” systems, while addressing fundamental questions such as   > How do biological organisms carry out morphog...

Multidimensional approach to complex system resilience analysis

International Nuclear Information System (INIS)

Gama Dessavre, Dante; Ramirez-Marquez, Jose E.; Barker, Kash

2016-01-01

Recent works have attempted to formally define a general metric for quantifying resilience for complex systems as a relationship of performance of the systems against time. The technical content in the proposed work introduces a new model that allows, for the first time, to compare the system resilience among systems (or different modifications to a system), by introducing a new dimension to system resilience models, called stress, to mimic the definition of resilience in material science. The applicability and usefulness of the model is shown with a new heat map visualization proposed in this work, and it is applied to a simulated network resilience case to exemplify its potential benefits. - Highlights: • We analyzed two of the main current metrics of resilience. • We create a new model that relates events with the effects they have. • We develop a novel heat map visualization to compare system resilience. • We showed the model and visualization usefulness in a simulated case.

Optimization of large-scale heterogeneous system-of-systems models.

Energy Technology Data Exchange (ETDEWEB)

Parekh, Ojas; Watson, Jean-Paul; Phillips, Cynthia Ann; Siirola, John; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Lee, Herbert K. H. (University of California, Santa Cruz, Santa Cruz, CA); Hart, William Eugene; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Woodruff, David L. (University of California, Davis, Davis, CA)

2012-01-01

Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.

Transforming Graphical System Models to Graphical Attack Models

DEFF Research Database (Denmark)

Ivanova, Marieta Georgieva; Probst, Christian W.; Hansen, Rene Rydhof

2016-01-01

Manually identifying possible attacks on an organisation is a complex undertaking; many different factors must be considered, and the resulting attack scenarios can be complex and hard to maintain as the organisation changes. System models provide a systematic representation of organisations...... approach to transforming graphical system models to graphical attack models in the form of attack trees. Based on an asset in the model, our transformations result in an attack tree that represents attacks by all possible actors in the model, after which the actor in question has obtained the asset....

Evolution of complexity in RNA-like replicator systems

Directory of Open Access Journals (Sweden)

Hogeweg Paulien

2008-03-01

Full Text Available Abstract Background The evolution of complexity is among the most important questions in biology. The evolution of complexity is often observed as the increase of genetic information or that of the organizational complexity of a system. It is well recognized that the formation of biological organization – be it of molecules or ecosystems – is ultimately instructed by the genetic information, whereas it is also true that the genetic information is functional only in the context of the organization. Therefore, to obtain a more complete picture of the evolution of complexity, we must study the evolution of both information and organization. Results Here we investigate the evolution of complexity in a simulated RNA-like replicator system. The simplicity of the system allows us to explicitly model the genotype-phenotype-interaction mapping of individual replicators, whereby we avoid preconceiving the functionality of genotypes (information or the ecological organization of replicators in the model. In particular, the model assumes that interactions among replicators – to replicate or to be replicated – depend on their secondary structures and base-pair matching. The results showed that a population of replicators, originally consisting of one genotype, evolves to form a complex ecosystem of up to four species. During this diversification, the species evolve through acquiring unique genotypes with distinct ecological functionality. The analysis of this diversification reveals that parasitic replicators, which have been thought to destabilize the replicator's diversity, actually promote the evolution of diversity through generating a novel "niche" for catalytic replicators. This also makes the current replicator system extremely stable upon the evolution of parasites. The results also show that the stability of the system crucially depends on the spatial pattern formation of replicators. Finally, the evolutionary dynamics is shown to

New Challenges for the Management of the Development of Information Systems Based on Complex Mathematical Models

DEFF Research Database (Denmark)

Carugati, Andrea

2002-01-01

has been initiated with the scope of investigating the questions that mathematical modelling technology poses to traditional information systems development projects. Based on the past body of research, this study proposes a framework to guide decision making for managing projects of information......The advancements in complexity and sophistication of mathematical models for manufacturing scheduling and control and the increase of the ratio power/cost of computers are beginning to provide the manufacturing industry with new software tools to improve production. A Danish action research project...... systems development. In a presented case the indications of the model are compared with the decisions taken during the development. The results highlight discrepancies between the structure and predictions of the model and the case observations, especially with regard to the importance given to the users...

Complex adaptative systems and computational simulation in Archaeology

Directory of Open Access Journals (Sweden)

Salvador Pardo-Gordó

2017-07-01

Full Text Available Traditionally the concept of ‘complexity’ is used as a synonym for ‘complex society’, i.e., human groups with characteristics such as urbanism, inequalities, and hierarchy. The introduction of Nonlinear Systems and Complex Adaptive Systems to the discipline of archaeology has nuanced this concept. This theoretical turn has led to the rise of modelling as a method of analysis of historical processes. This work has a twofold objective: to present the theoretical current characterized by generative thinking in archaeology and to present a concrete application of agent-based modelling to an archaeological problem: the dispersal of the first ceramic production in the western Mediterranean.

Formal Modeling and Reconfiguration of User Interfaces for Reduction of Errors in Failure Handling of Complex Systems

NARCIS (Netherlands)

Weyers, Benjamin; Burkolter, Dina; Luther, Wolfram; Kluge, Annette

2012-01-01

Controlling and observing complex systems is central to the study of human-machine interaction. In our understanding, there is much to be gained from integrating formal modeling and analysis, including the reconfiguration of user interfaces, with the development of user interfaces with high

Modelling the complex dynamics of vegetation, livestock and rainfall ...

African Journals Online (AJOL)

Open Access DOWNLOAD FULL TEXT ... In this paper, we present mathematical models that incorporate ideas from complex systems theory to integrate several strands of rangeland theory in a hierarchical framework. ... Keywords: catastrophe theory; complexity theory; disequilibrium; hysteresis; moving attractors

MOIRA models and methodologies for assessing the effectiveness of countermeasures in complex aquatic systems contaminated by radionuclides

Energy Technology Data Exchange (ETDEWEB)

Monte, L. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Ambiente; Brittain, J.E. [Oslo Univ., Oslo (Norway); Zoological Museum, Oslo (Norway); Haakanson, L. [Uppsala Univ., Uppsala (Sweden). Inst. of Earth Science; Gallego Diaz, E. [Madrid Univ. Politecnica, Madrid (Spain). Dept. de Ingenieria Nuclear

1999-07-01

The present report is composed of a set of articles written by the partners of the MOIRA project (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas). The report describes models for predicting the behaviour of radionuclides in complex aquatic systems and the effects of countermeasures for their restoration. [Italian] Il rapporto contiene articoli preparati nell'ambito del progetto MOIRA (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas), che descrive alcuni modelli per la previsione del comportamento di radionuclidi in sistemi acquatici complessi e per la valutazione dell'effetto delle contromisure per il loro recupero.

MOIRA models and methodologies for assessing the effectiveness of countermeasures in complex aquatic systems contaminated by radionuclides

Energy Technology Data Exchange (ETDEWEB)

Monte, L [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Ambiente; Brittain, J E [Oslo Univ., Oslo (Norway); Zoological Museum, Oslo [Norway; Haakanson, L [Uppsala Univ., Uppsala (Sweden). Inst. of Earth Science; Gallego Diaz, E [Madrid Univ. Politecnica, Madrid (Spain). Dept. de Ingenieria Nuclear

1999-07-01

The present report is composed of a set of articles written by the partners of the MOIRA project (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas). The report describes models for predicting the behaviour of radionuclides in complex aquatic systems and the effects of countermeasures for their restoration. [Italian] Il rapporto contiene articoli preparati nell'ambito del progetto MOIRA (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas), che descrive alcuni modelli per la previsione del comportamento di radionuclidi in sistemi acquatici complessi e per la valutazione dell'effetto delle contromisure per il loro recupero.

Complex Time-Delay Systems Theory and Applications

CERN Document Server

Atay, Fatihcan M

2010-01-01

Time delays in dynamical systems arise as an inevitable consequence of finite speeds of information transmission. Realistic models increasingly demand the inclusion of delays in order to properly understand, analyze, design, and control real-life systems. The goal of this book is to present the state-of-the-art in research on time-delay dynamics in the framework of complex systems and networks. While the mathematical theory of delay equations is quite mature, its application to the particular problems of complex systems and complexity is a newly emerging field, and the present volume aims to play a pioneering role in this perspective. The chapters in this volume are authored by renowned experts and cover both theory and applications in a wide range of fields, with examples extending from neuroscience and biology to laser physics and vehicle traffic. Furthermore, all chapters include sufficient introductory material and extensive bibliographies, making the book a self-contained reference for both students and ...

Tools and techniques for developing policies for complex and uncertain systems.

Science.gov (United States)

Bankes, Steven C

2002-05-14

Agent-based models (ABM) are examples of complex adaptive systems, which can be characterized as those systems for which no model less complex than the system itself can accurately predict in detail how the system will behave at future times. Consequently, the standard tools of policy analysis, based as they are on devising policies that perform well on some best estimate model of the system, cannot be reliably used for ABM. This paper argues that policy analysis by using ABM requires an alternative approach to decision theory. The general characteristics of such an approach are described, and examples are provided of its application to policy analysis.

Promoting evaluation capacity building in a complex adaptive system.

Science.gov (United States)

Lawrenz, Frances; Kollmann, Elizabeth Kunz; King, Jean A; Bequette, Marjorie; Pattison, Scott; Nelson, Amy Grack; Cohn, Sarah; Cardiel, Christopher L B; Iacovelli, Stephanie; Eliou, Gayra Ostgaard; Goss, Juli; Causey, Lauren; Sinkey, Anne; Beyer, Marta; Francisco, Melanie

2018-04-10

This study provides results from an NSF funded, four year, case study about evaluation capacity building in a complex adaptive system, the Nanoscale Informal Science Education Network (NISE Net). The results of the Complex Adaptive Systems as a Model for Network Evaluations (CASNET) project indicate that complex adaptive system concepts help to explain evaluation capacity building in a network. The NISE Network was found to be a complex learning system that was supportive of evaluation capacity building through feedback loops that provided for information sharing and interaction. Participants in the system had different levels of and sources of evaluation knowledge. To be successful at building capacity, the system needed to have a balance between both centralized and decentralized control, coherence, redundancy, and diversity. Embeddedness of individuals within the system also provided support and moved the capacity of the system forward. Finally, success depended on attention being paid to the control of resources. Implications of these findings are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Large-Scale Transport Model Uncertainty and Sensitivity Analysis: Distributed Sources in Complex Hydrogeologic Systems

International Nuclear Information System (INIS)

Sig Drellack, Lance Prothro

2007-01-01

The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result of the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The

Complex Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

CERN Document Server

Baianu, I C

2004-01-01

Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

BlenX-based compositional modeling of complex reaction mechanisms

Directory of Open Access Journals (Sweden)

Judit Zámborszky

2010-02-01

Full Text Available Molecular interactions are wired in a fascinating way resulting in complex behavior of biological systems. Theoretical modeling provides a useful framework for understanding the dynamics and the function of such networks. The complexity of the biological networks calls for conceptual tools that manage the combinatorial explosion of the set of possible interactions. A suitable conceptual tool to attack complexity is compositionality, already successfully used in the process algebra field to model computer systems. We rely on the BlenX programming language, originated by the beta-binders process calculus, to specify and simulate high-level descriptions of biological circuits. The Gillespie's stochastic framework of BlenX requires the decomposition of phenomenological functions into basic elementary reactions. Systematic unpacking of complex reaction mechanisms into BlenX templates is shown in this study. The estimation/derivation of missing parameters and the challenges emerging from compositional model building in stochastic process algebras are discussed. A biological example on circadian clock is presented as a case study of BlenX compositionality.

