The ability to accurately simulate the time evolu-tion of quantum systems stands as a cornerstone of modern molecular science.It provides the essential mechanistic bridge between a system’s microscopic structure and ...The ability to accurately simulate the time evolu-tion of quantum systems stands as a cornerstone of modern molecular science.It provides the essential mechanistic bridge between a system’s microscopic structure and its macroscopic function,a challenge first envisioned by Feynman.The central difficulty,and the unifying theme of this Special Topic,is the problem of“complexity”:a multifaceted challenge arising from the interplay of strongly coupled electronic and vibrational degrees of freedom,quantum statistics,and the non-trivial,often non-Markovian,memory effects exerted by a surrounding environment.展开更多
In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling struct...In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.展开更多
Researches on organization and structure in complex systems are academic and industrial fronts in modern sciences. Though many theories are tentatively proposed to analyze complex systems, we still lack a rigorous the...Researches on organization and structure in complex systems are academic and industrial fronts in modern sciences. Though many theories are tentatively proposed to analyze complex systems, we still lack a rigorous theory on them. Complex systems possess various degrees of freedom, which means that they should exhibit all kinds of structures. However, complex systems often show similar patterns and structures. Then the question arises why such similar structures appear in all kinds of complex systems. The paper outlines a theory on freedom degree compression and the existence of hierarchical self-organization for all complex systems is found. It is freedom degree compression and hierarchical self-organization that are responsible for the existence of these similar patterns or structures observed in the complex systems.展开更多
Related to complexity, there is a wide diversity of concepts, ranging from ‘‘systemic" to ‘‘complex", implying a need for a unified terminology. Per different authors, the main drivers of complexity can ...Related to complexity, there is a wide diversity of concepts, ranging from ‘‘systemic" to ‘‘complex", implying a need for a unified terminology. Per different authors, the main drivers of complexity can be found in human behaviour and uncertainty. This complexity, structural or dynamic can be organizational, technological, or nested in their relationship. ISO international standard 31000:2009 definition of risk management ‘‘coordinated activities to direct and control an organization with regard to risk", when applied to economic sectors, industry, services, project, or activity, it requires the use of models or theories as guidelines. Therefore, as its basic elements comprehend human behaviour and/or uncertainty, risk management to be effective and adapted as much as possible to reality, must be operational within complex systems, as already demonstrated in different R&D environments. Risk management faces demanding challenges when approaching specific and endogenous needs, such as the mining sector. This paper presents a multivariable function analysis methodology approach based on complex system modelling and through real data corresponding to a risk management tool in the mining sector.展开更多
The composition of the modern aerospace system becomes more and more complex.The performance degradation of any device in the system may cause it difficult for the whole system to keep normal working states.Therefore,...The composition of the modern aerospace system becomes more and more complex.The performance degradation of any device in the system may cause it difficult for the whole system to keep normal working states.Therefore,it is essential to evaluate the performance of complex aerospace systems.In this paper,the performance evaluation of complex aerospace systems is regarded as a Multi-Attribute Decision Analysis(MADA)problem.Based on the structure and working principle of the system,a new Evidential Reasoning(ER)based approach with uncertain parameters is proposed to construct a nonlinear optimization model to evaluate the system performance.In the model,the interval form is used to express the uncertainty,such as error in testing data and inaccuracy in expert knowledge.In order to analyze the subsystems that have a great impact on the performance of the system,the sensitivity analysis of the evaluation result is carried out,and the corresponding maintenance strategy is proposed.For a type of Inertial Measurement Unit(IMU)used in a rocket,the proposed method is employed to evaluate its performance.Then,the parameter sensitivity of the evaluation result is analyzed,and the main factors affecting the performance of IMU are obtained.Finally,the comparative study shows the effectiveness of the proposed method.展开更多
THE Industrial Revolution starting from about 1760 and ending at around 1840 has been viewed as the first Industrial Revolution.It features with the replacement of human and animal muscle power with steam and mechanic...THE Industrial Revolution starting from about 1760 and ending at around 1840 has been viewed as the first Industrial Revolution.It features with the replacement of human and animal muscle power with steam and mechanical power.Human income per capita had taken 800 years to double by展开更多
