Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

Patterns of Interactions of the Complex City System:Emotional Urban Objects as Triggering Agents-A Secondary Publication

This article presents an analysis of the patterns of interactions resulting from the positive and negative emotional events that occur in cities,considering them as complex systems.It explores,from the imaginaries,how certain urban objects can act as emotional agents and how these events affect the urban system as a whole.An adaptive complex systems perspective is used to analyze these patterns.The results show patterns in the processes and dynamics that occur in cities based on the objects that affect the emotions of the people who live there.These patterns depend on the characteristics of the emotional charge of urban objects,but they can be generalized in the following process:(1)immediate reaction by some individuals;(2)emotions are generated at the individual level which begins to generalize,permuting to a collective emotion;(3)a process of reflection is detonated in some individuals from the reading of collective emotions;(4)integration/significance in the community both at the individual and collective level,on the concepts,roles and/or functions that give rise to the process in the system.Therefore,it is clear that emotions play a significant role in the development of cities and these aspects should be considered in the design strategies of all kinds of projects for the city.Future extensions of this work could include a deeper analysis of specific emotional events in urban environments,as well as possible implications for urban policy and decision making.

APPLICATION STUDY ON ADAPTIVE NEURAL FUZZY INFERENCE MODEL IN COMPLEX SOCIAL-TECHNICAL SYSTEM

The adaptive neural fuzzy inference system （ANFIS） is used to make a ease study considering features of complex social-technical system with the target of increasing organizational efficiency of public scientific research institutions. An integrated ANFIS model is built and the effectiveness of the model is verified by means of investigation data and their processing results. The model merges the learning mechanism of neural network and the language inference ability of fuzzy system, and thereby remedies the defects of neural network and fuzzy logic system. Result of this case study shows that the model is suitable for complicated socio-technical systems and has bright application perspective to solve such problems of prediction, evaluation and policy-making in managerial fields.

Chromatic Adaptation to Complex Field

Chromatic adaptation of human eyes to complex field is investigated using binocular asymmetric matching method. The results show that the leve of chromatic adapta- tion mainly depends on the average color of adapting field, whereas no obvious change oc- curs when the number of hues and their color differences vary in a complex field. The shifts of perceived color evoked by chromatic adaptation in CIE 1976 L U V color space are approximately proportional to the average color difference between the adapting field and reference field.

Complex Systems Theory: Some Considerations for Sociology

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.

Theory and model of water resources complex adaptive allocation system

Complex adaptive sys tem theory is a new and important embranchment of system science, which prov ides a new thought to research water resources allocation system. Based on the a nalysis of complexity and complex adaptive mechanism of water resources allocat ion system, a fire-new analysis model is presented in this paper. With t he description of dynamical mechanism of system, behavior characters of agents and the evaluation method of system status, an integrity research system is built to analyse the evolvement rule of water resources allocation system. A nd a brief research for the impact of water resources allocation in benefi cial regions of the Water Transfer from South to North China Project is conducted.

A Method for Reducing Ocean Wave-Induced Magnetic Noises in Shallow-Water MT Data Using a Complex Adaptive Filter

In shallow-water areas,the marine magnetotelluric(MT)method faces a challenge in the investigation of seabed conductivity structures due to electrical and magnetic noises induced by ocean waves,which seriously contaminate MT data.Ocean waves can affect electric and magnetic fields to different extents.In general,their influence on magnetic fields is considerably greater than that on electric fields.In this paper,a complex adaptive filter is adopted to reduce wave-induced magnetic noises in the frequency domain.The processing results of synthetic and measured MT data indicate that the proposed method can effectively reduce wave-induced magnetic noises and provide reliable apparent resistivity and phase data.

