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针对萤火虫算法(FA)易出现过早收敛,陷入局部最优的缺点,引入小生境技术,提出一种小生境萤火虫优化算法(NFA),通过测试后,利用其搜索BP神经网络的参数.最后建立基于小生境萤火虫优化BP算法的企业经营状况评价模型,并与传统的BP神经网络模型进行对比,仿真结果表明,基于NFA-BP算法的经营状况评价模型的正确识别率高于传统的BP模型,是一种有效的评价模型.
Aiming at the disadvantage that firefly algorithm (FA) tends to converge prematurely and fall into the local optimum, niche technology is introduced to propose a niche firefly optimization algorithm (NFA), which can be used to search parameters of BP neural network after testing BP neural network model based on niche firefly optimization BP algorithm is established and compared with the traditional BP neural network model. The simulation results show that the correct recognition rate of the business condition evaluation model based on NFA-BP algorithm is higher than that of the traditional BP model , Is an effective evaluation model.