Visions of Synergetics

1997 ◽  
Vol 07 (09) ◽  
pp. 1927-1951 ◽  
Author(s):  
Hermann Haken
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Order Parameter ◽  
Computer Network ◽  
Open Systems ◽  
Movement Patterns ◽  
Order Parameters ◽  
Self Organization ◽  
Computer Algorithms ◽  
Stability And Instability

Synergetics is an interdisciplinary field of research. It deals with open systems that are composed of many individual parts that interact with each other and that can form spatial, temporal, or functional structures by self-organization. The research goal of synergetics is three-fold: (1) Are there general principles of self-organization? (2) Are there analogies in the behavior of self-organizing systems? (3) Can new devices be constructed because of the results (1) and (2)? From a mathematical point of view, synergetics deals with nonlinear partial stochastic differential equations and studies their solutions close to those points where the solutions change their behavior qualitatively. As I will show in my article, synergetics in its present form is based on the concepts of stability and instability, control parameters, order parameters, and the slaving principle. The slaving principle allows one to compress the information that is necessary to describe complex systems into a few order parameters. This is possible if systems are close to their instability points. But it appears that the order parameter concept is also applicable to situations away from such instabilities. At the level of the order parameter equations, profound analogies between otherwise quite different systems become visible. This allows one to realize the same process (for instance dealing with information) on quite different material substrates. The order parameter concept and the slaving principle are explained and their extension to discrete noisy maps and to delay equations are mentioned. These results can be applied to pattern formation in fluids, lasers, semiconductors, plasmas, and other fields. A section is devoted to the analysis of spatio-temporal patterns in terms of order parameters and the slaving principle. It is shown how the concepts of synergetics can be utilized to devise a new type of computer for pattern recognition. In connection with preprocessing, it can recognize patterns that are shifted, scaled or rotated in space and that are deformed. It can recognize scenes and also facial expressions as well as movement patterns. The learning procedure is briefly outlined. Because of the analogy principle of synergetics, this computer allows for hardware realizations by means of semiconductors and lasers. Decision-making by humans or machines is interpreted by means of an analogy with pattern recognition. Further sections are devoted to recognition of dynamic processes and learning by machines. In this author's opinion, synergetics will find important applications in medicine, for instance in the analysis of MEG and EEG patterns, and in the development of devices with brain-like functions. Future tasks of synergetics will be the application of the order parameter concept and the slaving principle to the integration of specialized computers or computer algorithms, for instance for the recognition of faces, movement patterns, and so on, into a computer network for scene analysis and decision making. This will also hold for complicated production processes and so on. Generally speaking, the potentialities of synergetics are based on its self-organization principles.

SYNERGETICS: FROM PATTERN FORMATION TO PATTERN ANALYSIS AND PATTERN RECOGNITION

1994 ◽  
Vol 04 (05) ◽  
pp. 1069-1083 ◽  
Author(s):  
HERMANN HAKEN
Keyword(s):  
Pattern Analysis ◽  
Open Systems ◽  
Equations Of Motion ◽  
Order Parameters ◽  
Point Of View ◽  
Self Organization ◽  
Ginzburg Landau ◽  
Nonlinear Optical Devices ◽  
Ginzburg Landau Equations ◽  
Pattern Formations

It is by now well known that numerous open systems in physics (fluids, plasmas, lasers, nonlinear optical devices, semiconductors), chemistry and biology (morphogenesis) may spontaneously develop spatial, temporal or spatiotemporal structures by self-organization. Quite often, striking analogies between the corresponding patterns can be observed in spite of the fact that the underlying systems are of quite a different nature. In this paper I shall first give an outline of general concepts that allow us to deal with the spontaneous formation of structures from a unifying point of view that is based on concepts of instability, order parameters and enslavement. We shall discuss a number of generalized Ginzburg-Landau equations. In most cases treated so far, theory started from microscopic or mesoscopic equations of motion from which the evolving structures were derived. In my paper I shall address two further problems that are in a way the reverse, namely (1) Can we derive order parameters and the basic modes from observed experimental data? (2) Can we construct systems by means of an underlying dynamics that are capable of producing patterns or structures that we prescribe? In order to address (1), a new variational principle that may be derived from path intergrals is introduced and illustrated by examples. An approach to the problem (2) is illustrated by the device of a computer that recognizes patterns and that may be realized by various kinds of spontaneous pattern formations in semiconductors and lasers.