This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key...This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.展开更多
The field of environmental sciences is abundant with various interfaces and is the right place for the application of new fundamental approaches leading towards a better understanding of environmental phenomena. Follo...The field of environmental sciences is abundant with various interfaces and is the right place for the application of new fundamental approaches leading towards a better understanding of environmental phenomena. Following the definition of environmental interface by Mihailovic and Bala? [1], such interface can be, for example, placed between: human or animal bodies and surrounding air, aquatic species and water and air around them, and natural or artificially built surfaces (vegetation, ice, snow, barren soil, water, urban communities) and the atmosphere, cells and surrounding environment, etc. Complex environmental interface systems are (i) open and hierarchically organised (ii) interactions between their constituent parts are nonlinear, and (iii) their interaction with the surrounding environment is noisy. These systems are therefore very sensitive to initial conditions, deterministic external perturbations and random fluctuations always present in nature. The study of noisy non-equilibrium processes is fundamental for modelling the dynamics of environmental interface regarded as biophysical complex system and for understanding the mechanisms of spatio-temporal pattern formation in contemporary environmental sciences. In this paper we will investigate an aspect of dynamics of energy flow based on the energy balance equation. The energy exchange between interacting environmen- tal interfaces regarded as biophysical complex systems can be represented by coupled maps. Therefore, we will numerically investigate coupled maps representing that exchange. In ana- lysis of behaviour of these maps we applied Lyapunov exponent and cross sample entropy.展开更多
In this paper,we review some existing control methodologies for complex systems with particular emphasis on those that are near critical.Due to the shortage of the classical control theory in handling complex systems,...In this paper,we review some existing control methodologies for complex systems with particular emphasis on those that are near critical.Due to the shortage of the classical control theory in handling complex systems,the reviewed control methods are mainly associated with machine learning techniques,game-theoretical approaches,and sparse control strategies.Additionally,several interesting and promising directions for future research are also proposed.展开更多
The fundamental and simplest structure of a complex system is a network.According to this idea,we plan to develop a general methematical framework of complex systems.In this paper,we discuss in detail the concept of s...The fundamental and simplest structure of a complex system is a network.According to this idea,we plan to develop a general methematical framework of complex systems.In this paper,we discuss in detail the concept of systems,a general description of systems:System=(Hardware,Software,Environment),and whole-part relations,including relations between elements and systems,subsystems and systems,and between systems.The rules of operations of systems are given,and the induced transformations between hardware and software of systems are briefly discussed.展开更多
Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the ...Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the context of complex system thinking. Three features of complex systems are that they are uncertain, non-linear and self-organizing. Modeling regional development requires a consideration of these features. This paper discusses the feasibility of using the artificial neural networt(ANN) to establish an adjustment prediction model for the complex systems of sustainable development (CSSD). Shanghai Municipality was selected as the research area to set up the model, from which reliable prediction data were produced in order to help regional development planning. A new approach, which could help to manage regional sustainable development, is then explored.展开更多
The purpose of this work is to analyze the electrical properties of the metal–semiconductor contact(MSC)in the framework of the theory of complex systems.The effect of inhomogeneity of the different microstructures:p...The purpose of this work is to analyze the electrical properties of the metal–semiconductor contact(MSC)in the framework of the theory of complex systems.The effect of inhomogeneity of the different microstructures:polycrystalline,monocrystalline,amorphous metal–semiconductor contact surface is investigated,considering a Schottky diode(SD)as a parallel connection of numerous subdiodes.It has been shown that the polycrystallinity of the metal translates a homogeneous contact into a complex system,which consists of parallel connected numerous elementary contacts having different properties and parameters.展开更多
