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Target training with soft computing tools

机译:使用软计算工具进行目标培训

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摘要

The personal capabilities and intentions of employees indicate their performance within their organization. It is important for the organization to capture this kind of tacit knowledge since the workforce are the true experts in perceiving the organization's current reality and evaluating which assets require development - including themselves as knowledge assets. The collective inner voice of the workforce helps the organization's management to steer the company and its assets in a sustainable direction. This article presents how the collective inner voice of the workforce can be captured and how it can be used for the benefit of the organization and its employees. The objective is to support individuals' personal aspirations, as well as to save the money, time and resources that an organization spends on personnel training. The focus of this article is on demonstrating a possible soft-computing method used for competency simulation. The process starts with a linguistic self-evaluation conducted by employees, where individuals' own perception of current and target competence levels is captured. The self-evaluation is conducted with the help of fuzzy logic. Clusters are formed from the result dataset using an unsupervised neural network clustering method: self-organizing maps. A demonstrator tool is then used to perform a "whatif" type of analysis/simulation on the clusters in the results. With the demonstrator tool, employees can roughly test the impact of alternative training scenarios for themselves. For individuals this may open up new directions for self-development, and for organizations this may allow the efficient use of training resources. We tested the approach with a dataset from a real human resource development project among nuclear power plant operators. The case study reveals the potential of soft-computing based collective competency simulation as one part of personnel development projects in the future. Yet the techniques and the demonstrator tool used in this experiment are far from being products that employees could easily use as part of their training project. Possible benefits of the proposed approach are demonstrated in this article.
机译:员工的个人能力和意图表明了他们在组织中的表现。对于组织而言,捕获这种隐性知识非常重要,因为员工是了解组织当前现实并评估哪些资产需要发展的真正专家,包括将自己作为知识资产。员工集体内心的声音可以帮助组织的管理层将公司及其资产导向可持续的方向。本文介绍了如何捕获员工的集体内心声音,以及如何将其用于组织及其员工的利益。目的是支持个人的个人愿望,并节省组织在人员培训上花费的金钱,时间和资源。本文的重点是演示一种用于能力模拟的可能的软计算方法。该过程始于员工进行的语言自我评估,其中记录了个人对当前和目标能力水平的看法。在模糊逻辑的帮助下进行自我评估。使用无监督神经网络聚类方法(自组织图)从结果数据集中形成聚类。然后,使用演示工具对结果中的集群执行“假设”类型的分析/模拟。借助演示工具,员工可以自己大致测试替代培训方案的影响。对于个人而言,这可以为自我发展开辟新的方向,对于组织而言,这可以使培训资源得到有效利用。我们使用来自核电厂运营商的实际人力资源开发项目中的数据集测试了该方法。案例研究揭示了基于软计算的集体能力仿真的潜力,这是将来人员发展项目的一部分。但是,该实验中使用的技术和演示工具远非员工可以轻松将其用作培训项目的一部分的产品。本文演示了该方法的可能好处。

著录项

  • 来源
    《Journal of computational science》 |2011年第3期|p.207-215|共9页
  • 作者单位

    Department of Knowledge Service Engineering, Korea Advanced Institute of Science and Technology, 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea;

    Teotlisuuden Voima Oyj, Olkiluoto, Fl-27160 Eurajoki, Finland;

    Institute of Signal Processing, Tampere University ofTechnology, P.O. Box 553, FIN-33101 Tampere, Finland;

    Ubiquitous Technology Application Research Center, School of Air Transport, Transportation and Logistics, Korea Aerospace University, 412-791 GoYang City, Republic of Korea;

    Department of Industrial Management, Tampere University ofTechnology at Port, Pohjoisranta 11 A, PL 300,28101 Pori, Finland;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    work role competencies som self-organizing map self-evaluation simu som;

    机译:工作角色能力自我组织图自我评估simu som;

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