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The following topics are dealt with: intelligent system design; neural networks, AI and expert systems; evolutionary computation; genetic algorithms; natural language processing & machine translation; artificial life and artificial immune systems; rough and fuzzy rough set; gray system and cloud computing; cognitive radio and computer vision; pattern recognition and machine learning; fuzzy system...
This paper focuses on the comprehensive review of the literature on applications of rough set theory in Civil Engineering. The relationships between rough set theory and other mathematical methods, such as conventional statistical methods, fuzzy sets, and evidence theory, are briefly introduced. The applications of rough set theory in Civil Engineering are discussed in structure engineering, pavement...
The following topics are dealt with: neural networks; evolutionary computing and genetic algorithms; fuzzy systems and soft computing; particle swarm optimization; artificial life and artificial immune systems; systems biology and neurobiology; support vector machine; rough and fuzzy rough set; knowledge discovery and data mining; kernel methods; supervised & semi-supervised learning; hybrid system;...
Signal process method is very important in welding automation and arc sensor is a kind of welding-sensor which works on the relationship between welding current and arc length. The using of Wavelet transform (WT) for detecting of welding gun slop with arc sensor is discussed in this paper. Sensor structure is introduced at first, and then Wavelet transform (WT) is induced into its signal processing...
In rough set theory, decision table is a kind of especial and important knowledge system which has been applied in the decision support and data mining fields widely. But rough set method can only deal with the dispersed value attribute decision table advantageously. Therefore, rough set method is limited to the analysis of discrete value attribute decision table. A key problem of the analysis of...
The following topics are dealt with: AI and expert systems; artificial immune systems and bio-informatics; chaos theory; data mining; fuzzy set theory; genetic algorithm; information retrieval; intelligent control; intelligent decision making; intelligent information processing; intelligent recognition; intelligent robotics; machine learning; natural language & machine translation; neural networks;...
The paper adopts rough set reduction algorithm to reduce the influence factors of power plant selection and eliminate the uncorrelated attribution, through which we can obtain typical samples. After this, adopting fuzzy method to calculate the membership degree of the typical samples, which are looked on as the input of BP Neural Network and the expert values are as the expected output to train the...
This paper combines rough set and genetic algorithm with fuzzy theory to diagnose faults in aluminum electrolysis to save energy. Firstly the author gets the simplest decision table by using the rough set to reduce the initial decision table which is made up of the original data. Because of one of important part in rough set being the reduction of condition attribute so a satisfied result can be got...
Rough set theory offers a novel approach to manage uncertainty that has been used for the discovery of data dependencies, importance of features, patterns in sample data, feature space dimensionality reduction, and the classification of objects. Consequently, rough sets have been successfully employed for various image processing tasks including image segmentation, enhancement and classification....
This paper proposes a novel hybrid intelligent system denoted as genetic algorithm and rough set incorporated neural fuzzy inference system (GARSINFIS). Its network structure dynamically changes along with the evolving genetic algorithm based rough set clustering (GARSC) technique. When input data set is applied, only the most essential information is retained in the clustering result, as knowledge...
The rough set theory is a new mathematical tool to study vague and uncertain information, and is widely used in intelligent systems. In this paper, the basic ideas of rough set theory are introduced, and the notion of up and low approximation sets, attribute reduction, core and some extensions of rough set theory are also presented. Then the application of rough set theory in intelligent systems....
In this paper, we study the application of fuzzy set theory, genetic algorithms and rough set theory techniques to the control of the rectifier. A fuzzy adaptive control scheme with the aid of rough set theory via genetic algorithms (GAs) finding the center parameters in place of the classical control is proposed. On the one hand, genetic algorithm gets optimal parameters of an accurate domain model,...
A method to construct fuzzy rough model is proposed. By means of adaptive Gaustafason-Kessel (G-K) clustering algorithm, fuzzy partition can be accomplished and corresponding fuzzy clusters are achieved in data space. Then based on the search of cluster number and attribute subsets through GA search strategy, optimal FRM will be found, and a decision model can be built. The experiment results indicate...
This paper provides a broad overview of logical and black box approaches to fuzzy and rough hybridization. The logical approaches include theoretical, supervised learning, feature selection, and unsupervised learning. The black box approaches consist of neural and evolutionary computing. Since both theories originated in the expert system domain, there are a number of research proposals that combine...
An attribute reduction method based on fuzzy rough set is applied for the result obtained by PCA method and the recognition process use neural network ensemble. The method avoids losing of information caused by dispersing before rough set attribute reduction. The reduction result can reflect the classification ability of the original information system completely. As a result, the recognition accuracy...
Using rough sets to reason from data hinges on three basic concepts of rough sets theory: approximations, decision rules and dependencies. Main objective of reasoning from data is finding hidden patterns in data. Genetic algorithms provides a general frame to optimize problem solution of complex system without depending on the domain of problem, it is robust to many kinds of problem. In this paper...
Soft computing is gradually opening up several possibilities in bioinformatics, especially by generating low-cost, low-precision (approximate), good solutions. In this paper, we survey the role of different soft computing paradigms, like fuzzy sets (FSs), artificial neural networks (ANNs), evolutionary computation, rough sets (RSes), and support vector machines (SVMs), in this direction. The major...
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