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本人编写的incremental 随机神经元网络算法,该算法最大的特点是可以保证approximation特性,而且速度快效果不错,可以作为学术上的比较和分析。
本人编写的incremental 随机神经元网络算法,该算法最大的特点是可以保证approximation特性,而且速度快效果不错,可以作为学术上的比较和分析。目前只适合benchmark的regression问题。
具体效果可参考
G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006.
-I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,
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实现了图形话的节点表示和样本生成,
图形话的结果分析...
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演化计算是基于随即搜索的新算法;它的技术模型源于自然的演化。下面是一个例子,该函数是典型的多峰(震动剧烈)的函数。用的算法是郭涛算法。...
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人工神经元的bp算法,可用于函数拟合,时间序列数据的预测,目前应用非常广泛...
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遗传算法的经典程序,初学者一定要
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algorithm, used in artificial intelligence
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