EXPERT MANAGEMENT SYSTEMS OF AGROTECHNOLOGIES IN CLOUD INFORMATION TECHNOLOGY

1970 ◽  
pp. 12-17
Author(s):  
I. М. Mikhaylenko ◽  
V. N. Timoshin
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Information System ◽  
Knowledge Base ◽  
Information Technologies ◽  
Agricultural Sector ◽  
Perennial Grasses ◽  
Management Decision ◽  
Agricultural Technologies ◽  
Automation Systems

The transition to "intellectual" agriculture is the main vector of modernization of the agricultural sector of the economy. It is based on integrated automation and robotization of production, the use of automated decision-making systems. This is inevitably accompanied by a significant increase in data flow from sensors, monitoring systems, meteorological stations, drones, satellites and other external systems. Farm management has the opportunity to use various online applications for accurate recommendations and making various kinds of management decisions. In this regard, the most effective use of cloud information technologies, allowing implementing the most complex information and technical level of automation systems for management of agricultural technologies. The purpose of this work is to test the approach to creating expert management decision support systems (DSS) through the knowledge base (KB), formed in the cloud information system. For this, we consider an example of constructing a DSS for choosing the optimal date for preparing forage from perennial grasses. A complete theoretical and algorithmic database of the analytical DSS implemented in the data processing center of the cloud information system is given. On its basis, a KB is formed for a variety of different decision-making conditions. This knowledge base is transmitted to the local DSS. To make decisions about the optimal dates for the preparation of the local DSS, two variants of algorithms are used. The first option is based on management models, and the second uses the pattern recognition method. The approbation of the algorithms was carried out according to the BZ from 50 cases. According to the results of testing, the method of pattern recognition proved to be more accurate, which provides a more flexible adjustment of the situation on the local DSS to a similar situation in the KB. The considered technique can be extended to other crops.

scholarly journals Liquid Crystal Ordering in the Hexagonal Phase of Rod-Coil Diblock Copolymers

Polymers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1262
Author(s):  
Mikhail A. Osipov ◽  
Maxim V. Gorkunov ◽  
Alexander A. Antonov
Keyword(s):  
Liquid Crystal ◽  
Order Parameter ◽  
Density Functional ◽  
Diblock Copolymers ◽  
Microphase Separation ◽  
Hexagonal Phase ◽  
Orientational Order ◽  
Order Parameters ◽  
Copolymer Composition ◽  
Rigid Rod

Density functional theory of rod-coil diblock copolymers, developed recently by the authors, has been generalised and used to study the liquid crystal ordering and microphase separation effects in the hexagonal, lamellar and nematic phases. The translational order parameters of rod and coil monomers and the orientational order parameters of rod-like fragments of the copolymer chains have been determined numerically by direct minimization of the free energy. The phase diagram has been derived containing the isotropic, the lamellar and the hexagonal phases which is consistent with typical experimental data. The order parameter profiles as functions of temperature and the copolymer composition have also been determined in different anisotropic phases. Finally, the spatial distributions of the density of rigid rod fragments and of the corresponding orientational order parameter in the hexagonal phase have been calculated.

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.

Multi-criteria decision making and pattern recognition based on similarity measures for Fermatean fuzzy sets

2021 ◽  
pp. 1-17
Author(s):  
Changlin Xu ◽  
Juhong Shen
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Intuitionistic Fuzzy Set ◽  
Similarity Measures ◽  
New Method ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making

 Higher-order fuzzy decision-making methods have become powerful tools to support decision-makers in solving their problems effectively by reflecting uncertainty in calculations better than crisp sets in the last 3 decades. Fermatean fuzzy set proposed by Senapati and Yager, which can easily process uncertain information in decision making, pattern recognition, medical diagnosis et al., is extension of intuitionistic fuzzy set and Pythagorean fuzzy set by relaxing the restraint conditions of the support for degrees and support against degrees. In this paper, we focus on the similarity measures of Fermatean fuzzy sets. The definitions of the Fermatean fuzzy sets similarity measures and its weighted similarity measures on discrete and continuous universes are given in turn. Then, the basic properties of the presented similarity measures are discussed. Afterward, a decision-making process under the Fermatean fuzzy environment based on TOPSIS method is established, and a new method based on the proposed Fermatean fuzzy sets similarity measures is designed to solve the problems of medical diagnosis. Ultimately, an interpretative multi-criteria decision making example and two medical diagnosis examples are provided to demonstrate the viability and effectiveness of the proposed method. Through comparing the different methods in the multi-criteria decision making and the medical diagnosis application, it is found that the new method is as efficient as the other methods. These results illustrate that the proposed method is practical in dealing with the decision making problems and medical diagnosis problems.

scholarly journals A New Hybrid Distance-Based Similarity Measure for Refined Neutrosophic sets and its Application in Medical Diagnosis

MATEMATIKA ◽  
2019 ◽  
Vol 35 (1) ◽  
pp. 83-94 ◽  
Author(s):  
Vakkas Ulucay ◽  
Adil Kılıç ◽  
Memet Şahin ◽  
Harun Deniz
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Image Segmentation ◽  
Similarity Measure ◽  
Real World ◽  
Medical Diagnosis ◽  
Neutrosophic Sets ◽  
Hybrid Distance