An exploratory study of the growth of the Accountable Care Organization and its impact on physician groups’ profit: a complex adaptive system approach

The emergence of Accountable Care Organizations(ACOs)in the landscape of the U.S.healthcare system marks a paradigm shift in healthcare operations.The potential impact of ACOs has been a topic of intense debate.Traditional analytical approaches do not lend themselves to examining the complex phenomenon of the emergence and growth of ACOs in the healthcare network.We adopt a complex adaptive system lens to examine the growth of ACOs among physician groups and explore factors that influence this growth.We also discuss the impact of ACOs on the profit of physician groups.An agent-based model was built to simulate physician groups'ACO entrance and exit based on a set of simple rules and their complex interactions with other agents.Based on the simulation results,we derive patterns of ACO expansion and contraction,following four stages of wait-and-see,rollercoaster,fast growth,and stabilizing.Findings suggest that the growth of ACOs is sensitive to the initial state of ACO membership.When the initial size of ACO membership increases,it helps to eliminate the rollercoaster stage.In addition,the growth of the ACO varies depending on the cost–quality tradeoff.When both cost and quality objectives can be met simultaneously,the growth of ACO membership follows wait-and-see and fast growth stages followed by a different stage that we term sticky state.The impact of ACOs on physician groups’cumulative profit varies by the service quality level of the physician group.Physician groups affiliated with insurance companies charging the lowest or the highest level of health insurance premiums are worse off with the ACO option.However,the ACO benefits physician groups affiliated with an insurance company charging a moderate level of premiums.

Multi-point Layout Planning for Multi-energy Power System Based on Complex Adaptive System Theory

Aiming at the problem of multi-point layout planning of a multi-energy power system,the output characteristics of a multi-energy power system composed of wind power generation,photovoltaic power generation,hydropower generation,traditional thermal power generation and solar thermal power generation are comprehensively analyzed.Combining power optimization planning with complex adaptive system theory,a multi-point layout planning model of multi-energy sources based on complex adaptive system theory is proposed.The model takes the minimum construction step size of each new energy source as the agent.Through the interaction between the agents and the accumulation of experience,the behavior rules are constantly changed,the installed positions of various types of power sources are adjusted,and the optimal layout scheme of various power capacities of each node is obtained.Moreover,an agent modeling method based on a simple rule emerging complex phenomena is proposed,which reveals the core idea of complex adaptive system theory—adaptability makes complexity.Taking an actual power grid in a certain region of China as an example,it is verified that the proposed method has a significant effect on improving the consumption of new energy,and has certain guiding significance for the actual engineering construction.

Ecological Network Resilience of Shiyang River Basin: An Arid Inland Watershed of Northwest China

Due to the uncertainties posed by climate change,resilience has become an increasingly important variable for evaluating regional ecosystem stability.The assessment of Ecological Network Resilience(ENR)is crucial for establishing mitigation strategies and sustainable socioeconomic development in arid regions.Shiyang River Basin is an arid watershed in Northwest China with complex characteristics,its ENR and spatial differentiation characteristics in 2020 were investigated in this work based on the Complex Adaptive System(CAS)theory.The results indicated that the mean Ecological Network Resilience Index(ENRI)value for the Shiyang River Basin was 0.390 in 2020,and the mean values in the southern mountainous,middle oasis,and northern desert regions of the basin were 0.598,0.461,and 0.237,respectively,demonstrating evident spatial differences.Additionally,the ENR of the basin exhibited distinct distribution characteristics across different dimension,whereas the trend of the integrated ENR of the basin was consistent with that of elemental,structural,and functional resilience,indicating the constructed three-region ENR model based on the logical relationship of element-structure-function was suitable for evaluation of the ENR in arid inland river watersheds.Furthermore,strategies for enhancing regional ENR were proposed from the perspective of adapting to climate change.

Thinking in three's: Changing surgical patient safety practices in the complex modern operating room

The three surgical patient safety events, wrong site surgery, retained surgical items (RSI) and surgical fires are rare occurrences and thus their effects on the complex modern operating room (OR) are difficult to study. The likelihood of occurrence and the magnitude of risk for each of these surgical safety events are undefined. Many providers may never have a personal experience with one of these events and training and education on these topics are sparse. These circumstances lead to faulty thinking that a provider won't ever have an event or if one does occur the provider will intuitively know what to do. Surgeons are not preoccupied with failure and tend to usually consider good outcomes, which leads them to ignore or diminish the importance of implementing and following simple safety practices. These circumstances contribute to the persistent low level occurrence of these three events and to the difficulty in generating sufficient interest to resource solutions. Individual facilities rarely have the time or talent to understand these events and develop lasting solutions. More often than not, even the most well meaning internal review results in a new line to a policy and some rigorous enforcement mandate. This approach routinely fails and is another reason why these problems are so persistent. Vigilance actions alone havebeen unsuccessful so hospitals now have to take a systematic approach to implementing safer processes and providing the resources for surgeons and other stake-holders to optimize the OR environment. This article discusses standardized processes of care for mitigation of injury or outright prevention of wrong site surgery, RSI and surgical fires in an action-oriented framework illustrating the strategic elements important in each event and focusing on the responsibilities for each of the three major OR agents-anesthesiologists, surgeons and nurses. A Surgical Patient Safety Checklist is discussed that incorporates the necessary elements to bring these team members together and influence the emergence of a safer OR.

