TY -的A2 -艾哈迈德,赛义德·哈桑AU - Yu,川东AU - Du,南PY - 2021 DA - 2021/07/24 TI -分析景观生态规划基于高阶多小波神经网络算法SP - 9420532六世- 2021 AB -风景园林具有自然和社会属性,这是人们保护自然环境的体现。自工业革命以来,现代工业发展迅速。它增加了人们的生活水平和消费大量的自然资源如森林和能量。生态环境已被严重损坏,景观园林的影响。因此,找到一个方法来评估具有重要意义的景观生态学和景观生态规划。本文提出了一种新的高阶小波神经网络算法将小波分析与人工神经网络相结合的产物。景观生态评价的模型基于高阶小波神经网络算法评估景观生态学和景观的生态规划提供参考数据。结果表明,小波神经网络的训练时间达到目标精度的少3600倍比BP神经网络。算法的MSE和梅是0.0639和0.1501,分别。模型的平均误差的综合评价指数景观生态学是0.005。 The accuracy of the model to evaluate the sustainability of landscape land resources is 98.67%. The above results show that the model based on the wavelet neural network can effectively and accurately complete the evaluation of landscape ecology and then provide a decision-making basis for landscape ecological planning, which is of high practicability. SN - 1687-5265 UR - https://doi.org/10.1155/2021/9420532 DO - 10.1155/2021/9420532 JF - Computational Intelligence and Neuroscience PB - Hindawi KW - ER -