面向员工发展与保留的人才招聘与管理的神经网络模型

P. N. Mwaro, Kennedy Ogada, W. Cheruiyot
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引用次数: 1

摘要

人才管理是确定空缺职位,招聘合适的人,发展此人的技能和专业知识,使其更适合该职位,并留住他以实现机构的长期业务目标的过程。本研究的目的是开发一个用于人力资源部门人才招聘和管理的机器学习模型。因此,本研究提出了一个人力资源集成神经网络模型,用于人才招聘和管理,以促进员工的发展和保留。该模型的预测准确率达到95.313%,表明机器学习模型可以连续应用于人力资源部门的人才招聘。本研究对神经网络及其应用的文献综述进行了探讨,为本研究提供了基础。
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Neural Network Model for Talent Recruitment and Management for Employee Development and Retention
Talent management is the process of identifying the vacant position, recruiting the suitable person, developing the skills and expertise of the person to make the person more suitable for the position and retaining him to achieve long term business objectives of the institution. The purpose of this research was to develop a machine learning model for talent recruitment and management for use in human resource department. The research therefore proposes a human resource Ensemble neural network model for use in talent recruitment and management for employee development and retention. The model developed attained a predictive accuracy of 95.313% and this showed that machine learning models can be used successively for talent recruitment in human resource department. The study explores literature review on neural network and how it has been used which gives the basis of this study.
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