Designing complex systems - a structured activity

NARCIS (Netherlands)

van der Veer, Gerrit C.; van Vliet, Johannes C.; Lenting, Bert; Olson, Gary M.; Schuon, Sue

1995-01-01

This paper concerns the development of complex systems from the point of view of design as a structure of activities, related both to the clients and the users. Several modeling approaches will be adopted for different aspects of design, and several views on design will be integrated. The proposed

Discontinuity and complexity in nonlinear physical systems

CERN Document Server

Baleanu, Dumitru; Luo, Albert

2014-01-01

This unique book explores recent developments in experimental research in this broad field, organized in four distinct sections. Part I introduces the reader to the fractional dynamics and Lie group analysis for nonlinear partial differential equations. Part II covers chaos and complexity in nonlinear Hamiltonian systems, important to understand the resonance interactions in nonlinear dynamical systems, such as Tsunami waves and wildfire propagations; as well as Lev flights in chaotic trajectories, dynamical system synchronization and DNA information complexity analysis. Part III examines chaos and periodic motions in discontinuous dynamical systems, extensively present in a range of systems, including piecewise linear systems, vibro-impact systems and drilling systems in engineering. And in Part IV, engineering and financial nonlinearity are discussed. The mechanism of shock wave with saddle-node bifurcation and rotating disk stability will be presented, and the financial nonlinear models will be discussed....

Modeling Complex Time Limits

Directory of Open Access Journals (Sweden)

Oleg Svatos

2013-01-01

Full Text Available In this paper we analyze complexity of time limits we can find especially in regulated processes of public administration. First we review the most popular process modeling languages. There is defined an example scenario based on the current Czech legislature which is then captured in discussed process modeling languages. Analysis shows that the contemporary process modeling languages support capturing of the time limit only partially. This causes troubles to analysts and unnecessary complexity of the models. Upon unsatisfying results of the contemporary process modeling languages we analyze the complexity of the time limits in greater detail and outline lifecycles of a time limit using the multiple dynamic generalizations pattern. As an alternative to the popular process modeling languages there is presented PSD process modeling language, which supports the defined lifecycles of a time limit natively and therefore allows keeping the models simple and easy to understand.

Recording information on protein complexes in an information management system.

Science.gov (United States)

Savitsky, Marc; Diprose, Jonathan M; Morris, Chris; Griffiths, Susanne L; Daniel, Edward; Lin, Bill; Daenke, Susan; Bishop, Benjamin; Siebold, Christian; Wilson, Keith S; Blake, Richard; Stuart, David I; Esnouf, Robert M

2011-08-01

The Protein Information Management System (PiMS) is a laboratory information management system (LIMS) designed for use with the production of proteins in a research environment. The software is distributed under the CCP4 licence, and so is available free of charge to academic laboratories. Like most LIMS, the underlying PiMS data model originally had no support for protein-protein complexes. To support the SPINE2-Complexes project the developers have extended PiMS to meet these requirements. The modifications to PiMS, described here, include data model changes, additional protocols, some user interface changes and functionality to detect when an experiment may have formed a complex. Example data are shown for the production of a crystal of a protein complex. Integration with SPINE2-Complexes Target Tracker application is also described. Copyright © 2011 Elsevier Inc. All rights reserved.

Summer School Mathematical Foundations of Complex Networked Information Systems

CERN Document Server

Fosson, Sophie; Ravazzi, Chiara

2015-01-01

Introducing the reader to the mathematics beyond complex networked systems, these lecture notes investigate graph theory, graphical models, and methods from statistical physics. Complex networked systems play a fundamental role in our society, both in everyday life and in scientific research, with applications ranging from physics and biology to economics and finance. The book is self-contained, and requires only an undergraduate mathematical background.

Innovative three-dimensional neutronics analyses directly coupled with cad models of geometrically complex fusion systems

International Nuclear Information System (INIS)

Sawan, M.; Wilson, P.; El-Guebaly, L.; Henderson, D.; Sviatoslavsky, G.; Bohm, T.; Kiedrowski, B.; Ibrahim, A.; Smith, B.; Slaybaugh, R.; Tautges, T.

2007-01-01

Fusion systems are, in general, geometrically complex requiring detailed three-dimensional (3-D) nuclear analysis. This analysis is required to address tritium self-sufficiency, nuclear heating, radiation damage, shielding, and radiation streaming issues. To facilitate such calculations, we developed an innovative computational tool that is based on the continuous energy Monte Carlo code MCNP and permits the direct use of CAD-based solid models in the ray-tracing. This allows performing the neutronics calculations in a model that preserves the geometrical details without any simplification, eliminates possible human error in modeling the geometry for MCNP, and allows faster design iterations. In addition to improving the work flow for simulating complex 3- D geometries, it allows a richer representation of the geometry compared to the standard 2nd order polynomial representation. This newly developed tool has been successfully tested for a detailed 40 degree sector benchmark of the International Thermonuclear Experimental Reactor (ITER). The calculations included determining the poloidal variation of the neutron wall loading, flux and nuclear heating in the divertor components, nuclear heating in toroidal field coils, and radiation streaming in the mid-plane port. The tool has been applied to perform 3-D nuclear analysis for several fusion designs including the ARIES Compact Stellarator (ARIES-CS), the High Average Power Laser (HAPL) inertial fusion power plant, and ITER first wall/shield (FWS) modules. The ARIES-CS stellarator has a first wall shape and a plasma profile that varies toroidally within each field period compared to the uniform toroidal shape in tokamaks. Such variation cannot be modeled analytically in the standard MCNP code. The impact of the complex helical geometry and the non-uniform blanket and divertor on the overall tritium breeding ratio and total nuclear heating was determined. In addition, we calculated the neutron wall loading variation in

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

Science.gov (United States)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and

Statistical physics of complex systems a concise introduction

CERN Document Server

Bertin, Eric

2016-01-01

This course-tested primer provides graduate students and non-specialists with a basic understanding of the concepts and methods of statistical physics and demonstrates their wide range of applications to interdisciplinary topics in the field of complex system sciences, including selected aspects of theoretical modeling in biology and the social sciences. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting units, and on the other to predict the macroscopic, collective behavior of the system considered from the perspective of the microscopic laws governing the dynamics of the individual entities. These two goals are essentially also shared by what is now called 'complex systems science', and as such, systems studied in the framework of statistical physics may be considered to be among the simplest examples of complex systems – while also offering a rather well developed mathematical treatment. The second ...

Dependability problems of complex information systems

CERN Document Server

Zamojski, Wojciech

2014-01-01

This monograph presents original research results on selected problems of dependability in contemporary Complex Information Systems (CIS). The ten chapters are concentrated around the following three aspects: methods for modelling of the system and its components, tasks ? or in more generic and more adequate interpretation, functionalities ? accomplished by the system and conditions for their correct realization in the dynamic operational environment. While the main focus is on theoretical advances and roadmaps for implementations of new technologies, a?much needed forum for sharing of the bes

Systems thinking and complexity: considerations for health promoting schools.

Science.gov (United States)

Rosas, Scott R

2017-04-01

The health promoting schools concept reflects a comprehensive and integrated philosophy to improving student and personnel health and well-being. Conceptualized as a configuration of interacting, interdependent parts connected through a web of relationships that form a whole greater than the sum of its parts, school health promotion initiatives often target several levels (e.g. individual, professional, procedural and policy) simultaneously. Health promoting initiatives, such as those operationalized under the whole school approach, include several interconnected components that are coordinated to improve health outcomes in complex settings. These complex systems interventions are embedded in intricate arrangements of physical, biological, ecological, social, political and organizational relationships. Systems thinking and characteristics of complex adaptive systems are introduced in this article to provide a perspective that emphasizes the patterns of inter-relationships associated with the nonlinear, dynamic and adaptive nature of complex hierarchical systems. Four systems thinking areas: knowledge, networks, models and organizing are explored as a means to further manage the complex nature of the development and sustainability of health promoting schools. Applying systems thinking and insights about complex adaptive systems can illuminate how to address challenges found in settings with both complicated (i.e. multi-level and multisite) and complex aspects (i.e. synergistic processes and emergent outcomes). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Computer Simulations and Theoretical Studies of Complex Systems: from complex fluids to frustrated magnets

Science.gov (United States)

Choi, Eunsong

Computer simulations are an integral part of research in modern condensed matter physics; they serve as a direct bridge between theory and experiment by systemactically applying a microscopic model to a collection of particles that effectively imitate a macroscopic system. In this thesis, we study two very differnt condensed systems, namely complex fluids and frustrated magnets, primarily by simulating classical dynamics of each system. In the first part of the thesis, we focus on ionic liquids (ILs) and polymers--the two complementary classes of materials that can be combined to provide various unique properties. The properties of polymers/ILs systems, such as conductivity, viscosity, and miscibility, can be fine tuned by choosing an appropriate combination of cations, anions, and polymers. However, designing a system that meets a specific need requires a concrete understanding of physics and chemistry that dictates a complex interplay between polymers and ionic liquids. In this regard, molecular dynamics (MD) simulation is an efficient tool that provides a molecular level picture of such complex systems. We study the behavior of Poly (ethylene oxide) (PEO) and the imidazolium based ionic liquids, using MD simulations and statistical mechanics. We also discuss our efforts to develop reliable and efficient classical force-fields for PEO and the ionic liquids. The second part is devoted to studies on geometrically frustrated magnets. In particular, a microscopic model, which gives rise to an incommensurate spiral magnetic ordering observed in a pyrochlore antiferromagnet is investigated. The validation of the model is made via a comparison of the spin-wave spectra with the neutron scattering data. Since the standard Holstein-Primakoff method is difficult to employ in such a complex ground state structure with a large unit cell, we carry out classical spin dynamics simulations to compute spin-wave spectra directly from the Fourier transform of spin trajectories. We

THE PROBLEMS OF MODELING THE RELIABILITY STRUCTURE OF THE COMPLEX TECHNICAL SYSTEM ON THE BASIS OF A STEAM‐WATER SYSTEM OF THE ENGINE ROOM

Directory of Open Access Journals (Sweden)

Leszek CHYBOWSKI

2012-04-01

Full Text Available In the paper the concept of a system structure with particular emphasis on the reliability structure has been presented. Advantages and disadvantages of modeling the reliability structure of a system using reliability block diagrams (RBD have been shown. RBD models of a marine steam‐water system constructed according to the concept of ‘multi‐component’, ‘one component’ and mixed models have been discussed. Critical remarks on the practical application of models which recognize only the structural surplus have been dealt with. The significant value of the model by professors Smalko and Jaźwiński called by them ‘default reliability structure’ has been pointed out. The necessity of building a new type of models: quality‐quantity, useful in the methodology developed by the author's multi-criteria analysis of importance of elements in the reliability structure of complex technical systems.

Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model

International Nuclear Information System (INIS)

Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan

2017-01-01

Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

Science.gov (United States)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Thinking about complexity in health: A systematic review of the key systems thinking and complexity ideas in health.