This paper deals with the finite-time stabilization of unified chaotic complex systems with known and unknown parameters. Based on the finite-time stability theory, nonlinear control laws are presented to achieve fini...This paper deals with the finite-time stabilization of unified chaotic complex systems with known and unknown parameters. Based on the finite-time stability theory, nonlinear control laws are presented to achieve finite-time chaos control of the determined and uncertain unified chaotic complex systems, respectively. The two controllers are simple, and one of the uncertain unified chaotic complex systems is robust. For the design of a finite-time controller on uncertain unified chaotic complex systems, only some of the unknown parameters need to be bounded. Simulation results for the chaotic complex Lorenz, Lu¨ and Chen systems are presented to validate the design and analysis.展开更多
In this paper, by use of equivalence operators δi and semi-equivalence operators Εi we study the clustering problems of complex systems, present δ (1,3) disconnection principle, dual transformation principle and la...In this paper, by use of equivalence operators δi and semi-equivalence operators Εi we study the clustering problems of complex systems, present δ (1,3) disconnection principle, dual transformation principle and large-scale systems decomposition principle for analizing and operating complex systems, discuss interconnectivity and disconnectivity of complex systems in detail and present some related theorems. Finally, we discuss the levels of systems according to pansystems clustering approach proposed in this paper.展开更多
The Golden Ratio Theorem, deeply rooted in fractal mathematics, presents a pioneering perspective on deciphering complex systems. It draws a profound connection between the principles of interchangeability, self-simil...The Golden Ratio Theorem, deeply rooted in fractal mathematics, presents a pioneering perspective on deciphering complex systems. It draws a profound connection between the principles of interchangeability, self-similarity, and the mathematical elegance of the Golden Ratio. This research unravels a unique methodological paradigm, emphasizing the omnipresence of the Golden Ratio in shaping system dynamics. The novelty of this study stems from its detailed exposition of self-similarity and interchangeability, transforming them from mere abstract notions into actionable, concrete insights. By highlighting the fractal nature of the Golden Ratio, the implications of these revelations become far-reaching, heralding new avenues for both theoretical advancements and pragmatic applications across a spectrum of scientific disciplines.展开更多
This paper presents an innovative solution regarding complex systems to scientists, and prepares a novel system simulator for complex systems. A complex system in nature is not a black box but a solvable systematic pr...This paper presents an innovative solution regarding complex systems to scientists, and prepares a novel system simulator for complex systems. A complex system in nature is not a black box but a solvable systematic problem. The solution is not derived from conventional physics based on reductionism, but rather from engineering sciences such as the feedback systems analysis method and engineering principles. Furthermore, this paper presents the conception of the solution to scientists for solving the problem. Moreover, nobody can doubt this research based on simulator. Complex systems are not mysterious science and not black box.展开更多
This essay presents a reflection on the main implications of Complexity Theory for science in general, redefining and dispelling myths of traditional science, and Sociology in particular, suggesting a redefinition of ...This essay presents a reflection on the main implications of Complexity Theory for science in general, redefining and dispelling myths of traditional science, and Sociology in particular, suggesting a redefinition of Parsons’ classic concept of Social System, articulated around the property of self-maintenance of order rather than on its possible discontinuity and instability. It argues that Complexity Theory has established the limits of Classic Science, leading to a more realistic awareness of working and evolution mechanisms of Natural and Social Systems and showing the limits of our capacity to predict and control events. Dissipative structures have shown the creative role of time. Instability, emergence, surprise, unpredictability are the rule rather than the exception when systems move away from equilibrium (entropy), even if these processes are generated from a system’s deterministic working mechanisms. Therefore, we have come to realize how constructive the contribution of Complexity is, in regards to the long lasting problem of the relationship between order and disorder. Today, the terms of this relationship have been re-specified in its new configuration of inter-relationship link, according to a unicum which finds its synthesis in self-organization and deterministic chaos concepts. From this perspective, as Prigogine suggested, studies on Complex Systems are heading toward a historical, biological conception of Physics, and a new alliance between natural systems and living, social systems. Non-linearity, far from equilibrium self-organization, emergence and surprise meet at all levels, as this paper attempts to highlight. In Sociology, insights of Complexity Theory have contributed to a new way of thinking about social systems, by re-addressing some fundamental issues starting to social system, emergence and change concepts. The current social system conception as complex dynamical systems is supported by a profitable use of non-liner models (in particular, the Logistic map) in the study of social processes.展开更多
