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基于GA-BP神经网络的高校毕业生就业心理问题成因的预测

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针对传统BP算法的神经网络易陷入局部极小,收敛慢的缺点,提出遗传算法GA优化的BP神经网络对影响高校毕业生就业心理问题的各项因素进行分析的模型.该模型可以预测高校毕业生的就业心理存在哪些不足.对因素量化采用了模糊数学中的综合评判法和专家打分的方法.仿真结果表明:该系统模型有效地避免BP神经网络陷入局部最优,具有较高的准确性.预测值与实际值的误差低于4%,可以将此模型应用于对高校毕业生就业心理问题成因的预测.
Prediction of the Causes of Employment Psychological Problems of Higher Vocational Graduates Based on GA-BP Neural Network
Aiming at the shortcomings of traditional BP neural network,which is easy to fall into local minima and slow convergence,this paper puts forward a model of combining genetic algorithm GA and BP algorithm to analyze various factors affecting the employment psychological problems of higher vocational graduates.This model can predict what shortcomings exist in the employment psychology of higher vocational graduates.The comprehensive evaluation method and expert scoring method in fuzzy mathematics are used to quantify the factors.The simulation results show that the system model can ef-fectively avoid the BP neural network from falling into local optimum and has high accuracy.The error between the predicted value and the actual value is less than 4%,so this model can be applied to predict the causes of employment psychological problems of higher vocational graduates.

genetic algorithmBP neural networkpsychological problems in employmentpre-diction

董秀英、李泽军、沐娟、张佑春

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安徽工商职业学院智能制造与汽车学院,安徽 合肥 231131

安徽交通职业技术学院城市轨道交通与信息工程系,安徽 合肥 230051

遗传算法 BP神经网络 就业心理问题 预测

2024

佳木斯大学学报(自然科学版)
佳木斯大学

佳木斯大学学报(自然科学版)

影响因子:0.159
ISSN:1008-1402
年,卷(期):2024.42(11)