Science.gov (United States)

Rusoja, Evan; Haynie, Deson; Sievers, Jessica; Mustafee, Navonil; Nelson, Fred; Reynolds, Martin; Sarriot, Eric; Swanson, Robert Chad; Williams, Bob

2018-01-30

As the Sustainable Development Goals are rolled out worldwide, development leaders will be looking to the experiences of the past to improve implementation in the future. Systems thinking and complexity science (ST/CS) propose that health and the health system are composed of dynamic actors constantly evolving in response to each other and their context. While offering practical guidance for steering the next development agenda, there is no consensus as to how these important ideas are discussed in relation to health. This systematic review sought to identify and describe some of the key terms, concepts, and methods in recent ST/CS literature. Using the search terms "systems thinkin * AND health OR complexity theor* AND health OR complex adaptive system* AND health," we identified 516 relevant full texts out of 3982 titles across the search period (2002-2015). The peak number of articles were published in 2014 (83) with journals specifically focused on medicine/healthcare (265) and particularly the Journal of Evaluation in Clinical Practice (37) representing the largest number by volume. Dynamic/dynamical systems (n = 332), emergence (n = 294), complex adaptive system(s) (n = 270), and interdependent/interconnected (n = 263) were the most common terms with systems dynamic modelling (58) and agent-based modelling (43) as the most common methods. The review offered several important conclusions. First, while there was no core ST/CS "canon," certain terms appeared frequently across the reviewed texts. Second, even as these ideas are gaining traction in academic and practitioner communities, most are concentrated in a few journals. Finally, articles on ST/CS remain largely theoretical illustrating the need for further study and practical application. Given the challenge posed by the next phase of development, gaining a better understanding of ST/CS ideas and their use may lead to improvements in the implementation and practice of the Sustainable Development

Multi-Level Formation of Complex Software Systems

Directory of Open Access Journals (Sweden)

Hui Li

2016-05-01

Full Text Available We present a multi-level formation model for complex software systems. The previous works extract the software systems to software networks for further studies, but usually investigate the software networks at the class level. In contrast to these works, our treatment of software systems as multi-level networks is more realistic. In particular, the software networks are organized by three levels of granularity, which represents the modularity and hierarchy in the formation process of real-world software systems. More importantly, simulations based on this model have generated more realistic structural properties of software networks, such as power-law, clustering and modularization. On the basis of this model, how the structure of software systems effects software design principles is then explored, and it could be helpful for understanding software evolution and software engineering practices.

QMU as an approach to strengthening the predictive capabilities of complex models.

Energy Technology Data Exchange (ETDEWEB)

Gray, Genetha Anne.; Boggs, Paul T.; Grace, Matthew D.

2010-09-01

Complex systems are made up of multiple interdependent parts, and the behavior of the entire system cannot always be directly inferred from the behavior of the individual parts. They are nonlinear and system responses are not necessarily additive. Examples of complex systems include energy, cyber and telecommunication infrastructures, human and animal social structures, and biological structures such as cells. To meet the goals of infrastructure development, maintenance, and protection for cyber-related complex systems, novel modeling and simulation technology is needed. Sandia has shown success using M&S in the nuclear weapons (NW) program. However, complex systems represent a significant challenge and relative departure from the classical M&S exercises, and many of the scientific and mathematical M&S processes must be re-envisioned. Specifically, in the NW program, requirements and acceptable margins for performance, resilience, and security are well-defined and given quantitatively from the start. The Quantification of Margins and Uncertainties (QMU) process helps to assess whether or not these safety, reliability and performance requirements have been met after a system has been developed. In this sense, QMU is used as a sort of check that requirements have been met once the development process is completed. In contrast, performance requirements and margins may not have been defined a priori for many complex systems, (i.e. the Internet, electrical distribution grids, etc.), particularly not in quantitative terms. This project addresses this fundamental difference by investigating the use of QMU at the start of the design process for complex systems. Three major tasks were completed. First, the characteristics of the cyber infrastructure problem were collected and considered in the context of QMU-based tools. Second, UQ methodologies for the quantification of model discrepancies were considered in the context of statistical models of cyber activity. Third

Top-down models in biology: explanation and control of complex living systems above the molecular level.

Science.gov (United States)

Pezzulo, Giovanni; Levin, Michael

2016-11-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).

Model order reduction for complex high-tech systems

NARCIS (Netherlands)

Lutowska, A.; Hochstenbach, M.E.; Schilders, W.H.A.; Michielsen, B.; Poirier, J.R.

2012-01-01

This paper presents a computationally efficient model order reduction (MOR) technique for interconnected systems. This MOR technique preserves block structures and zero blocks and exploits separate MOR approximations for the individual sub-systems in combination with low rank approximations for the

Performance modeling & simulation of complex systems (A systems engineering design & analysis approach)

Science.gov (United States)

Hall, Laverne

1995-01-01

Modeling of the Multi-mission Image Processing System (MIPS) will be described as an example of the use of a modeling tool to design a distributed system that supports multiple application scenarios. This paper examines: (a) modeling tool selection, capabilities, and operation (namely NETWORK 2.5 by CACl), (b) pointers for building or constructing a model and how the MIPS model was developed, (c) the importance of benchmarking or testing the performance of equipment/subsystems being considered for incorporation the design/architecture, (d) the essential step of model validation and/or calibration using the benchmark results, (e) sample simulation results from the MIPS model, and (f) how modeling and simulation analysis affected the MIPS design process by having a supportive and informative impact.

A coupled mass transfer and surface complexation model for uranium (VI) removal from wastewaters

International Nuclear Information System (INIS)

Lenhart, J.; Figueroa, L.A.; Honeyman, B.D.

1994-01-01

A remediation technique has been developed for removing uranium (VI) from complex contaminated groundwater using flake chitin as a biosorbent in batch and continuous flow configurations. With this system, U(VI) removal efficiency can be predicted using a model that integrates surface complexation models, mass transport limitations and sorption kinetics. This integration allows the reactor model to predict removal efficiencies for complex groundwaters with variable U(VI) concentrations and other constituents. The system has been validated using laboratory-derived kinetic data in batch and CSTR systems to verify the model predictions of U(VI) uptake from simulated contaminated groundwater

Complex scaling in the cluster model

International Nuclear Information System (INIS)

Kruppa, A.T.; Lovas, R.G.; Gyarmati, B.

1987-01-01

To find the positions and widths of resonances, a complex scaling of the intercluster relative coordinate is introduced into the resonating-group model. In the generator-coordinate technique used to solve the resonating-group equation the complex scaling requires minor changes in the formulae and code. The finding of the resonances does not need any preliminary guess or explicit reference to any asymptotic prescription. The procedure is applied to the resonances in the relative motion of two ground-state α clusters in 8 Be, but is appropriate for any systems consisting of two clusters. (author) 23 refs.; 5 figs

Extending Life Concepts to Complex Systems

Directory of Open Access Journals (Sweden)

Jean Le Fur

2013-01-01

Full Text Available There is still no consensus definition of complex systems. This article explores, as a heuristic approach, the possibility of using notions associated with life as transversal concepts for defining complex systems. This approach is developed within a general classification of systems, with complex systems considered as a general ‘living things’ category and living organisms as a specialised class within this category. Concepts associated with life are first explored in the context of complex systems: birth, death and lifetime, adaptation, ontogeny and growth, reproduction. Thereafter, a refutation approach is used to test the proposed classification against a set of diverse systems, including a reference case, edge cases and immaterial complex systems. The summary of this analysis is then used to generate a definition of complex systems, based on the proposal, and within the background of cybernetics, complex adaptive systems and biology. Using notions such as ‘birth’ or ‘lifespan’ as transversal concepts may be of heuristic value for the generic characterization of complex systems, opening up new lines of research for improving their definition.

MODELING OF OPERATION MODES OF SHIP POWER PLANT OF COMBINED PROPULSION COMPLEX WITH CONTROL SYSTEM BASED ON ELECTRONIC CONTROLLERS

Directory of Open Access Journals (Sweden)

E. A. Yushkov

2016-12-01

Full Text Available Purpose. Designing of diagrams to optimize mathematic model of the ship power plant (SPP combined propulsion complexes (CPC for decreasing operational loss and increasing fuel efficiency with simultaneous load limiting on medium revolutions diesel generator (MRDG by criterion reducing of wear and increasing operation time between repairs. Methodology. After analyzing of ship power plant modes of CPC proposed diagrams to optimize mathematic model of the above mentioned complex. The model based on using of electronic controllers in automatic regulation and control systems for diesel and thruster which allow to actualize more complicated control algorithm with viewpoint of increasing working efficiency of ship power plant at normal and emergency modes. Results. Determined suitability of comparative computer modeling in MatLab Simulink for building of imitation model objects based on it block diagrams and mathematic descriptions. Actualized diagrams to optimize mathematic model of the ship’s power plant (SPP combined propulsion complexes (CPC with Azipod system in MatLab Simulink software package Ships_CPC for decreasing operational loss and increasing fuel efficiency with simultaneous load limiting on medium revolutions diesel generator (MRDG by criterion reducing of wear and increasing operation time between repairs. The function blocks of proposed complex are the main structural units which allow to investigate it normal and emergency modes. Originality. This model represents a set of functional blocks of the components SPP CPC, built on the principle of «input-output». For example, the function boxes outputs of PID-regulators of MRDG depends from set excitation voltage and rotating frequency that in turn depends from power-station load and respond that is a ship moving or dynamically positioning, and come on input (inputs of thruster rotating frequency PID-regulator models. Practical value. The results of researches planned to use in

Application of an electronic bulletin board, as a mechanism of coordination of actions in complex systems - reference model

Directory of Open Access Journals (Sweden)

Katarzyna Grzybowska

2015-06-01

Full Text Available Background: In her previous research, the author of this publication indicates that coordination is a dependent variable which has a great driving force and is a very unstable factor. This results in the fact that all of the actions connected with coordination have an impact on other factors of cooperation as well as the integration of the enterprises in the structures of a supply chain type structure. Material and methods:  The article has been divided into two basic parts. The first part regards the reference models in complex systems (supply chain systems. They can constitute a starting point for the modelling of target processes in the built supply chain structure. The second part presents template process models (Reference Models for selected action coordination mechanisms during enterprise cooperation. The aim of the article is the presentation the model an Electronic Bulletin Board (EBB, as a mechanism of coordination of actions in complex systems. Results: The article was prepared on the basis of literature from the researched area. The material was also prepared on the basis of interviews with practitioners. They have allowed for the preparation of template process models (Reference Models for selected action coordination methods in the supply chain. Conclusions: The result of the work is a prepared model as well as its description in the use of IDEF0. The presented model is a demonstrative model. The proposed reference model makes it possible to define the parameters of a selected mechanism of coordination of actions, and forms a basis for affecting the progression of the process through an analysis of values of identified parameters. The parameterization of elements constitutes the foundation for the monitoring of the process via 1 unambiguous identification of the object of monitoring and 2 analysis of different variants of the progression of the process.

System crash as dynamics of complex networks.

Science.gov (United States)

Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

2016-10-18

Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

6th International Conference on Complex Systems Design & Management

CERN Document Server

Bocquet, Jean-Claude; Bonjour, Eric; Krob, Daniel

2016-01-01

This book contains all refereed papers that were accepted to the sixth edition of the « Complex Systems Design & Management Paris » (CSD&M Paris 2015) international conference which took place in Paris (France) on November 23-25, 2015. These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (aeronautics & aerospace, defense & security, electronics & robotics, energy & environment, health & welfare, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, systems modeling tools) and systems types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2015 conference is organized under the guidance of the CESAMES non-profit organization, address...

Engineering Complex Embedded Systems with State Analysis and the Mission Data System

Science.gov (United States)

Ingham, Michel D.; Rasmussen, Robert D.; Bennett, Matthew B.; Moncada, Alex C.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.

