f-psa造句

• In actual application the data of different area have different characteristic , when the hidden layers and input nerve centers are less , we use f - psa combining with bp to predict oil reservoir parameters ; otherwise we use f - gsa combining with bp to predict oil reservoir parameters . in this thesis some emulation results and actual application results are offered
  Gsa ，并将它们与bp网络相结合应用到薄互油藏参数的预测中。对于不同地区，由于地区性差异，当根据实际情况，网络隐层和输入神经元较少时，将fpsa与bp网结合，完成参数预测。
• Based on studying simulated annealing algorithm and powell algorithm , in allusion to simulated annealing algorithm convergence slow , the two fast simulated annealing combination optimization algorithm are offered . one is optimal reservation simulated annealing and powell combination algorithm ( f - psa ) . the other one is optimal reservation simulated annealing and genetic algorithm optimal combination algorithm ( f - gsa ) . and these two optimal combination algorithm are combined with bp neural network to predict oil reservoir parameters
  在深入研究模拟退火算法、 powell算法的理论基础上，针对模拟退火算法收敛速度慢问题，提出了两种快速模拟退火组合优化算法，即最佳保留模拟退火与powell有机结合的fpsa和最佳保留模拟退火与遗传算法有机结合的f