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Titlebook: Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Appli; Oscar Castillo,Patricia Ochoa,Jose S

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發(fā)表于 2025-3-21 17:16:39 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Appli
編輯Oscar Castillo,Patricia Ochoa,Jose Soria
視頻videohttp://file.papertrans.cn/279/278713/278713.mp4
概述Focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area.Demonstrates that using fuzzy systems combined
叢書名稱SpringerBriefs in Applied Sciences and Technology
圖書封面Titlebook: Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Appli; Oscar Castillo,Patricia Ochoa,Jose S
描述.This book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems..
出版日期Book 2021
關(guān)鍵詞Computational Intelligence; Fuzzy Logic; Differential Evolution Algorithm; Fuzzy Controller; Complex Con
版次1
doihttps://doi.org/10.1007/978-3-030-62133-9
isbn_softcover978-3-030-62132-2
isbn_ebook978-3-030-62133-9Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2021
The information of publication is updating

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發(fā)表于 2025-3-21 23:29:47 | 只看該作者
Conclusions, Type-1, Interval Type-2 and Generalized Type-2 fuzzy systems to be able to make a comparative study of the DE performance. In this case the different Differential Evolution variants were applied to a set of Benchmark control problems, and as a conclusion of our work we can state that the use of fuz
板凳
發(fā)表于 2025-3-22 03:29:32 | 只看該作者
2191-530X der in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems..978-3-030-62132-2978-3-030-62133-9Series ISSN 2191-530X Series E-ISSN 2191-5318
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發(fā)表于 2025-3-22 05:13:28 | 只看該作者
Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Appli
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發(fā)表于 2025-3-23 04:09:50 | 只看該作者
Xiaodan Du,Junle Yang,Jin Li,Jian Wang Differential Evolution variants were applied to a set of Benchmark control problems, and as a conclusion of our work we can state that the use of fuzzy logic to optimize the DE parameters improves performance, and for this book we have shown this with statistical tests.
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發(fā)表于 2025-3-23 06:50:37 | 只看該作者
Conclusions, Differential Evolution variants were applied to a set of Benchmark control problems, and as a conclusion of our work we can state that the use of fuzzy logic to optimize the DE parameters improves performance, and for this book we have shown this with statistical tests.
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