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Conference

Systems, Man and Cybernetics

About: Systems, Man and Cybernetics is an academic conference. The conference publishes majorly in the area(s): Fuzzy logic & Artificial neural network. Over the lifetime, 29896 publication(s) have been published by the conference receiving 802584 citation(s).

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29,896 results found


Journal ArticleDOI: 10.1109/TSMC.1973.4309314
01 Nov 1973-
Abstract: Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes some easily computable textural features based on gray-tone spatial dependancies, and illustrates their application in category-identification tasks of three different kinds of image data: photomicrographs of five kinds of sandstones, 1:20 000 panchromatic aerial photographs of eight land-use categories, and Earth Resources Technology Satellite (ERTS) multispecial imagery containing seven land-use categories. We use two kinds of decision rules: one for which the decision regions are convex polyhedra (a piecewise linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89 percent for the photomicrographs, 82 percent for the aerial photographic imagery, and 83 percent for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

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18,474 Citations


Journal ArticleDOI: 10.1109/TSMC.1985.6313399
T. Takagi1, Michio Sugeno1Institutions (1)
01 Jan 1985-
Abstract: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented. The premise of an implication is the description of fuzzy subspace of inputs and its consequence is a linear input-output relation. The method of identification of a system using its input-output data is then shown. Two applications of the method to industrial processes are also discussed: a water cleaning process and a converter in a steel-making process.

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Topics: Fuzzy set operations (69%), Fuzzy classification (68%), Genetic fuzzy systems (67%) ... show more

17,632 Citations


Journal ArticleDOI: 10.1109/21.256541
Jyh-Shing Roger Jang1Institutions (1)
01 May 1993-
Abstract: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data pairs. In the simulation, the ANFIS architecture is employed to model nonlinear functions, identify nonlinear components on-line in a control system, and predict a chaotic time series, all yielding remarkable results. Comparisons with artificial neural networks and earlier work on fuzzy modeling are listed and discussed. Other extensions of the proposed ANFIS and promising applications to automatic control and signal processing are also suggested. >

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Topics: Adaptive neuro fuzzy inference system (79%), Neuro-fuzzy (65%), Fuzzy control system (63%) ... show more

13,738 Citations


Journal ArticleDOI: 10.1109/3477.484436
01 Feb 1996-
Abstract: An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

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Topics: Metaheuristic (66%), Ant colony optimization algorithms (64%), Extremal optimization (63%) ... show more

10,378 Citations


Journal ArticleDOI: 10.1109/TSMC.1973.5408575
Lotfi A. Zadeh1Institutions (1)
01 Jan 1973-
Abstract: The approach described in this paper represents a substantive departure from the conventional quantitative techniques of system analysis. It has three main distinguishing features: 1) use of so-called ``linguistic'' variables in place of or in addition to numerical variables; 2) characterization of simple relations between variables by fuzzy conditional statements; and 3) characterization of complex relations by fuzzy algorithms. A linguistic variable is defined as a variable whose values are sentences in a natural or artificial language. Thus, if tall, not tall, very tall, very very tall, etc. are values of height, then height is a linguistic variable. Fuzzy conditional statements are expressions of the form IF A THEN B, where A and B have fuzzy meaning, e.g., IF x is small THEN y is large, where small and large are viewed as labels of fuzzy sets. A fuzzy algorithm is an ordered sequence of instructions which may contain fuzzy assignment and conditional statements, e.g., x = very small, IF x is small THEN Y is large. The execution of such instructions is governed by the compositional rule of inference and the rule of the preponderant alternative. By relying on the use of linguistic variables and fuzzy algorithms, the approach provides an approximate and yet effective means of describing the behavior of systems which are too complex or too ill-defined to admit of precise mathematical analysis.

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Topics: Fuzzy set operations (66%), Fuzzy number (65%), Type-2 fuzzy sets and systems (64%) ... show more

8,223 Citations


Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
20214
2020726
2019707
2018707
2017667
2016935

Top Attributes

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Conference's top 5 most impactful authors

MengChu Zhou

213 papers, 9.3K citations

Keith W. Hipel

123 papers, 1.7K citations

Saeid Nahavandi

109 papers, 935 citations

Krishna R. Pattipati

53 papers, 2K citations

Max Mulder

50 papers, 912 citations

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