A significant number and range of challenges besetting sustainability can be traced to the actions and inter actions of multiple autonomous agents(people mostly)and the entities they create(e.g.,institutions,policies,...A significant number and range of challenges besetting sustainability can be traced to the actions and inter actions of multiple autonomous agents(people mostly)and the entities they create(e.g.,institutions,policies,social network)in the corresponding social-environmental systems(SES).To address these challenges,we need to understand decisions made and actions taken by agents,the outcomes of their actions,including the feedbacks on the corresponding agents and environment.The science of complex adaptive systems-complex adaptive sys tems(CAS)science-has a significant potential to handle such challenges.We address the advantages of CAS science for sustainability by identifying the key elements and challenges in sustainability science,the generic features of CAS,and the key advances and challenges in modeling CAS.Artificial intelligence and data science combined with agent-based modeling promise to improve understanding of agents’behaviors,detect SES struc tures,and formulate SES mechanisms.展开更多
For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The propose...For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The proposed algorithm integrates two-point and multi-point time correlation functions into a unified framework.Further,it is verified by a practical application in complex financial systems,demonstrating its potential in various complex dynamic systems.展开更多
This study examines the spatiotemporal evolution of Tibetan villages in western Sichuan through state transition models and predictive simulations to understand their complex dynamics and key driving factors.Using a c...This study examines the spatiotemporal evolution of Tibetan villages in western Sichuan through state transition models and predictive simulations to understand their complex dynamics and key driving factors.Using a combination of multivariate time-series analysis and chaotic attractor identification,the research identifies forest cover,economic growth,employment rates,road density,and communication network coverage as critical determinants of village trajectories.For instance,Molo Village recovers rapidly with a 10%increase in regional economic growth,while Xisuo Village becomes unstable with employment rate fluctuations above 2%.Shenzuo Village benefits from improved road density,and Minzu Village’s stability depends on forest cover.Jiangba Village relies on the growth of irrigated farmland and communication network coverage,whereas Kegeyi Village exhibits periodic dynamics and high sensitivity to employment variations.The findings underscore the inherent complexity and nonlinearity of rural systems,revealed through chaotic attractor analysis,which highlights the system’s sensitivity to initial conditions and external shocks.The article provides actionable insights into resilience mechanisms and offers practical recommendations for the sustainable development of culturally and ecologically sensitive regions.Emphasis on tailored management strategies is essential to meet the challenges faced by these unique systems in the face of modernization and environmental change.展开更多
文摘The ability to accurately simulate the time evolu-tion of quantum systems stands as a cornerstone of modern molecular science.It provides the essential mechanistic bridge between a system’s microscopic structure and its macroscopic function,a challenge first envisioned by Feynman.The central difficulty,and the unifying theme of this Special Topic,is the problem of“complexity”:a multifaceted challenge arising from the interplay of strongly coupled electronic and vibrational degrees of freedom,quantum statistics,and the non-trivial,often non-Markovian,memory effects exerted by a surrounding environment.
基金supported by the Natural Science Foundation of China underGrant 61833016 and 61873293the Shaanxi OutstandingYouth Science Foundation underGrant 2020JC-34the Shaanxi Science and Technology Innovation Team under Grant 2022TD-24.
文摘In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.
基金Supported by the Science Foundation of the Ministry of Education of China for the Returned Overseas Chinese Scholars
文摘Researches on organization and structure in complex systems are academic and industrial fronts in modern sciences. Though many theories are tentatively proposed to analyze complex systems, we still lack a rigorous theory on them. Complex systems possess various degrees of freedom, which means that they should exhibit all kinds of structures. However, complex systems often show similar patterns and structures. Then the question arises why such similar structures appear in all kinds of complex systems. The paper outlines a theory on freedom degree compression and the existence of hierarchical self-organization for all complex systems is found. It is freedom degree compression and hierarchical self-organization that are responsible for the existence of these similar patterns or structures observed in the complex systems.
