Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece
碩士 === 大葉大學 === 電機工程學系碩士在職專班 === 94 === PART Ⅰ Gene Network Modeling Computational intelligent approaches is adopted to construct the S-system of Eukaryotic cell cycle and Yeast cell cycle for further analysis of genetic regulatory networks. A highly nonlinear power-law differential equation is cons...
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ndltd-TW-094DYU014420132016-06-01T04:14:00Z http://ndltd.ncl.edu.tw/handle/47685969075671188403 Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece 基於計算智慧之基因網路建模暨機電系統控制 Wu cheng-tao 吳政道 碩士 大葉大學 電機工程學系碩士在職專班 94 PART Ⅰ Gene Network Modeling Computational intelligent approaches is adopted to construct the S-system of Eukaryotic cell cycle and Yeast cell cycle for further analysis of genetic regulatory networks. A highly nonlinear power-law differential equation is constructed to describe the transcriptional regulation of gene network from the time-courses dataset. Global artificial algorithm, based on hybrid differential evolution, can achieve global optimization for the highly nonlinear differential gene network modeling. The constructed gene regulatory networks will be a reference for researchers to realize the inhibitory and activatory operator for genes synthesis and decomposition in Eukaryotic cell cycle and Yeast cell cycle. PART Ⅱ Electromechanics Control The approach is to design an intelligent fuzzy controller for nonlinear inverted pendulum-and-crane system. The inverted pendulum system is first analytically modeled convert as a T-S fuzzy model. A robust optimal fuzzy controller is then designed to achieve angle- and position-control of the complex physical system. Simulation results show the proposed controller can balance the fuzzy system in very short time. C. T. Lin Y. N. Chung 林進燈 鍾翼能 2006 學位論文 ; thesis 30 en_US |
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碩士 === 大葉大學 === 電機工程學系碩士在職專班 === 94 === PART Ⅰ Gene Network Modeling
Computational intelligent approaches is adopted to construct the S-system of Eukaryotic cell cycle and Yeast cell cycle for further analysis of genetic regulatory networks. A highly nonlinear power-law differential equation is constructed to describe the transcriptional regulation of gene network from the time-courses dataset. Global artificial algorithm, based on hybrid differential evolution, can achieve global optimization for the highly nonlinear differential gene network modeling. The constructed gene regulatory networks will be a reference for researchers to realize the inhibitory and activatory operator for genes synthesis and decomposition in Eukaryotic cell cycle and Yeast cell cycle.
PART Ⅱ Electromechanics Control
The approach is to design an intelligent fuzzy controller for nonlinear inverted pendulum-and-crane system. The inverted pendulum system is first analytically modeled convert as a T-S fuzzy model. A robust optimal fuzzy controller is then designed to achieve angle- and position-control of the complex physical system. Simulation results show the proposed controller can balance the fuzzy system in very short time.
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C. T. Lin |
author_facet |
C. T. Lin Wu cheng-tao 吳政道 |
author |
Wu cheng-tao 吳政道 |
spellingShingle |
Wu cheng-tao 吳政道 Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece |
author_sort |
Wu cheng-tao |
title |
Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece |
title_short |
Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece |
title_full |
Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece |
title_fullStr |
Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece |
title_full_unstemmed |
Gene Network Modeling and Electromechanics Controlling Based on Computational Intellignece |
title_sort |
gene network modeling and electromechanics controlling based on computational intellignece |
publishDate |
2006 |
url |
http://ndltd.ncl.edu.tw/handle/47685969075671188403 |
work_keys_str_mv |
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