Based on the application of RBF-based neural network in prediction of lumber sales and using historical sales data as training data samples by Radial-basis function neural network algorithm for obtain the predicted value. Matlab simulation results show that compared with the actual value, the prediction error is small. Forecast data can be used as a basis for cutting applications submitted to the higher state forestry sector which helps to establish more scientific logging plans and reduce the log yard inventory, so as to improve the economic benefit.%基于径向基的神经网络算法在木材销售量预测上的应用,利用历史销售量数据作为样本训练数据,通过径向基的神经网络算法得到的预测值.通过Matlab仿真的结果表明预测值与实际销售量值相比较误差很小.预测数据可作为申请采伐的依据上报给上级国家林业部门,有助于林业管理部门制定更科学的采伐计划,有助于减少贮木场库存,从而提高经济效益.
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