文摘Related to complexity, there is a wide diversity of concepts, ranging from ‘‘systemic" to ‘‘complex", implying a need for a unified terminology. Per different authors, the main drivers of complexity can be found in human behaviour and uncertainty. This complexity, structural or dynamic can be organizational, technological, or nested in their relationship. ISO international standard 31000:2009 definition of risk management ‘‘coordinated activities to direct and control an organization with regard to risk", when applied to economic sectors, industry, services, project, or activity, it requires the use of models or theories as guidelines. Therefore, as its basic elements comprehend human behaviour and/or uncertainty, risk management to be effective and adapted as much as possible to reality, must be operational within complex systems, as already demonstrated in different R&D environments. Risk management faces demanding challenges when approaching specific and endogenous needs, such as the mining sector. This paper presents a multivariable function analysis methodology approach based on complex system modelling and through real data corresponding to a risk management tool in the mining sector.
基金supported by the National Natural Science Foundation of China(Nos.61773388,61751304,61833016,and 61702142)the Shaanxi Outstanding Youth Science Foundation(No.2020JC-34)the Key Research and Development Plan of Hainan(No.ZDYF2019007)。
文摘The composition of the modern aerospace system becomes more and more complex.The performance degradation of any device in the system may cause it difficult for the whole system to keep normal working states.Therefore,it is essential to evaluate the performance of complex aerospace systems.In this paper,the performance evaluation of complex aerospace systems is regarded as a Multi-Attribute Decision Analysis(MADA)problem.Based on the structure and working principle of the system,a new Evidential Reasoning(ER)based approach with uncertain parameters is proposed to construct a nonlinear optimization model to evaluate the system performance.In the model,the interval form is used to express the uncertainty,such as error in testing data and inaccuracy in expert knowledge.In order to analyze the subsystems that have a great impact on the performance of the system,the sensitivity analysis of the evaluation result is carried out,and the corresponding maintenance strategy is proposed.For a type of Inertial Measurement Unit(IMU)used in a rocket,the proposed method is employed to evaluate its performance.Then,the parameter sensitivity of the evaluation result is analyzed,and the main factors affecting the performance of IMU are obtained.Finally,the comparative study shows the effectiveness of the proposed method.
文摘THE Industrial Revolution starting from about 1760 and ending at around 1840 has been viewed as the first Industrial Revolution.It features with the replacement of human and animal muscle power with steam and mechanical power.Human income per capita had taken 800 years to double by
文摘This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.
基金funded by the Serbian Ministry of Science and Technology under the project No.III 43007“Research of climate changes and their impact on environment.Monitoring of the impact,adaptation and moderation”for 2011-2014.
文摘The field of environmental sciences is abundant with various interfaces and is the right place for the application of new fundamental approaches leading towards a better understanding of environmental phenomena. Following the definition of environmental interface by Mihailovic and Bala? [1], such interface can be, for example, placed between: human or animal bodies and surrounding air, aquatic species and water and air around them, and natural or artificially built surfaces (vegetation, ice, snow, barren soil, water, urban communities) and the atmosphere, cells and surrounding environment, etc. Complex environmental interface systems are (i) open and hierarchically organised (ii) interactions between their constituent parts are nonlinear, and (iii) their interaction with the surrounding environment is noisy. These systems are therefore very sensitive to initial conditions, deterministic external perturbations and random fluctuations always present in nature. The study of noisy non-equilibrium processes is fundamental for modelling the dynamics of environmental interface regarded as biophysical complex system and for understanding the mechanisms of spatio-temporal pattern formation in contemporary environmental sciences. In this paper we will investigate an aspect of dynamics of energy flow based on the energy balance equation. The energy exchange between interacting environmen- tal interfaces regarded as biophysical complex systems can be represented by coupled maps. Therefore, we will numerically investigate coupled maps representing that exchange. In ana- lysis of behaviour of these maps we applied Lyapunov exponent and cross sample entropy.
基金supported in part by the Shanghai Municipal Science and Technology,China Major Project(No.2021SHZDZX0100)in part by the National Natural Science Foundation of China(Nos.62073241,62088101,62103303)+1 种基金in part by the Shanghai Municipal Commission of Science and Technology,China Project(No.19511132101)and in part by the Fundamental Research Funds for the Central Universities(No.22120200077)。
文摘In this paper,we review some existing control methodologies for complex systems with particular emphasis on those that are near critical.Due to the shortage of the classical control theory in handling complex systems,the reviewed control methods are mainly associated with machine learning techniques,game-theoretical approaches,and sparse control strategies.Additionally,several interesting and promising directions for future research are also proposed.
