IJCATR Volume 3 Issue 3

Adaptive Neural Fuzzy Inference System for Employability Assessment

Rajani Kumari Vivek Kumar Sharma Sandeep Kumar
10.7753/IJCATR0303.1006
keywords : Neural Network, Fuzzy Logic, Employability, Sugeno type inference, Education, Understanding Power, Personal Development

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Employability is potential of a person for gaining and maintains employment. Employability is measure through the education, personal development and understanding power. Employability is not the similar as ahead a graduate job, moderately it implies something almost the capacity of the graduate to function in an employment and be capable to move between jobs, therefore remaining employable through their life. This paper introduced a new adaptive neural fuzzy inference system for assessment of employability with the help of some neuro fuzzy rules. The purpose and scope of this research is to examine the level of employability. The concern research use both fuzzy inference systems and artificial neural network which is known as neuro fuzzy technique for solve the problem of employability assessment. This paper use three employability skills as input and find a crisp value as output which indicates the glassy of employee. It uses twenty seven neuro fuzzy rules, with the help of Sugeno type inference in Mat-lab and finds single value output. The proposed system is named as Adaptive Neural Fuzzy Inference System for Employability Assessment (ANFISEA).
@artical{r332014ijcatr03031006,
Title = "Adaptive Neural Fuzzy Inference System for Employability Assessment",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "3",
Issue ="3",
Pages ="136 - 185",
Year = "2014",
Authors ="Rajani Kumari Vivek Kumar Sharma Sandeep Kumar"}
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