| 書目名稱 | Neural Networks and Micromechanics | | 編輯 | Ernst Kussul,Tatiana Baidyk,Donald C. Wunsch | | 視頻video | http://file.papertrans.cn/664/663707/663707.mp4 | | 概述 | This is an interdisciplinary field of research involving the use of neural network techniques for image recognition applied to tasks in the area of micromechanics..Includes supplementary material: | | 圖書封面 |  | | 描述 | Micromechanical manufacturing based on microequipment creates new possibi- ties in goods production. If microequipment sizes are comparable to the sizes of the microdevices to be produced, it is possible to decrease the cost of production drastically. The main components of the production cost - material, energy, space consumption, equipment, and maintenance - decrease with the scaling down of equipment sizes. To obtain really inexpensive production, labor costs must be reduced to almost zero. For this purpose, fully automated microfactories will be developed. To create fully automated microfactories, we propose using arti?cial neural networks having different structures. The simplest perceptron-like neural network can be used at the lowest levels of microfactory control systems. Adaptive Critic Design, based on neural network models of the microfactory objects, can be used for manufacturing process optimization, while associative-projective neural n- works and networks like ART could be used for the highest levels of control systems. We have examined the performance of different neural networks in traditional image recognition tasks and in problems that appear in micromechanical m | | 出版日期 | Book 2010 | | 關(guān)鍵詞 | Image recognition; Learning; Microassembly, micromachining; Micromechanics; Neural classifiers; Neural ne | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-02535-8 | | isbn_softcover | 978-3-642-42611-7 | | isbn_ebook | 978-3-642-02535-8 | | copyright | Springer-Verlag Berlin Heidelberg 2010 |
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