基于TS-BP算法的岗位配置与绩效预测模型构建  

Construction of position allocation and performance prediction model based on TS-BP algorithm

作　　者：余玥 岳晓婧 张戈 张旸 YU Yue;YUE Xiao-jing;ZHANG Ge;ZHANG Yang(Beijing Academy of Science and Technology,Beijing 100089,China)

机构地区：[1]北京市科学技术研究院,北京100089

出　　处：《信息技术》2024年第12期93-100,108,共9页Information Technology

基　　金：北京市思想政治工作研究会-基层课题项目(jckt-2022-22)。

摘　　要：人工智能的发展为企事业单位的人力岗位配置和绩效管理的进一步优化提供了更多更有效的手段。文中基于人工智能技术研究了人力岗位配置模式和绩效预测模型,阐述了人工智能与劳动关系之间的互动机制,并结合趋势预测模型和波动预测模型提出了基于TS-GABPNN预测方法的绩效预测模型,同时对模型的有效性和优越性进行了分析。结果表明,相对于GABPNN预测方法,基于TS-GABPNN的绩效预测模型具有一定的优越性,其对绩效指标预测的误差值在4%以内。With the development of artificial intelligence,more and more effective means have been provided for the further optimization of human resource position allocation and performance management in enterprises.This article is based on artificial intelligence technology,studying the human resource position allocation mode and performance prediction model,elaborating on the interaction mechanism between artificial intelligence and labor relations,and combining trend prediction model and fluctuation prediction model,proposing a performance prediction model based on TS-GABPNN prediction method.The effectiveness and superiority of the model are analyzed.The results indicate that compared to the GABPNN prediction method,the performance prediction model based on TS-GABPNN has certain advantages,with an error value of less than 4%in predicting performance indicators.

关 键 词：人工智能 人力资源 绩效管理 TS-GABPNN 预测模型 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]