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.
Author(s) Details
Addepalli V. N. Krishna
School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru-560074, India.
View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/180
Author(s) Details
Addepalli V. N. Krishna
School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru-560074, India.
View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/180
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