基于GA-BP神经网络的环境质量评估方法

Environmental Quality Assessment with GA-BP Neural Network

应用神经网络技术进行环境质量评估,为了提高评估的准确度和科学性,涉及多目标的复杂系统,因此对环境保护和正确决策制定具有重要意义。利用一种基于遗传算法优化BP神经网络进行环境质量评估的新方法。利用遗传算法优化BP神经网络初始权值,充分发挥GA全局寻优的能力和BP算法局部细致搜索优势。并通过MATLAB工具进行仿真模拟计算。结果表明,基于GA-BP算法的神经网络系统对环境质量评估有着良好的性能,与标准BP网络相比,收敛速度快,具有更好的全局收敛性,并提高了评估准确率对保护环境提供依据。

High-quality environmental assessments with neural network contribute to informed decision making. In this study,BP neural network improved by genetic algorithm is applied to the problem of environmental assessment to make full use of global optimization of GA and local accurate searching of BP.Matlab software and its neural network toolbox are used to simulate and compute.The experiment results show that compared with the conventional BP algorithm,the GA - BP learning algorithm has rapid convergence,better global convergence ability and better prediction accuracy.