Genetic algorithm optimized artificial neural network - co-optimization

Co-optimization of two response biomass (X), and PHA (P) based on RSM design - modeling and optimization. The second/ independent path takes the ANN approach. The same experimental design was exploited to have ANN-based modeling - ANN structure optimized with GA. The ANN model has been further utilized to co-optimize the responses.基于响应面法（Response Surface Methodology, RSM）设计，针对生物量（X）与聚羟基脂肪酸酯（PHA，P）两种响应变量开展协同优化研究，相关研究涵盖建模与优化流程。第二条独立研究路径采用人工神经网络（Artificial Neural Network, ANN）方法：沿用相同的实验设计构建基于人工神经网络的模型，并通过遗传算法（Genetic Algorithm, GA）优化人工神经网络的结构。后续进一步利用该人工神经网络模型，实现两种响应变量的协同优化。