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Existing search engines—with Google at the top—have many remarkable capabilities; but what is not among them is deduction capability—the capability to synthesize an answer to a query from bodies of information which reside in various parts of the knowledge base. In recent years, impressive progress has been made in enhancing performance of search engines through the use of methods based on bivalent...
We present a new, human consistent approach to the summarization of numeric time series aimed at capturing the very essence of what occurs in the data in terms of an increase, decrease and stable values of data, when relevant changes occur, and how long are periods of particular behavior types exemplified by an increase, decrease and a stable period, all with some intensity. We use natural language...
Inspired by human’s remarkable capability to perform a wide variety of physical and mental tasks without any measurements and computations and dissatisfied with classical logic as a tool for modeling human reasoning in an imprecise environment, Lotfi A. Zadeh developed the theory and foundation of fuzzy logic with his 1965 paper “Fuzzy Sets” [1] and extended his work with his 2005 paper “Toward a...
This contribution deals with developments in the history of philosophy, logic, and mathematics during the time before and up to the beginning of fuzzy logic. Even though the term “fuzzy” was introduced by Lotfi A. Zadeh in 1964/65, it should be noted that older concepts of “vagueness” and “haziness” had previously been discussed in philosophy, logic, mathematics, applied sciences, and medicine. This...
Selected results of the survey on research, instruction and development work with fuzzy systems are presented. This study was carried out by the request of the International Fuzzy Systems Association (IFSA). Electronic questionnaire forms were sent to the IFSA Societies, relevant mailing lists and central persons in fuzzy systems, and 166 persons from 36 countries filled our form. Since our data set...
This paper focuses on two essential topics of the fuzzy area. The first is the reduction of fuzzy rule bases. The classical inference methods of fuzzy systems deal with dense rule bases where the universe of discourse is fully covered. By applying sparse or hierarchical rule bases the computational complexity can be decreased. The second subject of the paper is the introduction of some fuzzy rule...
This work tries to follow some agreements linguistic seem to have on the semantical concept of antonym, and to model by means of a membership function an antonym aP of a predicate P, whose use is known by a given μP
In this paper, we introduce a new type of computation called ‘‘Morphic Computing’’. Morphic Computing is based on Field Theory and more specifically Morphic Fields. We claim that Morphic Computing is a natural extension of Holographic Computation, Quantum Computation, Soft Computing, and DNA Computing. All natural computations bonded by the Turing Machine can be formalised and extended by our new...
We present a nonlinear functional analytic framework for modeling and processing fuzzy sets in terms of their membership functions. Let X = {x} denote a universe of discourse, and A, a fuzzy set of elements x in X and membership function μA. First, we formally introduce a class C = {Ã} of attributes Ã, and a judgment criterion J in the definition of μA; and explain the role of such an attribute- and...
World Wide Web search engines including Google, Yahoo and MSN have become the most heavily-used online services (including the targeted advertising), with millions of searches performed each day on unstructured sites. In this presentation, we would like to go beyond the traditional web search engines that are based on keyword search and the Semantic Web which provides a common framework that allows...
Human decision making procedures in problems related with analysis of time series data bases (TSDB) often use perceptions like “several days”, “high price”, “quickly increasing” etc. Computing with Words and Perceptions can be used to formalize perception based expert knowledge and inference mechanisms defined on numerical domains of TSDB. For extraction from TSDB perception based information relevant...
Our concern is with the development of tools useful for the construction of semantically intelligent web based systems. We indicate that fuzzy set based reasoning systems such as approximate reasoning provide a fertile framework for the construction of these types of tools. Central to this framework is the representation of knowledge as the association of a constraint with a variable. Here we study...
Humans often mimic nature in the development of new machines or systems. The human brain, particularly its faculty for perception and cognition, is the most intriguing model for developing intelligent systems. Human cognitive processes have a great tolerance for imprecision or uncertainty. This is of great value in solving many engineering problems as there are innumerable uncertainties in real-world...
In this overview paper, we highlight role of Soft Computing techniques for intelligent reservoir characterization and exploration, seismic data processing and characterization, well logging, reservoir mapping and engineering. Reservoir characterization plays a crucial role in modern reservoir management. It helps to make sound reservoir decisions and improves the asset value of the oil and gas companies...
Land covers mix and high input dimension are two important issues to affect the classification accuracy of remote sensing images. Fuzzy classification has been developed to represent the mixture of land covers. Two fuzzy classifiers of Fuzzy Rule-Based (FRB) and Fuzzy Neural Network (FNN) were studied to illustrate the interpretability of fuzzy classification. A hierarchical structure was proposed...
Real world applications of a decision model of relationships between goals based on fuzzy relations (DMRG) are presented. In contrast to other approaches the relationships between decision goals or criteria for each decision situation are represented and calculated explicitly. The application fields are decision making for financial services, optimization of production sequences in car manufacturing...
Decision making in environments that do not allow much algorithmic modeling is not easy. Even more difficulties arise when part of the knowledge is expressed through linguistic terms instead of numeric values. Agricultural Sciences are such environments and Plant Breeding is one of them. This is why Fuzzy Theories can be very useful in building Decision Support Systems in this field. This chapter...
The chapter summarizes the current state of the art of applying soft computing solutions in the chemical industry, based on the experience of The Dow Chemical Company and projects the future trends in the field, based on the expected future industrial needs. Several examples of successful industrial applications of different soft computing techniques are given: automated operating discipline, based...
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