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Because traditional approaches for solving the simultaneous localization and map building (SLAM) problem have the limitation of computational complexity, imprecision of filter algorithm and fragile data association, soft computing technique has been used to solve the problem. In this paper, we reviewed the state of the art of the application of evolutionary algorithm, fuzzy logic and neural networks...
The following topics are dealt with: computational aspects of social networks; swarm-based computing; social network security; fast logic computation; middleware and component technology; smart home; complex networks and granular computing; intelligent systems; pattern analysis and optimization; business management applications; network control and intelligent computation; synergy between AI and brain...
The principle and step of performance evaluation of project management based on SVM and fuzzy rules are studied. The index system of performance evaluation of project management is set up. Then we built up the evaluation model on SVM and fuzzy rules. Finally, take some samples of project for an example, we carry on this model to instance. It can take a preferably evaluation, so that it is a viable...
Artificial neural networks (ANN) and fuzzy systems are the widely preferred artificial intelligence techniques for biological computational applications. While ANN is less accurate than fuzzy logic systems, fuzzy theory needs expertise knowledge to guarantee high accuracy. Since both the methodologies possess certain advantages and disadvantages, it is primarily important to compare and contrast these...
In this paper, a probabilistic fuzzy logic system (PFLS) is discussed for modeling the stochastic and imprecise information. The PFLS uses a 3-dimensional probabilistic fuzzy set to capture the imprecise stochastic information. A unique 3-dimensional probabilistic fuzzy logic is designed to perform rule inference under such imprecise and stochastic environment. When the PFLS and neural networks are...
Induction machines (IM) are widely employed as actuators in electromechanical driven system, and IMpsilas control problems, the demands of which are to realize energy saving and speed regulation, have become more significant than before. Efficiency and power factor are two crucial indices in energy saving control issues, and to realize economical running with remarkable efficiency and high power factor,...
We describe in this paper a new hybrid approach for optimization combining particle swarm optimization (PSO) and genetic algorithms (GAs) using fuzzy logic to integrate the results. The new evolutionary method combines the advantages of PSO and GA to give us an improved PSO+GA hybrid method fuzzy logic is used to combine the results of the PSO and GA in the best way possible. The new hybrid PSO+GA...
As the development of energy market and the interest for new energy recourses such as wind energy and solar energy, energy management system of distributed generation (DG) becomes significant for the stability and economic operation of the DG system. This paper introduced a basic structure of DG system and illustrated the principle of power forecasting using neutral network. Finally a novel energy...
This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS).This approach based on multi objective optimization mechanism for training parameters in antecedent part. It considers two cost functions as the objectives which are the maximum difference measurements between the real nonlinear system and the nonlinear model, and training mean square...
This paper addresses the problem of integrating successful existing implementations of Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS). The methodologies and challenges to integrate ATIS and ATMS are addressed in details. This paper discusses in details the development of a rule-based neuro-fuzzy logic to integrate existing ATIS and ATMS when they operate...
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