CFP last date
20 December 2024
Reseach Article

Crop Selection based on Fuzzy TOPSIS using Entropy Weights

by A. Sahaya Sudha, J. Rachel Inba Jeba
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 124 - Number 14
Year of Publication: 2015
Authors: A. Sahaya Sudha, J. Rachel Inba Jeba
10.5120/ijca2015905782

A. Sahaya Sudha, J. Rachel Inba Jeba . Crop Selection based on Fuzzy TOPSIS using Entropy Weights. International Journal of Computer Applications. 124, 14 ( August 2015), 16-20. DOI=10.5120/ijca2015905782

@article{ 10.5120/ijca2015905782,
author = { A. Sahaya Sudha, J. Rachel Inba Jeba },
title = { Crop Selection based on Fuzzy TOPSIS using Entropy Weights },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 124 },
number = { 14 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume124/number14/22173-2015905782/ },
doi = { 10.5120/ijca2015905782 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:14:44.540513+05:30
%A A. Sahaya Sudha
%A J. Rachel Inba Jeba
%T Crop Selection based on Fuzzy TOPSIS using Entropy Weights
%J International Journal of Computer Applications
%@ 0975-8887
%V 124
%N 14
%P 16-20
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The objective of this paper is to extend the TOPSIS to the fuzzy environment. FUZZY TOPSIS is one of the various models of multiple attributes decision making with triangular fuzzy values that so far diverse models have been introduced. The concepts represented in the decision data wherein the crisp value are inadequate to model in real-life situations. In this paper the rating of each alternatives are described by triangular fuzzy numbers, and the weights of each criterion are found by entropy. According to the concept of TOPSIS, a closeness coefficient is defined to determine the raking by calculating the distance of both the fuzzy positive-ideal solution and fuzzy negative-ideal solution. The proposed methods have been applied for five different crops with various criteria for a better and more accurate outputs.

References
  1. Atanassov.K.T., Intuitionistic fuzzy sets, Fuzzy sets and systems, Vol.20, No.1 (1986) 87-96.
  2. Ali mohammad, Abolfazlmohammadi, Hossain aryaeefar, Introduction a new method to expand TOPSIS decision making model to Fuzzy TOPSIS, The Journal of mathematics and Computer Science Vol.2. No.1 (2011) 150-159.
  3. Chang, Y.H., &Yeh, C.H. (2002), A survey analysis of service quality for domestic airlines, European Journal of Operational Research, 139, 166-177.
  4. Chen, T.Y., &Tsao, C. Y. (2007), The interval-valued fuzzy TOPSIS methods and experimental analysis, Fuzzy Sets and Systems.
  5. Chen-Tung Chen, Extension of the TOPSIS for group decision-making under Fuzzy environment, Elsevier, Fuzzy Sets and Systems 114 (2000) 1-9.
  6. Irajalavi and Hamid Alinejad-Rokny, