scholarly journals SELF-ORGANIZATION IN COMPLEX SYSTEMS AS DECISION MAKING

2014 ◽  
Vol 17 (03n04) ◽  
pp. 1450016 ◽  
Author(s):  
V. I. YUKALOV ◽  
D. SORNETTE
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Mathematical Formulation ◽  
Conditional Entropy ◽  
Self Organization ◽  
Entropy Maximization ◽  
Natural Systems ◽  
Macroscopic States ◽  
System States ◽  
Statistical Systems

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems.

scholarly journals ALGORITHM FOR USING FUZZY LOGIC IN MANAGEMENT AND DECISION-MAKING MODELS

2020 ◽  
pp. 75-81
Author(s):  
V.A. Druzhynin ◽  
M.M. Stepanov ◽  
G.B. Zhyrov ◽  
L.O. Rіaba
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Complex Systems ◽  
Mathematical Formulation ◽  
Control Process ◽  
External Factors ◽  
Linguistic Variables ◽  
Control Actions ◽  
Decision Making Models ◽  
Fuzzy Logical

In real conditions, when the task of formally describing the control process of a rather complex process arises, it is necessary to take into account several external factors (parameters) and their values, which potentially tend to Infinity. At the same time, the system's response is not limited to just one control action. To automate the process of composing all possible combinations of linguistic descriptions of variables at the stage of fuzzy conditional statements and the decision-making mechanism on the use of control actions in the development of control and decision-making models, it is proposed to use fuzzy logical models. Ways to construct algorithms for converting input perturbations of complex systems into conceptual relations for automating the control process and supporting decision-making are considered. The fuzzy logic apparatus relation is used to formalize, process, and make decisions about the use of system control signals in response to external disturbances. Fuzzy control systems combine information from human experts (natural language) with measurements and mathematical models. Fuzzy Systems will turn the knowledge base into a mathematical formulation that has proven very effective in many applications. When designing a fuzzy system, many questions need to be answered, in particular in creating linguistic models to describe the functioning of complex systems, in particular radar mapping systems with recognition of objects on the ground and making decisions for controlling unmanned systems. Thus, at the stage of composing a set of fuzzy instructions (statements), it is of interest to formalize the following processes, such as determining all possible combinations of terms of linguistic variables and making a decision on the application of control actions, depending on external factors. In the process of formalizing the process of determining all possible combinations and terms of linguistic variables, it is necessary to create fuzzy instructions (rules) for managing a system or object for fuzzy-logical control models and decision-making in the process of developing models for the functioning of complex systems.

scholarly journals Integrating Value Considerations in the Decision Making for the Design of Biorefineries

2020 ◽  
Vol 26 (6) ◽  
pp. 2927-2955
Author(s):  
Mar Palmeros Parada ◽  
Lotte Asveld ◽  
Patricia Osseweijer ◽  
John Alexander Posada
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Research And Development ◽  
Design Process ◽  
Design Decision ◽  
Value Sensitive Design ◽  
Design Practice ◽  
Novel Approach ◽  
Design Alternatives ◽  
Biobased Production

AbstractBiobased production has been promoted as a sustainable alternative to fossil resources. However, controversies over its impact on sustainability highlight societal concerns, value tensions and uncertainties that have not been taken into account during its development. In this work, the consideration of stakeholders’ values in a biorefinery design project is investigated. Value sensitive design (VSD) is a promising approach to the design of technologies with consideration of stakeholders’ values, however, it is not directly applicable for complex systems like biorefineries. Therefore, some elements of VSD, such as the identification of relevant values and their connection to a technology’s features, are brought into biorefinery design practice. Midstream modulation (MM), an approach to promoting the consideration of societal aspects during research and development activities, is applied to promote reflection and value considerations during the design decision making. As result, it is shown that MM interventions during the design process led to new design alternatives in support of stakeholders' values, and allowed to recognize and respond to emerging value tensions within the scope of the project. In this way, the present work shows a novel approach for the technical investigation of VSD, especially for biorefineries. Also, based on this work it is argued that not only reflection, but also flexibility and openness are important for the application of VSD in the context of biorefinery design.

In-Between and Through: Architecture and Complexity

2005 ◽  
Vol 3 (3) ◽  
pp. 335-354 ◽  
Author(s):  
Clarissa Ribeiro Pereira de Almeida ◽  
Anja Pratschke ◽  
Renata La Rocca
Keyword(s):  
Complex System ◽  
Software Engineering ◽  
Complex Systems ◽  
Design Process ◽  
Three Dimensional ◽  
Self Organization ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling ◽  
Complex Thought ◽  
Basic Characteristics

This paper draws on current research on complexity and design process in architecture and offers a proposal for how architects might bring complex thought to bear on the understanding of design process as a complex system, to understand architecture as a way of organizing events, and of organizing interaction. Our intention is to explore the hypothesis that the basic characteristics of complex systems – emergence, nonlinearity, self-organization, hologramaticity, and so forth – can function as effective tools for conceptualization that can usefully extend the understanding of the way architects think and act throughout the design process. To illustrate the discussions, we show how architects might bring complex thought inside a transdisciplinary design process by using models such as software engineering diagrams, and three-dimensional modeling network environments such as media to integrate, connect and ‘trans–act’.

On curvelet CS reconstructed MR images and GA-based fuzzy conditional entropy maximization for segmentation

2019 ◽  
Vol 17 (01) ◽  
pp. 1950003
Author(s):  
Apurba Roy ◽  
Santi P. Maity
Keyword(s):  
Image Reconstruction ◽  
Linear Prediction ◽  
Random Noise ◽  
Curvelet Transform ◽  
Conditional Entropy ◽  
Mr Images ◽  
Recursive Filtering ◽  
Entropy Maximization ◽  
Residual Noise ◽  
Incomplete Measurement

In many practical situations, magnetic resonance imaging (MRI) needs reconstruction of images at low measurements, far below the Nyquist rate, as sensing process may be very costly and slow enough so that one can measure the coefficients only a few times. Segmentation of such subsampled reconstructed MR images for medical analysis and diagnosis becomes a challenging task due to the inherent complex characteristics of the MR images. This paper considers reconstruction of MR images at compressive sampling (or compressed sensing (CS)) paradigm followed by its segmentation in an integrated platform. Image reconstruction is done from incomplete measurement space with random noise injection iteratively. A weighted linear prediction is done for the unobserved space followed by spatial domain denoising through adaptive recursive filtering. The reconstructed images, however, suffer from imprecise and/or missing edges, boundaries, lines, curvatures etc. and residual noise. Curvelet transform (CT) is purposely used for removal of noise and for edge enhancement through hard thresholding and suppression of approximate subbands, respectively. Then a fuzzy entropy-based clustering, using genetic algorithms (GAs), is done for segmentation of sharpen MR Image. Extensive simulation results are shown to highlight performance improvement of both image reconstruction and segmentation of the reconstructed images along with relative gain over the existing works.

scholarly journals A review of the complexity approach to the study human (society)-nature interactions

2010 ◽  
Vol 90 (2) ◽  
pp. 109-137 ◽  
Author(s):  
Dragana Miljanovic
Keyword(s):  
Complex Systems ◽  
Complexity Theory ◽  
Complex Dynamics ◽  
Traditional Approach ◽  
Human Society ◽  
Natural Systems ◽  
Two Systems

Traditional approach to the study of society-nature interactions based on reductionism and linear causality is no longer fully capable of explaining complex dynamics of integrated socio-economic and natural systems. For this reason demands for complexity theory is growing. Understanding interactions between society and nature, human and their environment must come from the examination of how the two systems operate together, and not from examination of those systems themselves in isolation. Since our geographical community is not familiar enough with complexity theory, first part of article is devoted to outlining shift from reductionism to holism and complexity theory. In the second part, features of complex systems as it is human (society)-environment system are discussed. .

scholarly journals Managing the Complexity of Climate Change

2021 ◽  
Author(s):  
Shann Turnbull
Keyword(s):  
Climate Change ◽  
Complex Systems ◽  
Political Science ◽  
Common Good ◽  
Institutional Analysis ◽  
Tax Incentives ◽  
Individual Behaviour ◽  
Unit Of Analysis ◽  
Natural Systems ◽  
Ecological Governance

This paper indicates how the knowledge of complex systems can be put into practice to counter climate change. A contribution of the paper is to show how individual behaviour, institutional analysis, political science and management can be grounded and integrated into the complexity of natural systems to introduce mutual sustainability. Bytes are used as the unit of analysis to explain how nature governs complexity on a more reliable and comprehensive basis than can be achieved by humans using markets and hierarchies. Tax incentives are described to increase revenues while encouraging organisations to adopt elements of ecological governance found in nature and in some social organisations identified by Ostrom and the author. Ecological corporations provide benefits for all stakeholders. This makes them a common good to promote global common goods like enriching democracy from the bottom up while countering: climate change, pollution, and inequalities in power, wealth and income.

scholarly journals Emergence and Self-Organisation of Complex Systems: the role of energy flows and information a philosophical approach

2018 ◽  
Vol 2 (1) ◽  
pp. 31 ◽  
Author(s):  
Norbert Fenzl
Keyword(s):  
Complex Systems ◽  
Driving Forces ◽  
Open Systems ◽  
Structural Information ◽  
Self Organization ◽  
Specific Information ◽  
Philosophical Approach ◽  
Energy Flows ◽  
Energy And Material Flows

How order emerges from noise? How higher complexity arises from lower complexity? For what reason a certain number of open systems start interacting in a coherent way, producing new structures, building up cohesion and new structural boundaries? To answer these questions we need to precise the concepts we use to describe open and complex systems and the basic driving forces of self-organization.   We assume that self-organization processes are related to the flow and throughput of Energy and Matter and the production of system-specific Information. These two processes are intimately linked together: Energy and Material flows are the fundamental carriers of signs, which are processed by the internal structure of the system to produce system-specific structural Information (Is). So far, the present theoretical reflections are focused on the emergence of open systems and on the role of Energy Flows and Information in a self-organizing process. Based on the assumption that Energy, Mass and Information are intrinsically linked together and are fundamental aspects of the Universe, we discuss how they might be related to each other and how they are able to produce the emergence of new structures and systems. 

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