中文摘要：

遗传算法GA与人工神经网络ANN相结合的GA_ANN预测模型,在解决大规模问题时,训练模型产生的巨大计算量会导致相当耗时。利用gprof工具剖析出GA_ANN模型的瓶颈所在,并基于OpenMP多线程技术设计出一种并行方案。实验结果表明随着种群规模、繁殖代数以及ANN训练次数的增加,粗粒度的策略结合一定数量的线程能够获得理想的加速比。

英文摘要：

In solving large scale problems,the GA_ANN model which combined the genetic algorithm and artificial neural network would be very time-consuming on the training stage.The bottleneck of GA_ANN model is analyzed by using gprof,and a parallel scheme is designed based on OpenMP multi-threading technology.The experiment results indicate that coarse-grained threading parallelization strategy can get an ideal speedup as the increasing of the population size,number of breeding generation and ANN training.