The study discusses the population census in identified states and its influence in neighborhood states. A fitting function will be generated from the identified data which will be processed using genetic algorithm to find the most probable state which influences population among the identified set. In continuation to that we can consider the House hold data in different states as rows and different types of House Holds like Good, Livable and Dilapidated as columns as input to the GenAlgo function. The problem is initialized with a fitness function and mutation function relevant to the Household problem. The work starts with data frame that is passed back to fitfun and mutfun to enable them to take advantage of any additional data viable for them to perform their proposed functions. The idea here is to have put together a data frame containing the Good number of households and Livable households of the population to identify the best performers of states in development activities. This work tries to map population growth with development activities like House hold data in finding a balance in growth among different states in India.
Addepalli V. N. Krishna
School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru-560074, India.
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