 In recent times, refined neutrosophic sets introduced by Deli [6] has been one of the most powerful and flexible approaches for dealing with complex and uncertain situations of real world. In particular, the decision making methods between refined neutrosophic sets are important since it has applications in various areas such as image segmentation, decision making, medical diagnosis, pattern recognition and many more. The aim of this paper is to introduce a new distance-based similarity measure for refined neutrosophic sets. The properties of the proposed new distance-based similarity measure have been studied and the findings are applied in medical diagnosis of some diseases with a common set of symptoms.

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. 

scholarly journals Order Parameters, Orientational Distribution Functions and Heliconical Tilt Angles of Oligomeric Liquid Crystals

2019 ◽  
Author(s):  
Richard Mandle ◽  
John W. Goodby
Keyword(s):  
Phase Transition ◽  
Liquid Crystals ◽  
Tilt Angle ◽  
Order Parameter ◽  
Nematic Phase ◽  
Liquid Crystalline ◽  
Thermal Evolution ◽  
Order Parameters ◽  
Distribution Functions ◽  
Orientational Distribution

We compare the order parameters, orientational distribution functions (ODF) and heliconical tilt angles of the TB phase exhibited by a liquid-crystalline dimer (CB7CB) to a tetramer (O47) and hexamer (O67) by SAXS/WAXS. Following the N-TB phase transition we find that all order parameters decrease, and while 〈P2 〉 remains positive 〈P4 〉 becomes negative. For all three materials the order parameter 〈P6 〉 is near zero in both phases. The ODF is sugarloaf-like in the nematic phase and volcano-like in the TB phase, allowing us to estimate the heliconical tilt angle of each material and its thermal evolution. The heliconical tilt angle appears to be largely independent of the material studied despite the differing number of mesogenic units.

Anisotropic Order Parameter in Two-Band Superconductivity

1998 ◽  
Vol 12 (29n31) ◽  
pp. 3099-3101 ◽  
Author(s):  
P. Konsin ◽  
N. Kristoffel ◽  
P. Rubin
Keyword(s):  
Order Parameter ◽  
Equation System ◽  
Order Parameters ◽  
Band Model ◽  
Gap Equation ◽  
Narrow Region ◽  
Interband Scattering ◽  
Parameter Symmetry ◽  
Order Parameter Symmetry

A two-overlapping band model of superconductivity with s+d interband scattering is investigated. The gap equation system has been solved numerically. Solutions of pure-d and -s, or of mixed s+d nature are possible. The pure Tcd(μ) or Tcs(μ) curves determine the onset of superconductivity with temperature lowering. In the under- and over-doped region pure-symmetry orderings are preferred. Mixed ordering can exist in a narrow region of μ, becoming narrower with T rising. The peculiarities of the and spectra are reflected in the behaviour of the order parameters. Order parameter symmetry can change with T and μ.

scholarly journals Coarse-graining for fast dynamics of order parameters in the phase-field model

2018 ◽  
Vol 376 (2113) ◽  
pp. 20170203 ◽  
Author(s):  
D. Jou ◽  
P. K. Galenko
Keyword(s):  
Master Equation ◽  
Thermodynamic Equilibrium ◽  
Phase Field ◽  
Order Parameter ◽  
Field Model ◽  
Local Thermodynamic Equilibrium ◽  
Phase Field Model ◽  
Coarse Graining ◽  
Order Parameters ◽  
Coarse Grained

In standard descriptions, the master equation can be obtained by coarse-graining with the application of the hypothesis of full local thermalization that is equivalent to the local thermodynamic equilibrium. By contrast, fast transformations proceed in the absence of local equilibrium and the master equation must be obtained with the absence of thermalization. In the present work, a non-Markovian master equation leading, in specific cases of relaxation to local thermodynamic equilibrium, to hyperbolic evolution equations for a binary alloy, is derived for a system with two order parameters. One of them is a conserved order parameter related to the atomistic composition, and the other one is a non-conserved order parameter, which is related to phase field. A microscopic basis for phenomenological phase-field models of fast phase transitions, when the transition is so fast that there is not sufficient time to achieve local thermalization between two successive elementary processes in the system, is provided. In a particular case, when the relaxation to local thermalization proceeds by the exponential law, the obtained coarse-grained equations are related to the hyperbolic phase-field model. The solution of the model equations is obtained to demonstrate non-equilibrium phenomenon of solute trapping which appears in rapid growth of dendritic crystals. This article is part of the theme issue ‘From atomistic interfaces to dendritic patterns’.

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