Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach

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O8M6P

Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach

Okpor .M. D
Okpor .M. D
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Abstract

Productivity refers to the physical relation between the quality produced (output) and the quantity of resource used in the course of production (input). Productivity is a relative term indicating the ratio between total output and the total inputs used therein on the other hand production is an absolute concept, which refers to the volume of output. Fuzzy Supervised Neural Network Training Algorithm has been designed and implemented with Matrix Laboratory (MATLAB) and Hypertext Preprocessor as the simulation language. This paper demonstrates the practical application of soft computing algorithm techniques in various well-meaning organizations.

Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach

Productivity refers to the physical relation between the quality produced (output) and the quantity of resource used in the course of production (input). Productivity is a relative term indicating the ratio between total output and the total inputs used therein on the other hand production is an absolute concept, which refers to the volume of output. Fuzzy Supervised Neural Network Training Algorithm has been designed and implemented with Matrix Laboratory (MATLAB) and Hypertext Preprocessor as the simulation language. This paper demonstrates the practical application of soft computing algorithm techniques in various well-meaning organizations.

Okpor .M. D
Okpor .M. D

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Okpor .M. D. 2014. “. Global Journal of Computer Science and Technology – G: Interdisciplinary GJCST-G Volume 14 (GJCST Volume 14 Issue G3): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach

Okpor .M. D
Okpor .M. D

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