A Machine Learning Model for Population Analysis among Different States in India which Influences the Socio, Demographic and Economic Needs of Society
Addepalli VN Krishna1, M. Bala Murugan2
1Dr. Addepalli VN Krishna, Professor, CSE, Faculty of Engineering, CHRIST, Bengalurur, India.
2Dr. M. Bala Murugan, Associate Professor, CSE, Faculty of Engineering, CHRIST, Bengalurur, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 123-126 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1066109119/2019©BEIESP | DOI: 10.35940/ijeat.A1066.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this work Data from 2011 census is taken to identify the state which influences more in Population census among the different states identified. The data is considered from Madhya Pradesh, followed with Utter Pradesh, then to Bihar, Bengal and Orissa. Similarly other case studies are also done for Southern Indian states and North Eastern States. Genetic algorithm will be tried to find the optimal location for the given study. A fitting function is calculated for the population data of 2011 using Lagrange Interpolation technique. This fitting function is given as input to Genetic algorithm to find the optimal state which have maximum influence in the population growth among different states of India as per the Case studies done.
Keywords: The population data of 2011 using Lagrange Interpolation technique.