英语翻译Artificial neural networks and fuzzy systems are similar in many ways.First,they both store knowledge and use it to make decisions on new inputs.Both can generalise; both produce correct responses despite minor variations in the input vec

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英语翻译Artificial neural networks and fuzzy systems are similar in many ways.First,they both store knowledge and use it to make decisions on new inputs.Both can generalise; both produce correct responses despite minor variations in the input vec
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英语翻译Artificial neural networks and fuzzy systems are similar in many ways.First,they both store knowledge and use it to make decisions on new inputs.Both can generalise; both produce correct responses despite minor variations in the input vec
英语翻译
Artificial neural networks and fuzzy systems are similar in many ways.First,they both store knowledge and use it to make decisions on new inputs.Both can generalise; both produce correct responses despite minor variations in the input vector.There are,however,fundamental differences between thetechniques,some of which weigh heavily in favour of fuzzy systems in certain applications.Artificial neural networks acquire knowledge through training.This has a major advantage:often the training set can be composed of actual observations of the physical world,rather than being formed of the human opinions used for fuzzy (or expert) systems.Pn other words,the
neural network ‘lets the data speak for itself‘.

英语翻译Artificial neural networks and fuzzy systems are similar in many ways.First,they both store knowledge and use it to make decisions on new inputs.Both can generalise; both produce correct responses despite minor variations in the input vec
人工神经网络和模糊系统在很多方面是相似的.首先,他们都是存储知识,和使用这些知识来对新的输入的做出决定.他们都能够进行概括;即使在输入的矢量有细小的变化时,也能够做出正确的反馈.然而,他们在技术方面还是有根本性的区别.在某些应用中的一些技术在很大程度上还是支持模糊系统的.人工神经系统通过培训获得知识.这是人工神经系统拥有一个主要优势:培训组并不是由应用于模糊(或者专家)系统的人类选择而形成的,而是由对物质世界的实际观察组成的.换句话说,神经网络让数据自己说话.
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人工神经网络和模糊系统在很多方面是相似的。首先,他们都是存储知识,和使用这些知识来对新的输入的做出决定。他们都能够进行概括;即使在输入的矢量有细小的变化时,也能够做出正确的反馈。然而,他们在技术方面还是有根本性的区别。在某些应用中的一些技术在很大程度上还是支持模糊系统的。人工神经系统通过培训获得知识。这是人工神经系统拥有一个主要优势:培训组并不是由应用于模糊(或者专家)系统的人类选择而形成的,而是...

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人工神经网络和模糊系统在很多方面是相似的。首先,他们都是存储知识,和使用这些知识来对新的输入的做出决定。他们都能够进行概括;即使在输入的矢量有细小的变化时,也能够做出正确的反馈。然而,他们在技术方面还是有根本性的区别。在某些应用中的一些技术在很大程度上还是支持模糊系统的。人工神经系统通过培训获得知识。这是人工神经系统拥有一个主要优势:培训组并不是由应用于模糊(或者专家)系统的人类选择而形成的,而是由对物质世界的实际观察组成
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