| 書目名稱 | Combining Artificial Neural Nets |
| 副標題 | Ensemble and Modular |
| 編輯 | Amanda J. C. Sharkey |
| 視頻video | http://file.papertrans.cn/231/230088/230088.mp4 |
| 概述 | There are no other books covering both modular and ensemble approaches (The ensemble approach uses a variety of methods to create a set of different nets trained on the same task; the modular approach |
| 叢書名稱 | Perspectives in Neural Computing |
| 圖書封面 |  |
| 描述 | The past decade could be seen as the heyday of neurocomputing: in which the capabilities of monolithic nets have been well explored and exploited. The question then is where do we go from here? A logical next step is to examine the potential offered by combinations of artificial neural nets, and it is that step that the chapters in this volume represent. Intuitively, it makes sense to look at combining ANNs. Clearly complex biological systems and brains rely on modularity. Similarly the principles of modularity, and of reliability through redundancy, can be found in many disparate areas, from the idea of decision by jury, through to hardware re- dundancy in aeroplanes, and the advantages of modular design and reuse advocated by object-oriented programmers. And it is not surprising to find that the same principles can be usefully applied in the field of neurocomput- ing as well, although finding the best way of adapting them is a subject of on-going research. |
| 出版日期 | Book 1999 |
| 關鍵詞 | Ensembl; cognition; genetic algorithm; neural network; proving; simulation; speech recognition |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4471-0793-4 |
| isbn_softcover | 978-1-85233-004-0 |
| isbn_ebook | 978-1-4471-0793-4Series ISSN 1431-6854 |
| issn_series | 1431-6854 |
| copyright | Springer-Verlag London Limited 1999 |
|Archiver|手機版|小黑屋|
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