Modelling Immune System:Principles,Models,Analysis and Perspectives

The biological immune system is a complex adaptive system.There are lots of benefits for building the model of the immune system.For biological researchers,they can test some hypotheses about the infection process or simulate the responses of some drugs.For computer researchers,they can build distributed,robust and fault tolerant networks inspired by the functions of the immune system.This paper provides a comprehensive survey of the literatures on modelling the immune system.From the methodology perspective,the paper compares and analyzes the existing approaches and models,and also demonstrates the focusing research effort on the future immune models in the next few years.

Comparing dynamical systems concepts and techniques for biomechanical analysis

Traditional biomechanical analyses of human movement are generally derived from linear mathematics.While these methods can be useful in many situations,they do not describe behaviors in human systems that are predominately nonlinear.For this reason,nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature.These analysis techniques have provided new insights into how systems(1) maintain pattern stability,(2) transition into new states,and(3) are governed by short-and long-term(fractal) correlational processes at different spatio-temporal scales.These different aspects of system dynamics are typically investigated using concepts related to variability,stability,complexity,and adaptability.The purpose of this paper is to compare and contrast these different concepts and demonstrate that,although related,these terms represent fundamentally different aspects of system dynamics.In particular,we argue that variability should not uniformly be equated with stability or complexity of movement.In addition,current dynamic stability measures based on nonlinear analysis methods(such as the finite maximal Lyapunov exponent) can reveal local instabilities in movement dynamics,but the degree to which these local instabilities relate to global postural and gait stability and the ability to resist external perturbations remains to be explored.Finally,systematic studies are needed to relate observed reductions in complexity with aging and disease to the adaptive capabilities of the movement system and how complexity changes as a function of different task constraints.

Theoretical convergence analysis of complex Gaussian kernel LMS algorithm

With the vigorous expansion of nonlinear adaptive filtering with real-valued kernel functions,its counterpart complex kernel adaptive filtering algorithms were also sequentially proposed to solve the complex-valued nonlinear problems arising in almost all real-world applications.This paper firstly presents two schemes of the complex Gaussian kernel-based adaptive filtering algorithms to illustrate their respective characteristics.Then the theoretical convergence behavior of the complex Gaussian kernel least mean square（LMS） algorithm is studied by using the fixed dictionary strategy.The simulation results demonstrate that the theoretical curves predicted by the derived analytical models consistently coincide with the Monte Carlo simulation results in both transient and steady-state stages for two introduced complex Gaussian kernel LMS algonthms using non-circular complex data.The analytical models are able to be regard as a theoretical tool evaluating ability and allow to compare with mean square error（MSE） performance among of complex kernel LMS（KLMS） methods according to the specified kernel bandwidth and the length of dictionary.

Understanding Agricultural Heritage Sites as Complex Adaptive Systems: The Challenge of Complexity

In rural life,everything is connected to everything else.Seen as a complex adaptive system,the ＂rural＂ in most regions of the world has evolved over many centuries and is well known to have endured invasive predations and conflicts and to have adapted to changing conditions,both physical and human,many times.Such changes are recorded in the culture and in the landscapes which have continuously evolved and which characterize rural places today.These features of contemporary rural life-economy,culture and landscape-are the key elements of rural systems.Interestingly,they have also become the elements that attract tourists to rural areas.This theoretical paper,starts from the position that the rural world as a whole is complex and that systems adjust in the face of uncertainty,and a type of dynamism that is generated externally in the form of shocks and stresses.Complex Adaptive Systems theory provides an excellent opportunity to examine living systems such as Globally Important Agricultural Heritage Systems （GIAHS） in China that can provide new perspectives on resilience and self-organizing capabilities of the system.The paper suggests that adopting such approaches in contemporary research will produce new insights of whole systems and stem the tide of mainstream scientific research that reduces systems to their component parts and studies them with micro-techniques,while mostly failing to reintegrate the component parts back into the system as a whole.By reviewing this approach in relation to GIAHS and by introducing tourism into the rural village system,as a perturbation,we can create new ways to understand the effects of rural development interventions in ancient landscapes such as those which cover many parts of rural China today.

