Evolutionary computation techniques : a comparative perspective
- 作者： Cuevas, Erik, author.
- 其他作者：
- 其他題名：
- Studies in computational intelligence ;
- 出版： Cham : Springer International Publishing :Imprint: Springer
- 叢書名： Studies in computational intelligence,volume 686
- 主題： Evolutionary computation. , Engineering. , Computational Intelligence. , Artificial Intelligence (incl. Robotics)
- ISBN： 9783319511092 (electronic bk.) 、 9783319511085 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: Preface -- Introduction -- Multilevel segmentation in digital images -- Multi-Circle detection on images -- Template matching -- Motion estimation -- Photovoltaic cell design -- Parameter identification of induction motors -- White blood cells Detection in images -- Estimation of view transformations in images -- Filter Design.
- 摘要註: This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.
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讀者標籤：
- 系統號： 005382138 | 機讀編目格式
館藏資訊
This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.