A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Slope deformation and soft soil foundation settlement prediction method based on GA-BP neural network
The invention discloses a slope deformation and soft soil foundation settlement prediction method based on a GABP neural network, and the method comprises the steps: carrying out the optimization design of the structure, initial connection weight, initial threshold value, learning rate and momentum factor of the neural network through employing a genetic algorithm, and positioning a better searchspace in a solution space; and then optimizing the connection weight and the threshold of the network again in the small solution spaces by using a BP algorithm, and searching an optimal solution, sothat the optimized BP neural network can better predict the output of the function. According to the method, the BP neural network method and the genetic algorithm are combined, and the advantages ofthe two methods are fully utilized, so that the improved method not only has strong learning ability and robustness of the BP neural network, but also has global optimization ability of the genetic algorithm, and has the advantages of high prediction precision, high network convergence speed and the like; and a good effect is achieved on slope deformation and soft soil foundation settlement prediction.
本发明公开了一种基于GA‑BP神经网络的边坡变形及软土地基沉降预测方法，首先用遗传算法对神经网络的结构、初始连接权、初始阈值以及学习率和动量因子进行优化设计，在解空间中定位出较好的搜索空间，然后用BP算法在这些小的解空间中对网络的连接权和阈值再次寻优，搜索出最优解，使优化后的BP神经网络能够更好地预测函数的输出。本申请将BP神经网络法和遗传算法相结合，充分利用两种方法的优点，使改进后的方法既有BP神经网络强大的学习能力和鲁棒性，又有遗传算法的全局寻优能力，使其具有预测精度高、网络收敛速度快等优点，对边坡变形及软土地基沉降预测有较好效果。
Slope deformation and soft soil foundation settlement prediction method based on GA-BP neural network
The invention discloses a slope deformation and soft soil foundation settlement prediction method based on a GABP neural network, and the method comprises the steps: carrying out the optimization design of the structure, initial connection weight, initial threshold value, learning rate and momentum factor of the neural network through employing a genetic algorithm, and positioning a better searchspace in a solution space; and then optimizing the connection weight and the threshold of the network again in the small solution spaces by using a BP algorithm, and searching an optimal solution, sothat the optimized BP neural network can better predict the output of the function. According to the method, the BP neural network method and the genetic algorithm are combined, and the advantages ofthe two methods are fully utilized, so that the improved method not only has strong learning ability and robustness of the BP neural network, but also has global optimization ability of the genetic algorithm, and has the advantages of high prediction precision, high network convergence speed and the like; and a good effect is achieved on slope deformation and soft soil foundation settlement prediction.
本发明公开了一种基于GA‑BP神经网络的边坡变形及软土地基沉降预测方法，首先用遗传算法对神经网络的结构、初始连接权、初始阈值以及学习率和动量因子进行优化设计，在解空间中定位出较好的搜索空间，然后用BP算法在这些小的解空间中对网络的连接权和阈值再次寻优，搜索出最优解，使优化后的BP神经网络能够更好地预测函数的输出。本申请将BP神经网络法和遗传算法相结合，充分利用两种方法的优点，使改进后的方法既有BP神经网络强大的学习能力和鲁棒性，又有遗传算法的全局寻优能力，使其具有预测精度高、网络收敛速度快等优点，对边坡变形及软土地基沉降预测有较好效果。
Slope deformation and soft soil foundation settlement prediction method based on GA-BP neural network
一种基于GA-BP神经网络的边坡变形及软土地基沉降预测方法
LIU JIE (author) / TANG XIYA (author) / YANG QINGGUANG (author) / WU MENGTAO (author) / LUO XIN (author)
2020-12-18
Patent
Electronic Resource
Chinese
Research on Prediction Method of Soft Soil Foundation Settlement
| British Library Conference Proceedings | 2011
Soft soil foundation settlement prediction system for highway construction
| European Patent Office | 2024
The Application of BP Neural Network in Settlement Prediction of Highway Soft Foundation
| British Library Conference Proceedings | 2011