Genetic algorithm based suggestion approach for state wise crop production in India

Saakshi Gusain, Kunal Kansal, Tribikram Pradhan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Agriculture is considered as the backbone of Indian economy. Despite the tremendous increase in industrialization and advancement in technology, a majority of India’s population is dependent on agriculture. Agriculture in India is not uniform throughout. In this paper, rule based classification has been applied to classify the states based on the amount of rainfall. The accuracy of Classification results is validated using Random Forest algorithm. Also we have found the major crops that can be grown in a state using a proposed algorithm by analyzing the soil, temperature and rainfall data. Due to time constraint and non-optimal usage of land resources, cultivation of all the suggested crops is not possible. Therefore, Genetic Algorithm is applied to give the best possible suggestion for crop cultivation across various states in India. So our proposed method will help to maximize the overall agriculture production in India.

Original languageEnglish
Title of host publicationIntelligent Systems Technologies and Applications 2016
PublisherSpringer Verlag
Pages771-787
Number of pages17
Volume530
ISBN (Print)9783319479514
DOIs
Publication statusPublished - 2016
EventInternational Symposium on Intelligent Systems Technologies and Applications, ISTA 2016 - Jaipur, India
Duration: 21-09-201624-09-2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume530
ISSN (Print)2194-5357

Conference

ConferenceInternational Symposium on Intelligent Systems Technologies and Applications, ISTA 2016
Country/TerritoryIndia
CityJaipur
Period21-09-1624-09-16

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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