摘要
文化产业发展质量直接影响到广大人民群众的幸福感和获得感,提升文化产业市场竞争力对促进经济发展,增强国家软实力具有至关重要的意义。本文构建了文化产业竞争力评价指标,同时采用MPA算法对BP神经网络的初始权值和阈值进行优化,获得了用于文化产业竞争力预测的MPA-BP神经网络模型。将MPA-BP预测模型和BP、GA-BP、PSO-BP预测模型进行对比,结果表明MPA-BP预测模型的准确率远高于其他模型,同时模型运行时间和BP预测模型相差不大。本论文的研究对更加高效、准确预测文化产业竞争力,促进文化产业的健康、可持续发展具有一定的参考价值。
The development quality of cultural industry directly affects the people's sense of happiness and acquisition.Improving the market competitiveness of cultural industry is of great significance to promote economic development and enhance national soft power.This paper constructs the evaluation index of cultural industry competitiveness,optimizes the initial weight and threshold of BP neural network by MPA algorithm,and obtains the MPA-BP neural network model for predicting the competitiveness of cultural industry.The MPA-BP prediction model is compared with BP,GA-BP and PSO-BP prediction models.The results show that the accuracy of MPA-BP prediction model is much higher than other models,and the running time of the model is almost the same as that of BP prediction model.The research of this paper has a certain reference value for more efficient and accurate prediction of the competitiveness of cultural industry and promoting the healthy and sustainable development of cultural industry.
作者
时杨
张曼
黄雯
Shi Yang;Zhang Man;Huang Wen(Business College(Management College),Northwest University of Political Science and Law Address,shannxi xi’an,China,710122)
出处
《现代科学仪器》
2022年第5期218-222,250,共6页
Modern Scientific Instruments
关键词
MPA-BP网络
文化产业发展
产业竞争力
预测
MPA-BP network
Cultural industry development
Industrial competitiveness
Forecast
