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删除53字节 、 2018年8月9日 (四) 22:18
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Advocates of hybrid models (combining neural networks and symbolic approaches), claim that such a mixture can better capture the mechanisms of the human mind.<ref>Sun and Bookman (1990)</ref><ref>{{Cite journal| last1 = Tahmasebi | last2 = Hezarkhani | title = A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation | url = http://www.sciencedirect.com/science/article/pii/S0098300412000398 | year = 2012| journal = Computers & Geosciences | pages = 18–27 | volume = 42| doi = 10.1016/j.cageo.2012.02.004 | bibcode = 2012CG.....42...18T }}</ref>
 
Advocates of hybrid models (combining neural networks and symbolic approaches), claim that such a mixture can better capture the mechanisms of the human mind.<ref>Sun and Bookman (1990)</ref><ref>{{Cite journal| last1 = Tahmasebi | last2 = Hezarkhani | title = A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation | url = http://www.sciencedirect.com/science/article/pii/S0098300412000398 | year = 2012| journal = Computers & Geosciences | pages = 18–27 | volume = 42| doi = 10.1016/j.cageo.2012.02.004 | bibcode = 2012CG.....42...18T }}</ref>
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==Types==
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==类型==
 
<!-- Split to [[Types of artificial neural networks]] -->
 
<!-- Split to [[Types of artificial neural networks]] -->
 
{{Main|Types of artificial neural networks}}
 
{{Main|Types of artificial neural networks}}
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Artificial neural networks have many variations. The simplest, static types have one or more static components, including number of units, number of layers, unit weights and [[topology]]. Dynamic types allow one or more of these to change during the learning process. The latter are much more complicated, but can shorten learning periods and produce better results. Some types allow/require learning to be "supervised" by the operator, while others operate independently. Some types operate purely in hardware, while others are purely software and run on general purpose computers.
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人工神经网络有很多类型。最简单的静态类型有一个或多个静态部分,包括一些单元,一些层,单元权重和[https://en.wikipedia.org/wiki/Topology 拓扑学]。动态类型允许这些中的一个或多个在学习过程中变化。后者更复杂,但是可以缩短学习时长并且产生更好的结果。一些类型允许/需要被操作“监督”,而另一些操作独立。一些类型的操作完全在硬件层面,而其他的完全在软件而且在通用计算机上运行。
    
==Gallery==
 
==Gallery==

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