文摘The fundamental and simplest structure of a complex system is a network.According to this idea,we plan to develop a general methematical framework of complex systems.In this paper,we discuss in detail the concept of systems,a general description of systems:System=(Hardware,Software,Environment),and whole-part relations,including relations between elements and systems,subsystems and systems,and between systems.The rules of operations of systems are given,and the induced transformations between hardware and software of systems are briefly discussed.
基金Under the auspices of the National Natural Science Foundation of China(No.40131020), and British Council's A-cademic Links with China Scheme(SHA/992/304)
文摘Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the context of complex system thinking. Three features of complex systems are that they are uncertain, non-linear and self-organizing. Modeling regional development requires a consideration of these features. This paper discusses the feasibility of using the artificial neural networt(ANN) to establish an adjustment prediction model for the complex systems of sustainable development (CSSD). Shanghai Municipality was selected as the research area to set up the model, from which reliable prediction data were produced in order to help regional development planning. A new approach, which could help to manage regional sustainable development, is then explored.
文摘The purpose of this work is to analyze the electrical properties of the metal–semiconductor contact(MSC)in the framework of the theory of complex systems.The effect of inhomogeneity of the different microstructures:polycrystalline,monocrystalline,amorphous metal–semiconductor contact surface is investigated,considering a Schottky diode(SD)as a parallel connection of numerous subdiodes.It has been shown that the polycrystallinity of the metal translates a homogeneous contact into a complex system,which consists of parallel connected numerous elementary contacts having different properties and parameters.
基金the National Natural Science Foundation of China(Grant Nos.60874009 and 10971120)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2010FM010)
文摘This paper deals with the finite-time stabilization of unified chaotic complex systems with known and unknown parameters. Based on the finite-time stability theory, nonlinear control laws are presented to achieve finite-time chaos control of the determined and uncertain unified chaotic complex systems, respectively. The two controllers are simple, and one of the uncertain unified chaotic complex systems is robust. For the design of a finite-time controller on uncertain unified chaotic complex systems, only some of the unknown parameters need to be bounded. Simulation results for the chaotic complex Lorenz, Lu¨ and Chen systems are presented to validate the design and analysis.
基金Supported by Lanzhou University key fund project"Modelling Principle and Approaches for Complex Systems
文摘In this paper, by use of equivalence operators δi and semi-equivalence operators Εi we study the clustering problems of complex systems, present δ (1,3) disconnection principle, dual transformation principle and large-scale systems decomposition principle for analizing and operating complex systems, discuss interconnectivity and disconnectivity of complex systems in detail and present some related theorems. Finally, we discuss the levels of systems according to pansystems clustering approach proposed in this paper.
文摘The Golden Ratio Theorem, deeply rooted in fractal mathematics, presents a pioneering perspective on deciphering complex systems. It draws a profound connection between the principles of interchangeability, self-similarity, and the mathematical elegance of the Golden Ratio. This research unravels a unique methodological paradigm, emphasizing the omnipresence of the Golden Ratio in shaping system dynamics. The novelty of this study stems from its detailed exposition of self-similarity and interchangeability, transforming them from mere abstract notions into actionable, concrete insights. By highlighting the fractal nature of the Golden Ratio, the implications of these revelations become far-reaching, heralding new avenues for both theoretical advancements and pragmatic applications across a spectrum of scientific disciplines.
文摘This paper presents an innovative solution regarding complex systems to scientists, and prepares a novel system simulator for complex systems. A complex system in nature is not a black box but a solvable systematic problem. The solution is not derived from conventional physics based on reductionism, but rather from engineering sciences such as the feedback systems analysis method and engineering principles. Furthermore, this paper presents the conception of the solution to scientists for solving the problem. Moreover, nobody can doubt this research based on simulator. Complex systems are not mysterious science and not black box.