Work Practice Simulation of Complex Human-Automation Systems in Safety Critical Situations: The Brahms Generalized berlingen Model

Science.gov (United States)

Clancey, William J.; Linde, Charlotte; Seah, Chin; Shafto, Michael

2013-01-01

anomalous condition, as occurred during the accident. Brahms-GUeM thus implicitly defines a class of scenarios, which include as an instance what occurred at Überlingen. Brahms-GUeM is a modeling framework enabling "what if" analysis of alternative work system configurations and thus facilitating design of alternative operations concepts. It enables subsequent adaption (reusing simulation components) for modeling and simulating NextGen scenarios. This project demonstrates that BRAHMS provides the capacity to model the complexity of air transportation systems, going beyond idealized and simple flights to include for example the interaction of pilots and ATCOs. The research shows clearly that verification and validation must include the entire work system, on the one hand to check that mechanisms exist to handle failures of communication and alerting subsystems and/or failures of people to notice, comprehend, or communicate problematic (unsafe) situations; but also to understand how people must use their own judgment in relating fallible systems like TCAS to other sources of information and thus to evaluate how the unreliability of automation affects system safety. The simulation shows in particular that distributed agents (people and automated systems) acting without knowledge of each others' actions can create a complex, dynamic system whose interactive behavior is unexpected and is changing too quickly to comprehend and control.

Unified Computational Intelligence for Complex Systems

CERN Document Server

Seiffertt, John

2010-01-01

Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e

A flexible object-based software framework for modeling complex systems with interacting natural and societal processes.

Energy Technology Data Exchange (ETDEWEB)

Christiansen, J. H.

2000-06-15

The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations. The DIAS infrastructure makes it feasible to build and manipulate complex simulation scenarios in which many thousands of objects can interact via dozens to hundreds of concurrent dynamic processes. The flexibility and extensibility of the DIAS software infrastructure stem mainly from (1) the abstraction of object behaviors, (2) the encapsulation and formalization of model functionality, and (3) the mutability of domain object contents. DIAS simulation objects are inherently capable of highly flexible and heterogeneous spatial realizations. Geospatial graphical representation of DIAS simulation objects is addressed via the GeoViewer, an object-based GIS toolkit application developed at ANL. DIAS simulation capabilities have been extended by inclusion of societal process models generated by the Framework for Addressing Cooperative Extended Transactions (FACET), another object-based framework developed at Argonne National Laboratory. By using FACET models to implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations, it has become possible to conveniently address a broad range of issues involving interaction and feedback among natural and societal processes. Example DIAS application areas discussed in this paper include a dynamic virtual oceanic environment, detailed simulation of clinical, physiological, and logistical aspects of health care delivery, and studies of agricultural sustainability of urban centers under environmental stress in ancient Mesopotamia.

Transition Manifolds of Complex Metastable Systems

Science.gov (United States)

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-04-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Complex Systems: An Introduction

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 14; Issue 9. Complex Systems: An Introduction - Anthropic Principle, Terrestrial Complexity, Complex Materials. V K Wadhawan. General Article Volume 14 Issue 9 September 2009 pp 894-906 ...

Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems

Science.gov (United States)

Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.

2018-01-01

The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.

Equation-free modeling unravels the behavior of complex ecological systems

Science.gov (United States)

DeAngelis, Donald L.; Yurek, Simeon

2015-01-01

Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.

Complex Systems and Dependability

CERN Document Server

Zamojski, Wojciech; Sugier, Jaroslaw

2012-01-01

Typical contemporary complex system is a multifaceted amalgamation of technical, information, organization, software and human (users, administrators and management) resources. Complexity of such a system comes not only from its involved technical and organizational structure but mainly from complexity of information processes that must be implemented in the operational environment (data processing, monitoring, management, etc.). In such case traditional methods of reliability analysis focused mainly on technical level are usually insufficient in performance evaluation and more innovative meth

Nonparametric Bayesian Modeling of Complex Networks

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Mørup, Morten

2013-01-01

an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

Low-complexity controllers for time-delay systems

CERN Document Server

Özbay, Hitay; Bonnet, Catherine; Mounier, Hugues

2014-01-01

This volume in the newly established series Advances in Delays and Dynamics (ADD@S) provides a collection of recent results on the design and analysis of Low Complexity Controllers for Time Delay Systems. A widely used indirect method to obtain low order controllers for time delay systems is to design a controller for the reduced order model of the plant. In the dual indirect approach, an infinite dimensional controller is designed first for the original plant model; then, the controller is approximated by keeping track of the degradation in performance and stability robustness measures. The present volume includes new techniques used at different stages of the indirect approach. It also includes new direct design methods for fixed structure and low order controllers. On the other hand, what is meant by low complexity controller is not necessarily low order controller. For example, Smith predictor or similar type of controllers include a copy of the plant internally in the controller, so they are technically ...

Clinical Complexity in Medicine: A Measurement Model of Task and Patient Complexity.

Science.gov (United States)

Islam, R; Weir, C; Del Fiol, G

2016-01-01

Complexity in medicine needs to be reduced to simple components in a way that is comprehensible to researchers and clinicians. Few studies in the current literature propose a measurement model that addresses both task and patient complexity in medicine. The objective of this paper is to develop an integrated approach to understand and measure clinical complexity by incorporating both task and patient complexity components focusing on the infectious disease domain. The measurement model was adapted and modified for the healthcare domain. Three clinical infectious disease teams were observed, audio-recorded and transcribed. Each team included an infectious diseases expert, one infectious diseases fellow, one physician assistant and one pharmacy resident fellow. The transcripts were parsed and the authors independently coded complexity attributes. This baseline measurement model of clinical complexity was modified in an initial set of coding processes and further validated in a consensus-based iterative process that included several meetings and email discussions by three clinical experts from diverse backgrounds from the Department of Biomedical Informatics at the University of Utah. Inter-rater reliability was calculated using Cohen's kappa. The proposed clinical complexity model consists of two separate components. The first is a clinical task complexity model with 13 clinical complexity-contributing factors and 7 dimensions. The second is the patient complexity model with 11 complexity-contributing factors and 5 dimensions. The measurement model for complexity encompassing both task and patient complexity will be a valuable resource for future researchers and industry to measure and understand complexity in healthcare.

Encyclopedia of Complexity and Systems Science

CERN Document Server

Meyers, Robert A

2009-01-01

Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...

7th International Conference on Complex Systems Design & Management

CERN Document Server

Goubault, Eric; Krob, Daniel; Stephan, François

2017-01-01

This book contains all refereed papers that were accepted to the seventh edition of the international conference « Complex Systems Design & Management Paris» (CSD&M Paris 2016) which took place in Paris (France) on the December 13-14, 2016 These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (aeronautic & aerospace, defense & security, electronics & robotics, energy & environment, healthcare & welfare services, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, system is modeling tools) and system types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2016 conference is organized under the guidance of the CESAMES non-profit orga...

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Welch, Gregory Francis [UNC-Chapel Hill/University of Central Florida; Zhang, Jinghe [UNC-Chapel Hill/Virginia Tech

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuities caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.

Complex multidisciplinary system composition for aerospace vehicle conceptual design

Science.gov (United States)

Gonzalez, Lex

Although, there exists a vast amount of work concerning the analysis, design, integration of aerospace vehicle systems, there is no standard for how this data and knowledge should be combined in order to create a synthesis system. Each institution creating a synthesis system has in house vehicle and hardware components they are attempting to model and proprietary methods with which to model them. This leads to the fact that synthesis systems begin as one-off creations meant to answer a specific problem. As the scope of the synthesis system grows to encompass more and more problems, so does its size and complexity; in order for a single synthesis system to answer multiple questions the number of methods and method interface must increase. As a means to curtail the requirement that the increase of an aircraft synthesis systems capability leads to an increase in its size and complexity, this research effort focuses on the idea that each problem in aerospace requires its own analysis framework. By focusing on the creation of a methodology which centers on the matching of an analysis framework towards the problem being solved, the complexity of the analysis framework is decoupled from the complexity of the system that creates it. The derived methodology allows for the composition of complex multi-disciplinary systems (CMDS) through the automatic creation and implementation of system and disciplinary method interfaces. The CMDS Composition process follows a four step methodology meant to take a problem definition and progress towards the creation of an analysis framework meant to answer said problem. The unique implementation of the CMDS Composition process take user selected disciplinary analysis methods and automatically integrates them, together in order to create a syntactically composable analysis framework. As a means of assessing the validity of the CMDS Composition process a prototype system (AVDDBMS) has been developed. AVD DBMS has been used to model the

Distributed redundancy and robustness in complex systems

KAUST Repository

Randles, Martin

2011-03-01

The uptake and increasing prevalence of Web 2.0 applications, promoting new large-scale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an \\'open-ended\\' manner where not all states of the system are prescribed at design-time. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components\\' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy. © 2010 Elsevier Inc.

Complex matrix model duality

International Nuclear Information System (INIS)

Brown, T.W.

2010-11-01

The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super- Yang-Mills. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich- Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces. (orig.)

Complex matrix model duality

Energy Technology Data Exchange (ETDEWEB)

Brown, T.W.

2010-11-15

The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super- Yang-Mills. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich- Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces. (orig.)

Adaptive generalized combination complex synchronization of uncertain real and complex nonlinear systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Shi-bing, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xing-yuan, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xiu-you [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Zhou, Yu-fei [College of Electrical Engineering and Automation, Anhui University, Hefei 230601 (China)

2016-04-15

With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complex Lü system, and hyperchaotic complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.

Complexity, Analysis and Control of Singular Biological Systems

CERN Document Server

Zhang, Qingling; Zhang, Xue

2012-01-01

Complexity, Analysis and Control of Singular Biological Systems follows the control of real-world biological systems at both ecological and phyisological levels concentrating on the application of now-extensively-investigated singular system theory. Much effort has recently been dedicated to the modelling and analysis of developing bioeconomic systems and the text establishes singular examples of these, showing how proper control can help to maintain sustainable economic development of biological resources. The book begins from the essentials of singular systems theory and bifurcations before tackling  the use of various forms of control in singular biological systems using examples including predator-prey relationships and viral vaccination and quarantine control. Researchers and graduate students studying the control of complex biological systems are shown how a variety of methods can be brought to bear and practitioners working with the economics of biological systems and their control will also find the ...

Management of complex dynamical systems

Science.gov (United States)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

A Complex Systems Perspective of Risk Mitigation and Modeling in Development and Acquisition Programs

Science.gov (United States)

2016-04-30

current methodologies used in risk assessment are heavily subjective and inaccurate in various life cycle phases of complex engineered systems. The...complexity content of the system. Many of the system’s life cycle risks are currently assessed subjectively by imprecise methodologies such as color...evaluated for multiple entities such as galaxies, stars, planets , plants, animals, societies, and technological systems, and also has been mapped

Automated design of complex dynamic systems.

Directory of Open Access Journals (Sweden)

Michiel Hermans

Full Text Available Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems.

Simulating Complex Window Systems using BSDF Data

Energy Technology Data Exchange (ETDEWEB)

Konstantoglou, Maria; Jonsson, Jacob; Lee, Eleanor

2009-06-22

Nowadays, virtual models are commonly used to evaluate the performance of conventional window systems. Complex fenestration systems can be difficult to simulate accurately not only because of their geometry but also because of their optical properties that scatter light in an unpredictable manner. Bi-directional Scattering Distribution Functions (BSDF) have recently been developed based on a mixture of measurements and modelling to characterize the optics of such systems. This paper describes the workflow needed to create then use these BSDF datasets in the Radiance lighting simulation software. Limited comparisons are made between visualizations produced using the standard ray-tracing method, the BSDF method, and that taken in a full-scale outdoor mockup.

