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Due to very stochastic nature of wind energy generation from a farm accurate prediction of   wind energy at a particular point of time is a challenging task. To predict the wind energy production from a farm we have divided the prediction time in different time horizon, short term prediction one hour ahead and medium term prediction twelve hour ahead. For short term prediction we have used statistical models and for medium term prediction we have used machine learning method artificial neural network (ANN).


Micro-credit institutions play a pivotal role in meeting the financial needs of both households and micro-enterprises. Various Micro-credit institutions and programs have come up and developed over the years to fill up the gap of providing adequate savings and credit services to the poor, created by the traditional financial institutions. The project investigates whether micro-credit can be considered as a strategy for reducing incidence of poverty in a state. The data collected were analyzed using  logistic regression model.


Using advanced regression techniques and factor analysis with scree plots to design, understand twenty nine  thousand respondent survey data and recommend best practices to Steel industry

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