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Stabilization of Chaotic Time Series by Proportional Pulse in the System Variable Based on Genetic Algorithm 被引量:1
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作者 Qing Li deling zheng Jianlong Zhou(Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China)(Handan iron and Steel Co., Handan 056015, China) 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 1999年第3期228-229,共2页
The PPSV (Proportional Pulse in the System Variable) algorithm is a convenient method for the stabilization of the chaotic time series. It does not require any previous knowledge of the system. The PPSV method also ha... The PPSV (Proportional Pulse in the System Variable) algorithm is a convenient method for the stabilization of the chaotic time series. It does not require any previous knowledge of the system. The PPSV method also has a shortcoming, that is, the determination off. is a procedure by trial and error, since it lacks of optimization. In order to overcome the blindness, GA (Genetic Algorithm), a search algorithm based on the mechanics of natural selection and natural genetics, is used to optimize the λi The new method is named as GAPPSV algorithm. The simulation results show that GAPPSV algorithm is very efficient because the control process is short and the steady-state error is small. 展开更多
关键词 STABILIZATION chaotic time series genetic algorithm
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Theory,Method and Application of a State Recognition Based on Theory of Evidence
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作者 deling zheng Xinbei Tang Wei Fang (Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China)(Peat Marwick Huazhen CPA Firm, 100020, China) 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 1999年第1期69-72,共4页
A new method of state recognition based on the theory of evidence was proposed. By this method, the plausible function which the sample awaiting recognition belongs to each category can be obtained through distance fu... A new method of state recognition based on the theory of evidence was proposed. By this method, the plausible function which the sample awaiting recognition belongs to each category can be obtained through distance function. For the marginal samples,two or a batch of evidences can be combined and a new plausible function can be obtained by new evidence. Then the categories of samples can be determined according to plausibility function. This method provides a beder reasoning framework. The result proves the rate of recoghition correctness. 展开更多
关键词 theory of evidence state recognition heating furnace
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