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Comparative Analysis of Neuro-Fuzzy Model For Human Resources
[Full Text]
AUTHOR(S)
Sapna Singh, Himanshu Kumar Shukla, Aditya Pratap Singh, Rohit Srivastava, * Mohit Gangwar
KEYWORDS
Neuro-Fuzzy, Human Resources, Neural Network, Management and Fuzzy Model.
ABSTRACT
Ranking techniques and applicant choice for employment roles within Human Resources include very high levels of uncertainty. This's because of the necessity to permit the different tastes as well as views of the various occupation domain specialists in the decision making process. Hence, there's a need to create a unit which is going to enable Human Resource departments to ascertain the most crucial needs criteria for a certain work, based on the personal preferences of various professionals, while making certain the expert's choices are impartial and properly weighted based on their expertise and knowledge. This can allow a far more effective method to list that is brief submitted candidate resume from a lot of candidates providing a fair and consistent resume ranking policy that is usually legally justified. This particular paper provides a Neuro Fuzzy style based method for identifying the primary key ability attributes determining each expert's preferences and ranking choices, while managing the concerns as well as inconsistencies in team choices of a panel of professionals. The presented item classifies the processes of needs specification as well as applicant's ranking. Tests are done to the taken service market industry in which the proposed model is proven to create ranking choices which were fairly extremely consistent with those of the man professionals.
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