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The problem of chaos rapid judging in traffic flow was studied using neural networks with particle swarm optimization (PSO). Based on analyzing the demand of intelligent transportation system and the problems of the existing methods of chaos identifying, the intelligent method of chaos rapid judging in traffic flow was proposed. The principle and the structure of the system are briefly introduced...
To solve the problem that a single model can not precisely describe the global properties of the lumber moisture content (LMC) during the wood drying process, LMC measurement based multi-modeling method is presented in this paper. The method based on double layers intelligent structure which Fuzzy C-Means clustering is classification layer to classify equivalent resistance value, the inlet ambient...
Aimed to the problem that it is hardship to get real-time and on-line measuring parameters in wood drying process, a novel PSO-SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to improve the nonlinearity caused by ambient temperature and other disturbance factors is presented. Support vector machines (SVM) based on statistical learning theory and structural...
The rapid recognition problem of chaos in traffic flow was studied by using rough set neural network. Based on analyzing the demand of intelligent transportation system and the problems of the exiting recognition methods of chaos in traffic flow, the intelligent recognition method of chaos was proposed. The principle and the structure of the system are briefly introduced. There are online recognition...
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