Parametric sensitivity in decision making process

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
P. Moos, M. Novák, Z. Votruba
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引用次数: 2

Abstract

This paper introduces a possibility of application of parametric sensitivity appearing in processes of decision making in systems represented by the general production functions of the Tinbergen type, depending on information content, information flow and qualification of human resources. The so-called parametric sensitivity considering the information content I as an ordering parameter, dependent on the information flow φ, applied on production function. The theory of production function describes the relation between physical outputs of a production process and physical inputs, i.e. factors of production. Finally, the influence of knowledge in information content I, leading to correct decision, is demonstrated through the parametric sensitivity concept. For this invention, J. Tinbergen and R. Frisch achieved in 1969 the “Nobel price of the Swedish National Bank”. Besides, the production functions theory surprisingly represents also a tool for finding the reasons of living bodies behavior.
决策过程中的参数敏感性
本文介绍了参数敏感性在Tinbergen型一般生产函数表示的系统决策过程中应用的可能性,这取决于信息内容、信息流和人力资源的资格。将信息量I作为排序参数,依赖于信息流φ的参数敏感性应用于生产函数。生产函数理论描述了生产过程的实物产出与实物投入(即生产要素)之间的关系。最后,通过参数敏感性概念论证了信息内容I中知识对正确决策的影响。由于这一发明,J. Tinbergen和R. Frisch在1969年获得了“瑞典国家银行的诺贝尔奖”。此外,令人惊讶的是,生产函数理论也代表了寻找生物行为原因的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neural Network World
Neural Network World 工程技术-计算机:人工智能
CiteScore
1.80
自引率
0.00%
发文量
0
审稿时长
12 months
期刊介绍: Neural Network World is a bimonthly journal providing the latest developments in the field of informatics with attention mainly devoted to the problems of: brain science, theory and applications of neural networks (both artificial and natural), fuzzy-neural systems, methods and applications of evolutionary algorithms, methods of parallel and mass-parallel computing, problems of soft-computing, methods of artificial intelligence.
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