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

Saakshi Gusain; Kunal Kansal; Tribikram Pradhan

doi:10.1007/978-3-319-47952-1_62

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 proceeding › Conference 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 language	English
Title of host publication	Intelligent Systems Technologies and Applications 2016
Editors	Sushmita Mitra, Sabu M. Thampi, El-Sayed El-Alfy, Juan Manuel Corchado Rodriguez
Publisher	Springer Verlag
Pages	771-787
Number of pages	17
Volume	530
ISBN (Print)	9783319479514
DOIs	https://doi.org/10.1007/978-3-319-47952-1_62
Publication status	Published - 2016
Event	International Symposium on Intelligent Systems Technologies and Applications, ISTA 2016 - Jaipur, India Duration: 21-09-2016 → 24-09-2016

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	530
ISSN (Print)	2194-5357

Conference

Conference	International Symposium on Intelligent Systems Technologies and Applications, ISTA 2016
Country/Territory	India
City	Jaipur
Period	21-09-16 → 24-09-16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-319-47952-1_62

Cite this

Gusain, S., Kansal, K., & Pradhan, T. (2016). Genetic algorithm based suggestion approach for state wise crop production in India. In S. Mitra, S. M. Thampi, E.-S. El-Alfy, & J. M. C. Rodriguez (Eds.), Intelligent Systems Technologies and Applications 2016 (Vol. 530, pp. 771-787). (Advances in Intelligent Systems and Computing; Vol. 530). Springer Verlag. https://doi.org/10.1007/978-3-319-47952-1_62

Gusain, Saakshi ; Kansal, Kunal ; Pradhan, Tribikram. / Genetic algorithm based suggestion approach for state wise crop production in India. Intelligent Systems Technologies and Applications 2016. editor / Sushmita Mitra ; Sabu M. Thampi ; El-Sayed El-Alfy ; Juan Manuel Corchado Rodriguez. Vol. 530 Springer Verlag, 2016. pp. 771-787 (Advances in Intelligent Systems and Computing).

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title = "Genetic algorithm based suggestion approach for state wise crop production in India",

abstract = "Agriculture is considered as the backbone of Indian economy. Despite the tremendous increase in industrialization and advancement in technology, a majority of India{\textquoteright}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.",

author = "Saakshi Gusain and Kunal Kansal and Tribikram Pradhan",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; International Symposium on Intelligent Systems Technologies and Applications, ISTA 2016 ; Conference date: 21-09-2016 Through 24-09-2016",

year = "2016",

doi = "10.1007/978-3-319-47952-1\_62",

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isbn = "9783319479514",

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editor = "Sushmita Mitra and Thampi, \{Sabu M.\} and El-Sayed El-Alfy and Rodriguez, \{Juan Manuel Corchado\}",

booktitle = "Intelligent Systems Technologies and Applications 2016",

address = "Germany",

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Gusain, S, Kansal, K & Pradhan, T 2016, Genetic algorithm based suggestion approach for state wise crop production in India. in S Mitra, SM Thampi, E-S El-Alfy & JMC Rodriguez (eds), Intelligent Systems Technologies and Applications 2016. vol. 530, Advances in Intelligent Systems and Computing, vol. 530, Springer Verlag, pp. 771-787, International Symposium on Intelligent Systems Technologies and Applications, ISTA 2016, Jaipur, India, 21-09-16. https://doi.org/10.1007/978-3-319-47952-1_62

Genetic algorithm based suggestion approach for state wise crop production in India. / Gusain, Saakshi; Kansal, Kunal; Pradhan, Tribikram.
Intelligent Systems Technologies and Applications 2016. ed. / Sushmita Mitra; Sabu M. Thampi; El-Sayed El-Alfy; Juan Manuel Corchado Rodriguez. Vol. 530 Springer Verlag, 2016. p. 771-787 (Advances in Intelligent Systems and Computing; Vol. 530).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Genetic algorithm based suggestion approach for state wise crop production in India

AU - Gusain, Saakshi

AU - Kansal, Kunal

AU - Pradhan, Tribikram

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

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DO - 10.1007/978-3-319-47952-1_62

M3 - Conference contribution

AN - SCOPUS:84989857135

SN - 9783319479514

VL - 530

T3 - Advances in Intelligent Systems and Computing

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EP - 787

BT - Intelligent Systems Technologies and Applications 2016

A2 - Mitra, Sushmita

A2 - Thampi, Sabu M.

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PB - Springer Verlag

T2 - International Symposium on Intelligent Systems Technologies and Applications, ISTA 2016

Y2 - 21 September 2016 through 24 September 2016

ER -

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

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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