人工神经网络在林业拟合问题中的应用

P. Radonja, M. Koprivica
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摘要

具有不同结构和不同激活函数的神经网络是解决许多近似问题的有力工具。将林业理论知识与存储在实例上训练的人工神经网络(ANN)中的经验知识相结合,相对于传统方法可以带来非常显著的结果。在我们的例子中,神经网络是解决林业拟合问题的一个非常强大的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial neural networks applications in problems of fitting in forestry
Neural networks with different architectures and different activation functions represent a powerful tool for solving many approximation problems. Combining the knowledge of a forestry theory with the empirical knowledge stored in an artificial neural networks (ANN) trained on examples, can bring very significant results with respect to traditional approaches. In our example neural networks represent a very powerful tool for solving problems of a fitting in forestry.
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