基于ADGA-BP神经网络模型的金融产业发展趋势仿真与预测

Simulation and Forecasting of Financial Industry Development Based on ADGA-BP Model

为了对新常态多目标条件下金融产业发展趋势进行仿真和预测,本文基于经济稳定增长、经济结构优化和创新驱动这三个目标以及金融产业发展速度与质量的相关变量,构建自适应遗传算法优化BP神经网络模型。对2016年三个目标进行敏感性调控,发现金融产业发展速度受经济结构优化目标的影响最大,受经济稳定增长目标的影响其次,受创新驱动目标的影响最小;而金融产业发展质量受三个目标的影响强度相反。并且对2017-2019年金融产业发展趋势进行预测,发现金融产业发展速度将大幅减缓,但是金融资产的质量将逐步提高。

In order to simulate and forecast the development trend of financial industry under new normal multi-objective conditions,this paper constructs an ADGA-BP neural network model based on three objectives: stable economic growth,economic structure optimization and innovation driving as well as the variables underlying the development speed and quality of financial industry. A sensitivity analysis of the three objectives in 2016 shows that the speed of financial development is most affected by economic structure optimization,secondly by economic stability growth,and least by innovation driving. However,the quality of financial industry development is affected by the three objectives to an opposite extent. The prediction of 2017-2019 results show that the speed of financial development will greatly slow down,but the quality will gradually improve.