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A neural network approach for predicting forest fires

机译:神经网络预测森林火灾的方法

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In this paper, we present an application of artificial neural networks to the real-world problem of predicting forest fire. The neural network used for this application is a multilayer perceptron whose architectural parameters, i.e., the number of hidden layers and the number of neurons per layer were heuristically determined. The synaptic weights of this architecture were adjusted using the backpropagation learning algorithm and a large set of real data related to the studied problem. We also present and discuss some preliminary results which illustrate the performance and the usefulness of the proposed approach.
机译:在本文中,我们提出了一种人工神经网络在预测森林火灾的现实问题中的应用。用于此应用的神经网络是多层感知器,其结构参数,即启发式确定的隐藏层数和每层神经元数。该结构的突触权重使用反向传播学习算法和与研究问题相关的大量实际数据进行了调整。我们还提出并讨论了一些初步结果,这些结果说明了所提出方法的性能和实用性。

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