Dependency visualization for complex system understanding

Energy Technology Data Exchange (ETDEWEB)

Smart, J. Allison Cory [Univ. of California, Davis, CA (United States)

1994-09-01

With the volume of software in production use dramatically increasing, the importance of software maintenance has become strikingly apparent. Techniques now sought and developed for reverse engineering and design extraction and recovery. At present, numerous commercial products and research tools exist which are capable of visualizing a variety of programming languages and software constructs. The list of new tools and services continues to grow rapidly. Although the scope of the existing commercial and academic product set is quite broad, these tools still share a common underlying problem. The ability of each tool to visually organize object representations is increasingly impaired as the number of components and component dependencies within systems increases. Regardless of how objects are defined, complex ``spaghetti`` networks result in nearly all large system cases. While this problem is immediately apparent in modem systems analysis involving large software implementations, it is not new. As will be discussed in Chapter 2, related problems involving the theory of graphs were identified long ago. This important theoretical foundation provides a useful vehicle for representing and analyzing complex system structures. While the utility of directed graph based concepts in software tool design has been demonstrated in literature, these tools still lack the capabilities necessary for large system comprehension. This foundation must therefore be expanded with new organizational and visualization constructs necessary to meet this challenge. This dissertation addresses this need by constructing a conceptual model and a set of methods for interactively exploring, organizing, and understanding the structure of complex software systems.

Synchronization in node of complex networks consist of complex chaotic system

Energy Technology Data Exchange (ETDEWEB)

Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)

2014-07-15

A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

Modeling complex and multi-component food systems in molecular dynamics simulations on the example of chocolate conching.

Science.gov (United States)

Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko

2014-02-01

Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively

State analysis requirements database for engineering complex embedded systems

Science.gov (United States)

Bennett, Matthew B.; Rasmussen, Robert D.; Ingham, Michel D.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer's intent, potentially leading to software errors. This problem is addressed by a systems engineering tool called the State Analysis Database, which provides a tool for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using the State Analysis Database.

What is complex in the complex world? Niklas Luhmann and the theory of social systems

Directory of Open Access Journals (Sweden)

Clarissa Eckert Baeta Neves

Full Text Available This paper discusses Niklas Luhmann's understanding of complexity, its function in the theory and the different ways of its use. It starts with the paradigmatic change that occurred in the field of general Science, with the rupture of the Newtonian model. In the 20th century, the paradigm of order, symmetry, regularity, regulation of the intellect to things, collapses.Based on new formulations of Physics, Chemistry, etc., a new universe is built on bases radically opposed to those of modern Science.Chaos, the procedural irreversibility, indeterminism, the observer and the complexity are rehabilitated.This new conceptual context served as substratum to Niklas Luhmann's theoretical reflection.With his Theory of Social Systems, he proposes the reduction of the world's complexity.Social systems have the function of reducing complexity because of their difference in relation to the environment.On the other hand, the reduction of complexity also creates its own complexity. Luhmann defines complexity as the moment when it is not possible anymore for each element to relate at any moment with all the others. Complexity forces the selection, what means contingency and risk. Luhmann expands the concept of complexity when he introduces the figure of the observer and the distinction of complexity as a unit of a multiplicity. He also deals with the limit of relations in connection, the time factor, the self-reference of operations and the representation of complexity in the form of sense. To conclude, the paper discusses the complexity in the system of science, the way it reduces internal and external complexity, in accordance in its own operative basis.

Simulation in Complex Modelling

DEFF Research Database (Denmark)

Nicholas, Paul; Ramsgaard Thomsen, Mette; Tamke, Martin

2017-01-01

This paper will discuss the role of simulation in extended architectural design modelling. As a framing paper, the aim is to present and discuss the role of integrated design simulation and feedback between design and simulation in a series of projects under the Complex Modelling framework. Complex...... performance, engage with high degrees of interdependency and allow the emergence of design agency and feedback between the multiple scales of architectural construction. This paper presents examples for integrated design simulation from a series of projects including Lace Wall, A Bridge Too Far and Inflated...... Restraint developed for the research exhibition Complex Modelling, Meldahls Smedie Gallery, Copenhagen in 2016. Where the direct project aims and outcomes have been reported elsewhere, the aim for this paper is to discuss overarching strategies for working with design integrated simulation....

Size and complexity in model financial systems

Science.gov (United States)

Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M.

2012-01-01

The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in “confidence” in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020

The meganism behind internally generated centennial-to-millennial scale climate variability in an earth system model of intermediate complexity

NARCIS (Netherlands)

Friedrich, T.; Timmermann, A.; Menviel, L.; Elison Timm, O.; Mouchet, A.; Roche, D.M.V.A.P.

2010-01-01

The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (∼22.1 )

European Conference on Complex Systems 2012

CERN Document Server

Kirkilionis, Markus; Nicolis, Gregoire

2013-01-01

The European Conference on Complex Systems, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. ECCS'12, its ninth edition, took place in Brussels, during the first week of September 2012. It gathered about 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. More specifically, the following tracks were covered:  1. Foundations of Complex Systems 2. Complexity, Information and Computation 3. Prediction, Policy and Planning, Environment 4. Biological Complexity 5. Interacting Populations, Collective Behavior 6. Social Systems, Economics and Finance This book contains a selection of the contributions presented at the conference and its satellite meetings. Its contents reflect the extent, diversity and richness of research areas in the field, both fundamental and applied.  

Quantum-information processing in disordered and complex quantum systems

International Nuclear Information System (INIS)

Sen, Aditi; Sen, Ujjwal; Ahufinger, Veronica; Briegel, Hans J.; Sanpera, Anna; Lewenstein, Maciej

2006-01-01

We study quantum information processing in complex disordered many body systems that can be implemented by using lattices of ultracold atomic gases and trapped ions. We demonstrate, first in the short range case, the generation of entanglement and the local realization of quantum gates in a disordered magnetic model describing a quantum spin glass. We show that in this case it is possible to achieve fidelities of quantum gates higher than in the classical case. Complex systems with long range interactions, such as ions chains or dipolar atomic gases, can be used to model neural network Hamiltonians. For such systems, where both long range interactions and disorder appear, it is possible to generate long range bipartite entanglement. We provide an efficient analytical method to calculate the time evolution of a given initial state, which in turn allows us to calculate its quantum correlations

Modelling methodology for assessing the impact of new technology on complex sociotechnical systems

CSIR Research Space (South Africa)

Oosthuizen, R

2014-11-01

Full Text Available Developing complex sociotechnical systems often involves integrating new technology into existing systems by applying systems engineering processes. This requires an understanding of the problem space and the possible impact of the new technology...

Formal heterogeneous system modeling with SystemC

DEFF Research Database (Denmark)

Niaki, Seyed Hosein Attarzadeh; Jakobsen, Mikkel Koefoed; Sulonen, Tero

2012-01-01

Electronic System Level (ESL) design of embedded systems proposes raising the abstraction level of the design entry to cope with the increasing complexity of such systems. To exploit the benefits of ESL, design languages should allow specification of models which are a) heterogeneous, to describe...

Performance evaluation of functioning of natural-industrial system of mining-processing complex with help of analytical and mathematical models

Science.gov (United States)

Bosikov, I. I.; Klyuev, R. V.; Revazov, V. Ch; Pilieva, D. E.

2018-03-01

The article describes research and analysis of hazardous processes occurring in the natural-industrial system and effectiveness assessment of its functioning using mathematical models. Studies of the functioning regularities of the natural and industrial system are becoming increasingly relevant in connection with the formulation of the task of modernizing production and the economy of Russia as a whole. In connection with a significant amount of poorly structured data, it is complicated by regulations for the effective functioning of production processes, social and natural complexes, under which a sustainable development of the natural-industrial system of the mining and processing complex would be ensured. Therefore, the scientific and applied problems, the solution of which allows one to formalize the hidden structural functioning patterns of the natural-industrial system and to make managerial decisions of organizational and technological nature to improve the efficiency of the system, are very relevant.

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany

Energy Technology Data Exchange (ETDEWEB)

Bonten, Luc T.C., E-mail: luc.bonten@wur.nl [Alterra-Wageningen UR, Soil Science Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands); Groenenberg, Jan E. [Alterra-Wageningen UR, Soil Science Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands); Meesenburg, Henning [Northwest German Forest Research Station, Abt. Umweltkontrolle, Sachgebiet Intensives Umweltmonitoring, Goettingen (Germany); Vries, Wim de [Alterra-Wageningen UR, Soil Science Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands)

2011-10-15

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well. - Highlights: > Surface complexation models can be well applied in field studies. > Soil chemistry under a forest site is adequately modelled using generic parameters. > The model is easily extended with extra elements within the existing framework. > Surface complexation models can show the linkages between major soil chemistry and trace element behaviour. - Surface complexation models with generic parameters make calibration of sorption superfluous in dynamic modelling of deposition impacts on soil chemistry under nature areas.

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany

International Nuclear Information System (INIS)

Bonten, Luc T.C.; Groenenberg, Jan E.; Meesenburg, Henning; Vries, Wim de

2011-01-01

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well. - Highlights: → Surface complexation models can be well applied in field studies. → Soil chemistry under a forest site is adequately modelled using generic parameters. → The model is easily extended with extra elements within the existing framework. → Surface complexation models can show the linkages between major soil chemistry and trace element behaviour. - Surface complexation models with generic parameters make calibration of sorption superfluous in dynamic modelling of deposition impacts on soil chemistry under nature areas.

Complex biological and bio-inspired systems

Energy Technology Data Exchange (ETDEWEB)

Ecke, Robert E [Los Alamos National Laboratory

2009-01-01

The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

Science.gov (United States)

Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

2014-01-27

The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W

Reduction of Subjective and Objective System Complexity

Science.gov (United States)

Watson, Michael D.

2015-01-01

Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached

Impact of delayed information in sub-second complex systems

Directory of Open Access Journals (Sweden)

Pedro D. Manrique

Full Text Available What happens when you slow down the delivery of information in large-scale complex systems that operate faster than the blink of an eye? This question just adopted immediate commercial, legal and political importance following U.S. regulators’ decision to allow an intentional 350 microsecond delay to be added in the ultrafast network of financial exchanges. However there is still no scientific understanding available to policymakers of the potential system-wide impact of such delays. Here we take a first step in addressing this question using a minimal model of a population of competing, heterogeneous, adaptive agents which has previously been shown to produce similar statistical features to real markets. We find that while certain extreme system-level behaviors can be prevented by such delays, the duration of others is increased. This leads to a highly non-trivial relationship between delays and system-wide instabilities which warrants deeper empirical investigation. The generic nature of our model suggests there should be a fairly wide class of complex systems where such delay-driven extreme behaviors can arise, e.g. sub-second delays in brain function possibly impacting individuals’ behavior, and sub-second delays in navigational systems potentially impacting the safety of driverless vehicles. Keywords: Ultra-fast networks, Temporal perturbation, Competition, Modeling

Relaxation and Diffusion in Complex Systems

CERN Document Server

Ngai, K L

2011-01-01

Relaxation and Diffusion in Complex Systems comprehensively presents a variety of experimental evidences of universal relaxation and diffusion properties in complex materials and systems. The materials discussed include liquids, glasses, colloids, polymers, rubbers, plastic crystals and aqueous mixtures, as well as carbohydrates, biomolecules, bioprotectants and pharmaceuticals. Due to the abundance of experimental data, emphasis is placed on glass-formers and the glass transition problem, a still unsolved problem in condensed matter physics and chemistry. The evidence for universal properties of relaxation and diffusion dynamics suggests that a fundamental physical law is at work. The origin of the universal properties is traced to the many-body effects of the interaction, rigorous theory of which does not exist at the present time. However, using solutions of simplified models as guides, key quantities have been identified and predictions of the universal properties generated. These predictions from Ngai’...

