基于BP神经网络的干热风灾害预测

Dry-hot Wind Hazard Prediction Based on the BP Neural Network

干热风是我国新疆,西北等地农业气象灾害之一,其形成因素呈现复杂的非线性关系.利用传统方法很难建立起一个精确完善的预测模型.人工神经网络具有强大的非线性映射能力,尤其是BP神经网络在预测领域中被广泛应用.本文利用BP神经网络对干热风灾害进行了预测.结果表明,基于BP神经网络的干热风预测模型误差小,能达到满意的效果.

Dry hot wind is one of agricultural meteorological disasters in Xinjiang, Northwest and other places, whose caused factors showed the complex nonlinear relationship. Using traditional methods is difficult to establish a accurate comprehensive prediction model. Artificial neural network has a strong nonlinear mapping ability, especially BP neural network is widely used in the field of prediction. In this paper, BP neural network was used to predict the dry hot wind disasters. The results showed that the hot wind prediction model based on BP neural network has small error and can achieve satisfactory results.