Department of Management Studies, Bahria University, Islamabad, Pakistan.
EIAS: Data Science and Blockchain Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia.
Biomed Res Int. 2022 Sep 17;2022:5775640. doi: 10.1155/2022/5775640. eCollection 2022.
Researchers in the past discussed the psychological issue like stress, anxiety, depression, phobias on various forms, and cognitive issues (e.g., positive thinking) together with personality traits on traditional research methodologies. These psychological issues vary from one human to other human based on different personality traits. In this paper, we discussed both psychological issues together with personality traits for predicting the best human capital that is mentally healthy and strong. In this research, we replace the traditional methods of research used in the past for judging the mental health of the society, with the latest artificial intelligence techniques to predict these components for attaining the best human capital. In the past, researchers have point out major flaws in predicting psychological issue and addressing a right solution to the human resource working in organizations of the world. In order to give solution to these issues, we used five different psychological issues pertinent to human beings for accurate prediction of human resource personality that effect the overall performance of the employee. In this regard, a sample of 500 data has been collected to train and test on computer through python for selecting the best model that will outperform all the other models. We used supervised AI techniques like support vector machine linear, support vector machine radial basis function, decision tree model, logistic regression, and neural networks. Results proved that psychological issue data from employee of different organizations are better means for predicting the overall performance based on personality traits than using either of them alone. Overall, the novel traditional techniques predicted that sustainable organization is always subject to the control of psychological illness and polishing the personality traits of their human capital.
过去的研究人员在传统的研究方法上，将压力、焦虑、抑郁、恐惧症等各种形式的心理问题，以及积极思考等认知问题与人格特质一起进行了讨论。这些心理问题因不同的人格特质而在人与人之间有所不同。在本文中，我们将心理问题与人格特质一起讨论，以预测最健康和强大的人力资本。在这项研究中，我们用最新的人工智能技术取代了过去用于判断社会心理健康的传统研究方法，来预测这些因素，以获得最佳的人力资本。过去，研究人员已经指出了在预测心理问题和为世界组织中的人力资源提供正确解决方案方面的主要缺陷。为了解决这些问题，我们使用了五种与人类相关的不同心理问题，对影响员工整体表现的人力资源人格进行准确预测。在这方面，我们收集了 500 个数据样本，通过 python 在计算机上进行训练和测试，以选择最佳模型，使其优于所有其他模型。我们使用了监督式 AI 技术，如支持向量机线性、支持向量机径向基函数、决策树模型、逻辑回归和神经网络。结果证明，来自不同组织的员工的心理问题数据是预测基于人格特质的整体表现的更好手段，比单独使用任何一种方法都要好。总的来说，传统的新技术预测，可持续组织总是受到心理疾病的控制，并且需要磨练其人力资本的人格特质。