Complex Networks in Psychological Models

Science.gov (United States)

Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

Modeling and simulation of systems using Matlab and Simulink

CERN Document Server

Chaturvedi, Devendra K

2009-01-01

Introduction to SystemsSystemClassification of SystemsLinear SystemsTime-Varying vs. Time-Invariant Systems Lumped vs. Distributed Parameter SystemsContinuous- and Discrete-Time Systems Deterministic vs. Stochastic Systems Hard and Soft Systems Analysis of Systems Synthesis of Systems Introduction to System Philosophy System Thinking Large and Complex Applied System Engineering: A Generic ModelingSystems ModelingIntroduction Need of System Modeling Modeling Methods for Complex Systems Classification of ModelsCharacteristics of Models ModelingMathematical Modeling of Physical SystemsFormulation of State Space Model of SystemsPhysical Systems Theory System Components and Interconnections Computation of Parameters of a Component Single Port and Multiport Systems Techniques of System Analysis Basics of Linear Graph Theoretic ApproachFormulation of System Model for Conceptual SystemFormulation System Model for Physical SystemsTopological RestrictionsDevelopment of State Model of Degenerative SystemSolution of Stat...

Return-to-Work Within a Complex and Dynamic Organizational Work Disability System

OpenAIRE

Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J.

2015-01-01

Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, an...

Anti-synchronization between different chaotic complex systems

International Nuclear Information System (INIS)

Liu Ping; Liu Shutang

2011-01-01

Many studies on the anti-synchronization of nonlinear real dynamic systems have been carried out, whereas the anti-synchronization of chaotic complex systems has not been studied extensively. In this work, the anti-synchronization between a new chaotic complex system and a complex Lorenz system and that between a new chaotic complex system and a complex Lue system were separately investigated by active control and nonlinear control methods, and explicit expressions were derived for the controllers that are used to achieve the anti-synchronization of chaotic complex systems. These expressions were tested numerically and excellent agreement was found. Concerning the new chaotic complex system, we discuss its dynamical properties including dissipation, chaotic behavior, fixed points, and their stability and invariance.

Modeling complexes of modeled proteins.

Science.gov (United States)

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Transforming Graphical System Models To Graphical Attack Models

NARCIS (Netherlands)

Ivanova, Marieta Georgieva; Probst, Christian W.; Hansen, René Rydhof; Kammüller, Florian; Mauw, S.; Kordy, B.

2015-01-01

Manually identifying possible attacks on an organisation is a complex undertaking; many different factors must be considered, and the resulting attack scenarios can be complex and hard to maintain as the organisation changes. System models provide a systematic representation of organisations that

Generative complexity of Gray-Scott model

Science.gov (United States)

Adamatzky, Andrew

2018-03-01

In the Gray-Scott reaction-diffusion system one reactant is constantly fed in the system, another reactant is reproduced by consuming the supplied reactant and also converted to an inert product. The rate of feeding one reactant in the system and the rate of removing another reactant from the system determine configurations of concentration profiles: stripes, spots, waves. We calculate the generative complexity-a morphological complexity of concentration profiles grown from a point-wise perturbation of the medium-of the Gray-Scott system for a range of the feeding and removal rates. The morphological complexity is evaluated using Shannon entropy, Simpson diversity, approximation of Lempel-Ziv complexity, and expressivity (Shannon entropy divided by space-filling). We analyse behaviour of the systems with highest values of the generative morphological complexity and show that the Gray-Scott systems expressing highest levels of the complexity are composed of the wave-fragments (similar to wave-fragments in sub-excitable media) and travelling localisations (similar to quasi-dissipative solitons and gliders in Conway's Game of Life).

Complexity in Dynamical Systems

Science.gov (United States)

Moore, Cristopher David

The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

Low-complexity Behavioral Model for Predictive Maintenance of Railway Turnouts

DEFF Research Database (Denmark)

Barkhordari, Pegah; Galeazzi, Roberto; Tejada, Alejandro de Miguel

2017-01-01

together with the Eigensystem Realization Algorithm – a type of subspace identification – to identify a fourth order model of the infrastructure. The robustness and predictive capability of the low-complexity behavioral model to reproduce track responses under different types of train excitations have been......Maintenance of railway infrastructures represents a major cost driver for any infrastructure manager since reliability and dependability must be guaranteed at all times. Implementation of predictive maintenance policies relies on the availability of condition monitoring systems able to assess...... the infrastructure health state. The core of any condition monitoring system is the a-priori knowledge about the process to be monitored, in the form of either mathematical models of different complexity or signal features characterizing the healthy/faulty behavior. This study investigates the identification...

A systems modelling framework for the design of integrated process control systems

International Nuclear Information System (INIS)

Lind, M.

1983-12-01

The paper describes a systems modelling methodology, called multilevel flow modelling, or MFM, which aims at describing complex production plants as designs, i.e. as systems having goals, functions and equipment realizing these functions. The modelling concepts are based on thermodynamics and lead to a system description in terms of multiple levels of interrelated mass or energy flow structures. The paper discusses as a basis for the modelling framework the general properties of artifacts or designs, characterizes the complexity of production systems and defines the MFM concepts which allow a consistent specification of goals and functions of these systems as generated in the process design. A modelling example is given and the application of the models for the design of plant control strategies is outlined. (author)

Complex logistics audit system

Directory of Open Access Journals (Sweden)

Zuzana Marková

2010-02-01

Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.

Propagating wave correlations in complex systems

International Nuclear Information System (INIS)

Creagh, Stephen C; Gradoni, Gabriele; Hartmann, Timo; Tanner, Gregor

2017-01-01

We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local mean of these correlation functions in terms of the underlying classical dynamics. By defining appropriate ensemble averages, we show that fluctuations about the mean can be characterised in terms of classical correlations. We give in particular an explicit expression relating fluctuations of diagonal contributions to those of the full wave correlation function. The methods have a wide range of applications both in quantum mechanics and for classical wave problems such as in vibro-acoustics and electromagnetism. We apply the methods here to simple quantum systems, so-called quantum maps, which model the behaviour of generic problems on Poincaré sections. Although low-dimensional, these models exhibit a chaotic classical limit and share common characteristics with wave propagation in complex structures. (paper)

A unified approach to model uptake kinetics of trace elements in complex aqueous – solid solution systems

International Nuclear Information System (INIS)

Thien, Bruno M.J.; Kulik, Dmitrii A.; Curti, Enzo

2014-01-01

Highlights: • There are several models able to describe trace element partitioning in growing minerals. • To describe complex systems, those models must be embedded in a geochemical code. • We merged two models into a unified one suitable for implementation in a geochemical code. • This unified model was tested against coprecipitation experimental data. • We explored how our model reacts to solution depletion effects. - Abstract: Thermodynamics alone is usually not sufficient to predict growth-rate dependencies of trace element partitioning into host mineral solid solutions. In this contribution, two uptake kinetic models were analyzed that are promising in terms of mechanistic understanding and potential for implementation in geochemical modelling codes. The growth Surface Entrapment Model (Watson, 2004) and the Surface Reaction Kinetic Model (DePaolo, 2011) were shown to be complementary, and under certain assumptions merged into a single analytical expression. This Unified Uptake Kinetics Model was implemented in GEMS3K and GEM-Selektor codes ( (http://gems.web.psi.ch)), a Gibbs energy minimization package for geochemical modelling. This implementation extends the applicability of the unified uptake kinetics model to accounting for non-trivial factors influencing the trace element partitioning into solid solutions, such as the changes in aqueous solution composition and speciation, or the depletion effects in closed geochemical systems

Large-scale modelling of neuronal systems

International Nuclear Information System (INIS)

Castellani, G.; Verondini, E.; Giampieri, E.; Bersani, F.; Remondini, D.; Milanesi, L.; Zironi, I.

2009-01-01

The brain is, without any doubt, the most, complex system of the human body. Its complexity is also due to the extremely high number of neurons, as well as the huge number of synapses connecting them. Each neuron is capable to perform complex tasks, like learning and memorizing a large class of patterns. The simulation of large neuronal systems is challenging for both technological and computational reasons, and can open new perspectives for the comprehension of brain functioning. A well-known and widely accepted model of bidirectional synaptic plasticity, the BCM model, is stated by a differential equation approach based on bistability and selectivity properties. We have modified the BCM model extending it from a single-neuron to a whole-network model. This new model is capable to generate interesting network topologies starting from a small number of local parameters, describing the interaction between incoming and outgoing links from each neuron. We have characterized this model in terms of complex network theory, showing how this, learning rule can be a support For network generation.

Design theoretic analysis of three system modeling frameworks.

Energy Technology Data Exchange (ETDEWEB)

McDonald, Michael James

2007-05-01

This paper analyzes three simulation architectures from the context of modeling scalability to address System of System (SoS) and Complex System problems. The paper first provides an overview of the SoS problem domain and reviews past work in analyzing model and general system complexity issues. It then identifies and explores the issues of vertical and horizontal integration as well as coupling and hierarchical decomposition as the system characteristics and metrics against which the tools are evaluated. In addition, it applies Nam Suh's Axiomatic Design theory as a construct for understanding coupling and its relationship to system feasibility. Next it describes the application of MATLAB, Swarm, and Umbra (three modeling and simulation approaches) to modeling swarms of Unmanned Flying Vehicle (UAV) agents in relation to the chosen characteristics and metrics. Finally, it draws general conclusions for analyzing model architectures that go beyond those analyzed. In particular, it identifies decomposition along phenomena of interaction and modular system composition as enabling features for modeling large heterogeneous complex systems.

Measuring Complexity of SAP Systems

Directory of Open Access Journals (Sweden)

Ilja Holub

2016-10-01

Full Text Available The paper discusses the reasons of complexity rise in ERP system SAP R/3. It proposes a method for measuring complexity of SAP. Based on this method, the computer program in ABAP for measuring complexity of particular SAP implementation is proposed as a tool for keeping ERP complexity under control. The main principle of the measurement method is counting the number of items or relations in the system. The proposed computer program is based on counting of records in organization tables in SAP.

European Conference on Complex Systems

CERN Document Server

Pellegrini, Francesco; Caldarelli, Guido; Merelli, Emanuela

2016-01-01

This work contains a stringent selection of extended contributions presented at the meeting of 2014 and its satellite meetings, reflecting scope, diversity and richness of research areas in the field, both fundamental and applied. The ECCS meeting, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. It offers cutting edge research and unique opportunities to study novel scientific approaches in a multitude of application areas. ECCS'14, its eleventh occurrence, took place in Lucca, Italy. It gathered some 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. The editors are among the best specialists in the area. The book is of great interest to scientists, researchers and graduate students in complexity, complex systems and networks.

The deconvolution of complex spectra by artificial immune system

Science.gov (United States)

Galiakhmetova, D. I.; Sibgatullin, M. E.; Galimullin, D. Z.; Kamalova, D. I.

2017-11-01

An application of the artificial immune system method for decomposition of complex spectra is presented. The results of decomposition of the model contour consisting of three components, Gaussian contours, are demonstrated. The method of artificial immune system is an optimization method, which is based on the behaviour of the immune system and refers to modern methods of search for the engine optimization.

Occupancy modeling and estimation of the holiday darter species complex within the Etowah River system

Science.gov (United States)

Anderson, Gregory B.; Freeman, Mary C.; Hagler, Megan M.; Freeman, Byron J.

2012-01-01

Documenting the status of rare fishes is a crucial step in effectively managing populations and implementing regulatory mechanisms of protection. In recent years, site occupancy has become an increasingly popular metric for assessing populations, but species distribution models that do not account for imperfect detection can underestimate the proportion of sites occupied and the strength of the relationship with a hypothesized covariate. However, valid detection requires temporal or spatial replication, which is often not feasible due to logistical or budget constraints. In this study, we used a method that allowed for spatial replication during a single visit to evaluate the current status of the holiday darter species complex, Etheostoma sp. cf. E. brevirostrum, within the Etowah River system. Moreover, the modeling approach used in this study facilitated comparisons of factors influencing stream occupancy as well as species detection within sites. The results suggest that there is less habitat available for the Etowah holiday darter form (Etheostoma sp. cf. E. brevirostrum B) than for the Amicalola holiday darter form (Etheostoma sp. cf. E. brevirostrum A). Additionally, occupancy models suggest that even small decreases in forest cover within these headwater systems adversely affect holiday darter populations.

