NDLI: Nature-Inspired Computation based on orthogonal intelligence optimization

Content Provider	IEEE Xplore Digital Library
Author	Yongxian Li Jiazhong Li
Copyright Year	2010
Description	Author affiliation: Transportation College, Zhejiang Normal University, Jinhua, China (Yongxian Li) \|\| College of Economics, Tianjin Polytechnic University, China (Jiazhong Li)
Abstract	In order to overcome premature convergence and low performance of existing intelligent optimization algorithms, a algorithm of Nature-Inspired Computation based on orthogonal intelligent optimization is put forward for continue and discrete function in this paper. The orthogonal intelligent optimization based on the variance analysis and variance ratio analysis of orthogonal design is developed, which provides further searching direction and searching range of orthogonal experiment. Because the characteristic of orthogonal design is easy to find an interval that contains the best solution in one arrayed calculation, the algorithm of orthogonal intelligent optimization based on the analysis of variance ratio is able to reuse in the optimization searching. The algorithm of Nature-Inspired Computation based on orthogonal intelligent optimization has less calculation amount, shorter searching time, more rapid speed and higher accuracy of optimization searching. The simulation analysis for nonlinear programming problem is performed successfully. The simulation result shows that this algorithm is much better than existing algorithms of Nature-Inspired Computation.
Starting Page	402
Ending Page	406
File Size	267933
Page Count	5
File Format	PDF
ISBN	9781424459582
e-ISBN	9781424459612
DOI	10.1109/ICNC.2010.5582916
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis variance ratio Nature-Inspired Computation Intelligent optimization Computational modeling Biological system modeling orthogonal design Programming Arrays Particle swarm optimization Optimization Swarm Intelligence
Content Type	Text
Resource Type	Article

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