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A Neural Network Based Model for Project Risk and Talent Management

机译:基于神经网络的项目风险与人才管理模型

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Objective of this research was to examine the effectiveness of using neural and fuzzy systems in the areas such as job recruitment, prediction of project success/failures and decision making process of employee performance appraisals related to any company/industry. Since these activities are common in many areas, the domain of the research was confined to the software industry. Through a thorough survey, most relevant parameters (together with their level of relevance) that are used in evaluating the suitability of candidates in recruitment etc. for various designations were gathered and fuzzy logic, neural network based approach was used for training and testing. Performance appraisals were also implemented using a neural network which was able to pinpoint the employee's appraisal to a great deal of accuracy. Further, the prediction of project success and failure was also implemented similarly. Since many linguistic terms are used in these activities, a fuzzy input/output interface was accommodated to the system. The evaluation of the proposed system with the support from the industry experts shows a very high level of accuracy.
机译:这项研究的目的是检验在诸如职位招聘,项目成功/失败的预测以及与任何公司/行业相关的员工绩效评估的决策过程等领域中使用神经系统和模糊系统的有效性。由于这些活动在许多领域都很普遍,因此研究范围仅限于软件行业。通过全面的调查,收集了用于评估候选人对各种指定的适应性等方面的最相关参数(及其相关程度),并使用了模糊逻辑,基于神经网络的方法进行培训和测试。绩效评估还使用神经网络进行,该神经网络能够精确地确定员工的评估。此外,对项目成败的预测也以类似的方式实现。由于在这些活动中使用了许多语言术语,因此将模糊的输入/输出接口容纳到系统中。在行业专家的支持下,对建议系统的评估显示出很高的准确性。

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