Evaluating Complex Healthcare Systems: A Critique of Four Approaches

Directory of Open Access Journals (Sweden)

Heather Boon

2007-01-01

Full Text Available The purpose of this paper is to bring clarity to the emerging conceptual and methodological literature that focuses on understanding and evaluating complex or ‘whole’ systems of healthcare. An international working group reviewed literature from interdisciplinary or interprofessional groups describing approaches to the evaluation of complex systems of healthcare. The following four key approaches were identified: a framework from the MRC (UK, whole systems research, whole medical systems research described by NCCAM (USA and a model from NAFKAM (Norway. Main areas of congruence include acknowledgment of the inherent complexity of many healthcare interventions and the need to find new ways to evaluate these; the need to describe and understand the components of complex interventions in context (as they are actually practiced; the necessity of using mixed methods including randomized clinical trials (RCTs (explanatory and pragmatic and qualitative approaches; the perceived benefits of a multidisciplinary team approach to research; and the understanding that methodological developments in this field can be applied to both complementary and alternative medicine (CAM as well as conventional therapies. In contrast, the approaches differ in the following ways: terminology used, the extent to which the approach attempts to be applicable to both CAM and conventional medical interventions; the prioritization of research questions (in order of what should be done first especially with respect to how the ‘definitive’ RCT fits into the process of assessing complex healthcare systems; and the need for a staged approach. There appears to be a growing international understanding of the need for a new perspective on assessing complex healthcare systems.

Coupled economic-ecological models for ecosystem-based fishery management: Exploration of trade-offs between model complexity and management needs

DEFF Research Database (Denmark)

Thunberg, Eric; Holland, Dan; Nielsen, J. Rasmus

2012-01-01

Ecosystem based fishery management has moved beyond rhetorical statements calling for a more holistic approach to resource management, to implementing decisions on resource use that are compatible with goals of maintaining ecosystem health and resilience. Coupled economic-ecological models...... are a primary tool for informing these decisions. Recognizing the importance of these models, the International Council for the Exploration of the Seas (ICES) formed a Study Group on Integration of Economics, Stock Assessment and Fisheries Management (SGIMM) to explore alternative modelling approaches...... and ecological systems are inherently complex, models are abstractions of these systems incorporating varying levels of complexity depending on available data and the management issues to be addressed. The objective of this special session was to assess the pros and cons of increasing model complexity...

Describing joint air defence within operations other than war context as a complex system

CSIR Research Space (South Africa)

Oosthuizen, R

2009-10-01

Full Text Available . This paper will firstly investigate the theory of complexity and identify the main characteristics. This will be applied to Systems Engineering and modelling techniques, to propose a method of implementation in the real world. The application... of complexity in warfare is discussed to form a foundation for the discussion of JAD. Finally, the sources of complexity in JAD are identified and an approach to address these proposed. 2 Complex Systems 2.1 Definition of Complex Systems The theory...

Power, autonomy, utopia new approaches toward complex systems

CERN Document Server

1986-01-01

The "world" is becoming more and more intractable. We have learned to discern "systems" in it, we have developed a highly sophisticated math­ ematical apparatus to "model'" them, large computer simulation programs handle thousands of equations with zillions of parameters. But how ade­ quate are these efforts? Part One of this volume is a discussion containing some proposals for eliminating the constraints we encounter when approaching complex systems with our models: Is it possible, at all, to design a political or econom­ ic system without considering killing, torture, and oppression? Can we adequately model the present state of affairs while ignoring their often symbolic and paradoxical nature? Is it possible to explain teleological concepts such as "means" and "ends" in terms of basically 17th century Newtonian mechanics? Can we really make appropriate use of the vast a­ mount of systems concepts without exploring their relations, without de­ veloping a "system of systems concepts"? And why do more th...

Sixth International Conference on Complex Systems

CERN Document Server

Minai, Ali; Bar-Yam, Yaneer; Unifying Themes in Complex Systems

2008-01-01

The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore the common themes and applications of complex systems science. In June 2006, 500 participants convened in Boston for the sixth ICCS, exploring an array of topics, including networks, systems biology, evolution and ecology, nonlinear dynamics and pattern formation, as well as neural, psychological, psycho-social, socio-economic, and global systems. This volume selects 77 papers from over 300 presented at the conference. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex systems science.

Simulating Complex, Cold-region Process Interactions Using a Multi-scale, Variable-complexity Hydrological Model

Science.gov (United States)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2017-12-01

Accurate management of water resources is necessary for social, economic, and environmental sustainability worldwide. In locations with seasonal snowcovers, the accurate prediction of these water resources is further complicated due to frozen soils, solid-phase precipitation, blowing snow transport, and snowcover-vegetation-atmosphere interactions. Complex process interactions and feedbacks are a key feature of hydrological systems and may result in emergent phenomena, i.e., the arising of novel and unexpected properties within a complex system. One example is the feedback associated with blowing snow redistribution, which can lead to drifts that cause locally-increased soil moisture, thus increasing plant growth that in turn subsequently impacts snow redistribution, creating larger drifts. Attempting to simulate these emergent behaviours is a significant challenge, however, and there is concern that process conceptualizations within current models are too incomplete to represent the needed interactions. An improved understanding of the role of emergence in hydrological systems often requires high resolution distributed numerical hydrological models that incorporate the relevant process dynamics. The Canadian Hydrological Model (CHM) provides a novel tool for examining cold region hydrological systems. Key features include efficient terrain representation, allowing simulations at various spatial scales, reduced computational overhead, and a modular process representation allowing for an alternative-hypothesis framework. Using both physics-based and conceptual process representations sourced from long term process studies and the current cold regions literature allows for comparison of process representations and importantly, their ability to produce emergent behaviours. Examining the system in a holistic, process-based manner can hopefully derive important insights and aid in development of improved process representations.

Saving Human Lives: What Complexity Science and Information Systems can Contribute

Science.gov (United States)

Helbing, Dirk; Brockmann, Dirk; Chadefaux, Thomas; Donnay, Karsten; Blanke, Ulf; Woolley-Meza, Olivia; Moussaid, Mehdi; Johansson, Anders; Krause, Jens; Schutte, Sebastian; Perc, Matjaž

2015-02-01

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Cognitive engineering models: A prerequisite to the design of human-computer interaction in complex dynamic systems

Science.gov (United States)

Mitchell, Christine M.

1993-01-01

This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.

Model complexity control for hydrologic prediction

NARCIS (Netherlands)

Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

2008-01-01

A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

Entropy, complexity, and Markov diagrams for random walk cancer models.

Science.gov (United States)

Newton, Paul K; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter

2014-12-19

The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential.

Collaborative Management of Complex Major Construction Projects: AnyLogic-Based Simulation Modelling

Directory of Open Access Journals (Sweden)

Na Zhao

2016-01-01

Full Text Available Complex supply chain system collaborative management of major construction projects effectively integrates the different participants in the construction project. This paper establishes a simulation model based on AnyLogic to reveal the collaborative elements in the complex supply chain management system and the modes of action as well as the transmission problems of the intent information. Thus it is promoting the participants to become an organism with coordinated development and coevolution. This study can help improve the efficiency and management of the complex system of major construction projects.

Axiomatic design in large systems complex products, buildings and manufacturing systems

CERN Document Server

Suh, Nam

2016-01-01

This book provides a synthesis of recent developments in Axiomatic Design theory and its application in large complex systems. Introductory chapters provide concise tutorial materials for graduate students and new practitioners, presenting the fundamentals of Axiomatic Design and relating its key concepts to those of model-based systems engineering. A mathematical exposition of design axioms is also provided. The main body of the book, which represents a concentrated treatment of several applications, is divided into three parts covering work on: complex products; buildings; and manufacturing systems. The book shows how design work in these areas can benefit from the scientific and systematic underpinning provided by Axiomatic Design, and in so doing effectively combines the state of the art in design research with practice. All contributions were written by an international group of leading proponents of Axiomatic Design. The book concludes with a call to action motivating further research into the engineeri...

From complex to simple: interdisciplinary stochastic models

International Nuclear Information System (INIS)

Mazilu, D A; Zamora, G; Mazilu, I

2012-01-01

We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions for certain physical quantities, such as the time dependence of the length of the microtubules, and diffusion coefficients. The second one is a stochastic adsorption model with applications in surface deposition, epidemics and voter systems. We introduce the ‘empty interval method’ and show sample calculations for the time-dependent particle density. These models can serve as an introduction to the field of non-equilibrium statistical physics, and can also be used as a pedagogical tool to exemplify standard statistical physics concepts, such as random walks or the kinetic approach of the master equation. (paper)

A Peep into the Uncertainty-Complexity-Relevance Modeling Trilemma through Global Sensitivity and Uncertainty Analysis

Science.gov (United States)

Munoz-Carpena, R.; Muller, S. J.; Chu, M.; Kiker, G. A.; Perz, S. G.

2014-12-01

Model Model complexity resulting from the need to integrate environmental system components cannot be understated. In particular, additional emphasis is urgently needed on rational approaches to guide decision making through uncertainties surrounding the integrated system across decision-relevant scales. However, in spite of the difficulties that the consideration of modeling uncertainty represent for the decision process, it should not be avoided or the value and science behind the models will be undermined. These two issues; i.e., the need for coupled models that can answer the pertinent questions and the need for models that do so with sufficient certainty, are the key indicators of a model's relevance. Model relevance is inextricably linked with model complexity. Although model complexity has advanced greatly in recent years there has been little work to rigorously characterize the threshold of relevance in integrated and complex models. Formally assessing the relevance of the model in the face of increasing complexity would be valuable because there is growing unease among developers and users of complex models about the cumulative effects of various sources of uncertainty on model outputs. In particular, this issue has prompted doubt over whether the considerable effort going into further elaborating complex models will in fact yield the expected payback. New approaches have been proposed recently to evaluate the uncertainty-complexity-relevance modeling trilemma (Muller, Muñoz-Carpena and Kiker, 2011) by incorporating state-of-the-art global sensitivity and uncertainty analysis (GSA/UA) in every step of the model development so as to quantify not only the uncertainty introduced by the addition of new environmental components, but the effect that these new components have over existing components (interactions, non-linear responses). Outputs from the analysis can also be used to quantify system resilience (stability, alternative states, thresholds or tipping

Non-Archimedean reaction-ultradiffusion equations and complex hierarchic systems

Science.gov (United States)

Zúñiga-Galindo, W. A.

2018-06-01

We initiate the study of non-Archimedean reaction-ultradiffusion equations and their connections with models of complex hierarchic systems. From a mathematical perspective, the equations studied here are the p-adic counterpart of the integro-differential models for phase separation introduced by Bates and Chmaj. Our equations are also generalizations of the ultradiffusion equations on trees studied in the 1980s by Ogielski, Stein, Bachas, Huberman, among others, and also generalizations of the master equations of the Avetisov et al models, which describe certain complex hierarchic systems. From a physical perspective, our equations are gradient flows of non-Archimedean free energy functionals and their solutions describe the macroscopic density profile of a bistable material whose space of states has an ultrametric structure. Some of our results are p-adic analogs of some well-known results in the Archimedean setting, however, the mechanism of diffusion is completely different due to the fact that it occurs in an ultrametric space.