文摘This essay presents a reflection on the main implications of Complexity Theory for science in general, redefining and dispelling myths of traditional science, and Sociology in particular, suggesting a redefinition of Parsons’ classic concept of Social System, articulated around the property of self-maintenance of order rather than on its possible discontinuity and instability. It argues that Complexity Theory has established the limits of Classic Science, leading to a more realistic awareness of working and evolution mechanisms of Natural and Social Systems and showing the limits of our capacity to predict and control events. Dissipative structures have shown the creative role of time. Instability, emergence, surprise, unpredictability are the rule rather than the exception when systems move away from equilibrium (entropy), even if these processes are generated from a system’s deterministic working mechanisms. Therefore, we have come to realize how constructive the contribution of Complexity is, in regards to the long lasting problem of the relationship between order and disorder. Today, the terms of this relationship have been re-specified in its new configuration of inter-relationship link, according to a unicum which finds its synthesis in self-organization and deterministic chaos concepts. From this perspective, as Prigogine suggested, studies on Complex Systems are heading toward a historical, biological conception of Physics, and a new alliance between natural systems and living, social systems. Non-linearity, far from equilibrium self-organization, emergence and surprise meet at all levels, as this paper attempts to highlight. In Sociology, insights of Complexity Theory have contributed to a new way of thinking about social systems, by re-addressing some fundamental issues starting to social system, emergence and change concepts. The current social system conception as complex dynamical systems is supported by a profitable use of non-liner models (in particular, the Logistic map) in the study of social processes.
基金The National Science Foundation funded this research under the Dy-namics of Coupled Natural and Human Systems program(Grants No.DEB-1212183 and BCS-1826839)support from San Diego State University and Auburn University.
文摘A significant number and range of challenges besetting sustainability can be traced to the actions and inter actions of multiple autonomous agents(people mostly)and the entities they create(e.g.,institutions,policies,social network)in the corresponding social-environmental systems(SES).To address these challenges,we need to understand decisions made and actions taken by agents,the outcomes of their actions,including the feedbacks on the corresponding agents and environment.The science of complex adaptive systems-complex adaptive sys tems(CAS)science-has a significant potential to handle such challenges.We address the advantages of CAS science for sustainability by identifying the key elements and challenges in sustainability science,the generic features of CAS,and the key advances and challenges in modeling CAS.Artificial intelligence and data science combined with agent-based modeling promise to improve understanding of agents’behaviors,detect SES struc tures,and formulate SES mechanisms.
基金Project supported by the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(Grant No.GZC20231050)the National Natural Science Foundation of China(Grant Nos.12175193 and 11905183)the 13th Five-year plan for Education Science Funding of Guangdong Province(Grant No.2021GXJK349)。
文摘For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The proposed algorithm integrates two-point and multi-point time correlation functions into a unified framework.Further,it is verified by a practical application in complex financial systems,demonstrating its potential in various complex dynamic systems.
文摘This study examines the spatiotemporal evolution of Tibetan villages in western Sichuan through state transition models and predictive simulations to understand their complex dynamics and key driving factors.Using a combination of multivariate time-series analysis and chaotic attractor identification,the research identifies forest cover,economic growth,employment rates,road density,and communication network coverage as critical determinants of village trajectories.For instance,Molo Village recovers rapidly with a 10%increase in regional economic growth,while Xisuo Village becomes unstable with employment rate fluctuations above 2%.Shenzuo Village benefits from improved road density,and Minzu Village’s stability depends on forest cover.Jiangba Village relies on the growth of irrigated farmland and communication network coverage,whereas Kegeyi Village exhibits periodic dynamics and high sensitivity to employment variations.The findings underscore the inherent complexity and nonlinearity of rural systems,revealed through chaotic attractor analysis,which highlights the system’s sensitivity to initial conditions and external shocks.The article provides actionable insights into resilience mechanisms and offers practical recommendations for the sustainable development of culturally and ecologically sensitive regions.Emphasis on tailored management strategies is essential to meet the challenges faced by these unique systems in the face of modernization and environmental change.
