Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach

Authors

  • Okpor .M. D

Keywords:

supervised-neural-network, fuzzy set, fuzzy logic, algorithm

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.

How to Cite

Okpor .M. D. (2014). Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach. Global Journal of Computer Science and Technology, 14(G3), 1–5. Retrieved from https://computerresearch.org/index.php/computer/article/view/1100

Worker Productivity: A Fuzzy Supervised Neural Training Algorithm Approach

Published

2014-05-15