遗传算法优化前向神经网络结构和权重矢量研究

Research on Genetic Algorithm Optimization of Forward Neural Network Structure and Weight Vector

新兴科技的支持下,复杂研究可以通过优化研究方法进行模拟和拓展。探究人类神经网络结构的过程中,存在诸多困难,新兴模拟算法和仿真计算,让科学家通过人工模拟神经网络系统中的互连神经元了解复杂的神经网络架构。基于此,分析了优化的遗传算法在前向神经网络结构研究中的应用,探究了如何优化权重设计达到最佳研究效果。

With the support of emerging science and technology, complex research can be simulated and expanded by optimizing research methods. In the process of exploring the structure of human neural network, there are many difficulties. Emerging simulation algorithms and simulation calculations enable scientists to understand the complex structure of neural network through artificial simulation of interconnected neurons in neural network system. Based on this, the application of the optimized genetic algorithm in the structure research of feed-forward neural network is analyzed, and how to optimize the weight design to achieve the best research results is explored.