A comparison between the fuzzy time series and genetic algorithm in the prediction of engineering manpower

The smooth working of industry depends on the availability of proper engineering manpower. If proper qualified and experienced technical personnels are not available, the industry cannot run in the most efficient way. Here an effort is made to assess the engineering manpower requirement (personnel belonging to mechanical engineering) in certain industry group (steel Manufacturing) in the state of West Bengal in India for the next five years. The models of fuzzy time series and genetic algorithm are tested and based on the error analysis, model with minimum average error value is selected and used for the assessment of engineering manpower requirement. Certain statistical functions, ie, least square technique based on linear, exponential, curvilinear equations and the tables of orthogonal polynomial are applied on the estimated data value calculated earlier for the prediction of futuristic engineering manpower. The particular statistical model is chosen based on the average error of estimated data generated using statistical models with the actual data over span of years. The said particular statistical model based on the estimated data using models of fuzzy time series or genetic algorithm can be used for the generation of futuristic forecasted engineering manpower.