STUDYING COMPLEX ADAPTIVE SYSTEMS

Complex adaptive systems （cas） - systems that involve many components that adapt or learn as they interact - are at the heart of important contemporary problems. The study of cas poses unique challenges： Some of our most powerful muthemutical tools, particularly methods involivng fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.

Robustness of critical points in a complex adaptive system： Effects of hedge behavior

In our recent papers, we have identified a class of phase transitions in the market-directed resource- allocation game, and found that there exists a critical point at which the phase transitions occur. The critical point is given by a certain resource ratio. Here, by performing computer simulations and theoretical analysis, we report that the critical point is robust against various kinds of human hedge behavior where the numbers of herds and contrarians can be varied widely. This means that the critical point can be independent of the total number of participants composed of normal agents, herds and contrarians, under some conditions. This finding means that the critical points we identified in this complex adaptive system （with adaptive agents） may also be an intensive quantity, similar to those revealed in traditional physical systems （with non-adaptive units）.

Globally Important Agricultural Heritage Systems(GIAHS)of China:the challenge of complexity in research

The challenge of researching Globally Important Agricultural Heritage Systems(GIAHS)as complex systems forms the subject matter of this study.Complex adaptive systems are those that combine natural ecological processes with human interactions to produce a mutually supportive agro-ecological system.In China,these highly varied systems have the added dimension of long historical time,in that they have evolved over many centuries and thus add a historical dimension to the natural and human dimensions of complexity.In preparing research on GIAHS,it is clear that seeing GIAHS sites as whole systems is an essential starting and ending point.Examining the adaptive capacity of a GIAHS with its multiple scales and complex interdependencies is a major challenge for researchers accustomed to specialized disciplinary thinking.A GIAHS represents a mature agro-ecological system with human agency as a central component that has been honed over many centuries,and has already adapted to many perturbations and changes.The beauty of the GIAHS is in the integration of custom,knowledge,and practice,and it should be studied for its"wholeness"as well as for its resilience and capacity for"self organization."The agro-ecological approach opens the possibility of researching a system as a whole and of taking its complexity seriously.This study reviews the essential features of the GIAHS as a complex adaptive system where uncertainty is normal and surprise is welcome and,in a case study of Qingtian rice–fish culture system,focuses on new perturbations,namely loss of young people and the introduction of tourism.

Desertification risk,economic resilience and social issues:From theory to practice

Land degradation and early forms of desertification in both advanced economies and emerging countries reflect complex socio-environmental processes driven by multiple interactions between biophysical and socioeconomic forces across different spatial scales.The present study investigates desertification risk,land degradation,and socio-demographic dynamics through the lens of“resilience,”adopting complex adaptive systems(CAS)thinking.The resilience of socio-environmental systems exposed to land degradation is defined as the capacity of a regional economy to respond to crises and reorganize by making changes to preserve functions,structure,and feedback,and to promote future development options.By reviewing the socioeconomic resilience of local socio-ecological systems exposed to land degradation,this study achieves a better comprehension of the multifaceted processes that lead to a higher risk of desertification and the intimate relationship with underlying population trends and demographic dynamics.A comprehensive approach based on resilience thinking was formulated to review both environmental and socio-demographic issues at the landscape scale,and provide a suitable foundation for sustainability science and regional development policies.

How Do Precision Medicine and System Biology Response to Human Body's Complex Adaptability？

In the field of life sciences, although system biology and ＂precision medicine＂ introduce some complex scientific methods and techniques, it is still based on the ＂analysis–reconstruction＂ of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the ＂analysis–reconstruction＂ concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will find the adaptability of complex system is not the obstacle that increases the difficulty of problem solving. It is the ＂exceptional＂, ＂right-hand man＂ that helping us to deal with the complexity of life more effectively.