The quantum-chemical modeling of structure and spectral characteristics for molecular complexes in system «penton-terlon»

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Andrey V. Tokar

2014-03-01

Full Text Available The structure and spectral properties for molecular complexes, which formed by added monomer form of pentaplast as well as N-phenylbenzamide with some species of intermolecular interaction in system «penton-terlon» have been investigated at ab initio level of theory. It is shown, that the main contribution in total energy of molecules have included by dispersion forces, which realized between Chlorine atom of CH2Cl-group and Hydrogen atoms of benzene rings with amide fragment. The proposed theoretical models are validated in reflection of spectral and energetic characteristics of investigating system. Finally, the results of calculations are in good agreement with that data, which have been obtained for such type modeling previously.

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

Energy Technology Data Exchange (ETDEWEB)

Marzouk, Youssef [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

2016-08-31

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

Philosophy of complex systems

CERN Document Server

2011-01-01

The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on. Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of comple...

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

Non-Hermitian multi-particle systems from complex root spaces

International Nuclear Information System (INIS)

Fring, Andreas; Smith, Monique

2012-01-01

We provide a general construction procedure for antilinearly invariant complex root spaces. The proposed method is generic and may be applied to any Weyl group allowing us to take any element of the group as a starting point for the construction. Worked-out examples for several specific Weyl groups are presented, focusing especially on those cases for which no solutions were found previously. When applied to the defining relations of models based on root systems, this usually leads to non-Hermitian models, which are nonetheless physically viable in a self-consistent sense as they are antilinearly invariant by construction. We discuss new types of Calogero models based on these complex roots. In addition, we propose an alternative construction leading to q-deformed roots. We employ the latter type of roots to formulate a new version of affine Toda field theories based on non-simply laced root systems. These models exhibit on the classical level a strong–weak duality in the coupling constant equivalent to a Lie algebraic duality, which is known for the quantum version of the undeformed case. (paper)

On Verification Modelling of Embedded Systems

NARCIS (Netherlands)

Brinksma, Hendrik; Mader, Angelika H.

Computer-aided verification of embedded systems hinges on the availability of good verification models of the systems at hand. Such models must be much simpler than full design models or specifications to be of practical value, because of the unavoidable combinatorial complexities in the

Application of functional derivatives to analysis of complex systems

Czech Academy of Sciences Publication Activity Database

Beran, Zdeněk; Čelikovský, Sergej

2013-01-01

Roč. 350, č. 10 (2013), s. 2982-2993 ISSN 0016-0032 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : complex systems * linear equation * modeling Subject RIV: BC - Control Systems Theory Impact factor: 2.260, year: 2013 http://library.utia.cas.cz/separaty/2013/TR/beran-0398123.pdf

5th International Conference on Complex Systems

CERN Document Server

Braha, Dan; Bar-Yam, Yaneer

2011-01-01

The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

7th International Conference on Complex Systems

CERN Document Server

Braha, Dan; Bar-Yam, Yaneer

2012-01-01

The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

An advanced modelling tool for simulating complex river systems.

Science.gov (United States)

Trancoso, Ana Rosa; Braunschweig, Frank; Chambel Leitão, Pedro; Obermann, Matthias; Neves, Ramiro

2009-04-01

The present paper describes MOHID River Network (MRN), a 1D hydrodynamic model for river networks as part of MOHID Water Modelling System, which is a modular system for the simulation of water bodies (hydrodynamics and water constituents). MRN is capable of simulating water quality in the aquatic and benthic phase and its development was especially focused on the reproduction of processes occurring in temporary river networks (flush events, pools formation, and transmission losses). Further, unlike many other models, it allows the quantification of settled materials at the channel bed also over periods when the river falls dry. These features are very important to secure mass conservation in highly varying flows of temporary rivers. The water quality models existing in MOHID are base on well-known ecological models, such as WASP and ERSEM, the latter allowing explicit parameterization of C, N, P, Si, and O cycles. MRN can be coupled to the basin model, MOHID Land, with computes runoff and porous media transport, allowing for the dynamic exchange of water and materials between the river and surroundings, or it can be used as a standalone model, receiving discharges at any specified nodes (ASCII files of time series with arbitrary time step). These features account for spatial gradients in precipitation which can be significant in Mediterranean-like basins. An interface has been already developed for SWAT basin model.

Using Models to Inform Policy: Insights from Modeling the Complexities of Global Polio Eradication

Science.gov (United States)

Thompson, Kimberly M.

Drawing on over 20 years of experience modeling risks in complex systems, this talk will challenge SBP participants to develop models that provide timely and useful answers to critical policy questions when decision makers need them. The talk will include reflections on the opportunities and challenges associated with developing integrated models for complex problems and communicating their results effectively. Dr. Thompson will focus the talk largely on collaborative modeling related to global polio eradication and the application of system dynamics tools. After successful global eradication of wild polioviruses, live polioviruses will still present risks that could potentially lead to paralytic polio cases. This talk will present the insights of efforts to use integrated dynamic, probabilistic risk, decision, and economic models to address critical policy questions related to managing global polio risks. Using a dynamic disease transmission model combined with probabilistic model inputs that characterize uncertainty for a stratified world to account for variability, we find that global health leaders will face some difficult choices, but that they can take actions that will manage the risks effectively. The talk will emphasize the need for true collaboration between modelers and subject matter experts, and the importance of working with decision makers as partners to ensure the development of useful models that actually get used.

Reliability of large and complex systems

CERN Document Server

Kolowrocki, Krzysztof

2014-01-01

Reliability of Large and Complex Systems, previously titled Reliability of Large Systems, is an innovative guide to the current state and reliability of large and complex systems. In addition to revised and updated content on the complexity and safety of large and complex mechanisms, this new edition looks at the reliability of nanosystems, a key research topic in nanotechnology science. The author discusses the importance of safety investigation of critical infrastructures that have aged or have been exposed to varying operational conditions. This reference provides an asympt

Geographical National Condition and Complex System

Directory of Open Access Journals (Sweden)

WANG Jiayao

2016-01-01

Full Text Available The significance of studying the complex system of geographical national conditions lies in rationally expressing the complex relationships of the “resources-environment-ecology-economy-society” system. Aiming to the problems faced by the statistical analysis of geographical national conditions, including the disunity of research contents, the inconsistency of range, the uncertainty of goals, etc.the present paper conducted a range of discussions from the perspectives of concept, theory and method, and designed some solutions based on the complex system theory and coordination degree analysis methods.By analyzing the concepts of geographical national conditions, geographical national conditions survey and geographical national conditions statistical analysis, as well as investigating the relationships between theirs, the statistical contents and the analytical range of geographical national conditions are clarified and defined. This investigation also clarifies the goals of the statistical analysis by analyzing the basic characteristics of the geographical national conditions and the complex system, and the consistency between the analysis of the degree of coordination and statistical analyses. It outlines their goals, proposes a concept for the complex system of geographical national conditions, and it describes the concept. The complex system theory provides new theoretical guidance for the statistical analysis of geographical national conditions. The degree of coordination offers new approaches on how to undertake the analysis based on the measurement method and decision-making analysis scheme upon which the complex system of geographical national conditions is based. It analyzes the overall trend via the degree of coordination of the complex system on a macro level, and it determines the direction of remediation on a micro level based on the degree of coordination among various subsystems and of single systems. These results establish

RATING MODELS AND INFORMATION TECHNOLOGIES APPLICATION FOR MANAGEMENT OF ADMINISTRATIVE-TERRITORIAL COMPLEXES

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O. M. Pshinko

2016-12-01

Full Text Available Purpose. The paper aims to develop rating models and related information technologies designed to resolve the tasks of strategic planning of the administrative and territorial units’ development, as well as the tasks of multi-criteria control of inhomogeneous multiparameter objects operation. Methodology. When solving problems of strategic planning of administrative and territorial development and heterogeneous classes management of objects under control, a set of agreed methods is used. Namely the multi-criteria properties analysis for objects of planning and management, diagnostics of the state parameters, forecasting and management of complex systems of different classes. Their states are estimated by sets of different quality indicators, as well as represented by the individual models of operation process. A new information technology is proposed and created to implement the strategic planning and management tasks. This technology uses the procedures for solving typical tasks, that are implemented in MS SQL Server. Findings. A new approach to develop models of analyze and management of complex systems classes based on the ratings has been proposed. Rating models development for analysis of multicriteria and multiparameter systems has been obtained. The management of these systems is performed on the base of parameters of the current and predicted state by non-uniform distribution of resources. The procedure of sensitivity analysis of the changes in the rating model of inhomogeneous distribution of resources parameters has been developed. The information technology of strategic planning and management of heterogeneous classes of objects based on the rating model has been created. Originality. This article proposes a new approach of the rating indicators’ using as a general model for strategic planning of the development and management of heterogeneous objects that can be characterized by the sets of parameters measured on different scales

Fusion, space and solar plasmas as complex systems

International Nuclear Information System (INIS)

Dendy, R O; Chapman, S C; Paczuski, M

2007-01-01

Complex systems science seeks to identify simple universal models that capture the key physics of extended macroscopic systems, whose behaviour is governed by multiple nonlinear coupled processes that operate across a wide range of spatiotemporal scales. In such systems, it is often the case that energy release occurs intermittently, in bursty events, and the phenomenology can exhibit scaling, that is a significant degree of self-similarity. Within plasma physics, such systems include Earth's magnetosphere, the solar corona and toroidal magnetic confinement experiments. Guided by broad understanding of the dominant plasma processes-for example, turbulent transport in tokamaks or reconnection in some space and solar contexts-one may construct minimalist complex systems models that yield relevant global behaviour. Examples considered here include the sandpile approach to tokamaks and the magnetosphere and a multiple loops model for the solar coronal magnetic carpet. Such models can address questions that are inaccessible to analytical treatment and are too demanding for contemporary computational resources; thus they potentially yield new insights, but risk being simplistic. Central to the utility of these models is their capacity to replicate distinctive aspects of observed global phenomenology, often strongly nonlinear, or of event statistics, for which no explanation can be obtained from first principles considerations such as the underlying equations. For example, a sandpile model, which embodies critical-gradient-triggered avalanching transport associated with nearest-neighbour mode coupling and simple boundary conditions (and little else), can be used to generate some of the distinctive observed elements of tokamak confinement phenomenology such as ELMing and edge pedestals. The same sandpile model can also generate distributions of energy-release events whose distinctive statistics resemble those observed in the auroral zone. Similarly, a multiple loops model

Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking

Science.gov (United States)

Berland, Matthew; Wilensky, Uri

2015-01-01

Both complex systems methods (such as agent-based modeling) and computational methods (such as programming) provide powerful ways for students to understand new phenomena. To understand how to effectively teach complex systems and computational content to younger students, we conducted a study in four urban middle school classrooms comparing…

Distributed Cooperation Solution Method of Complex System Based on MAS

Science.gov (United States)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Business model innovation in electricity supply markets: The role of complex value in the United Kingdom

International Nuclear Information System (INIS)

Hall, Stephen; Roelich, Katy

2016-01-01

This research investigates the new opportunities that business model innovations are creating in electricity supply markets at the sub-national scale. These local supply business models can offer significant benefits to the electricity system, but also generate economic, social, and environmental values that are not well accounted for in current policy or regulation. This paper uses the UK electricity supply market to investigate new business models which rely on more complex value propositions than the incumbent utility model. Nine archetypal local supply business models are identified and their value propositions, value capture methods, and barriers to market entry are analysed. This analysis defines 'complex value' as a key concept in understanding business model innovation in the energy sector. The process of complex value identification poses a challenge to energy researchers, commercial firms and policymakers in liberalised markets; to investigate the opportunities for system efficiency and diverse outcomes that new supplier business models can offer to the electricity system. - Highlights: •Business models of energy supply markets shape energy transitions. •The British system misses four opportunities of local electricity supply. •Nine new business model archetypes of local supply are analysed. •New electricity business models have complex value propositions. •A process for policy response to business model innovation is presented.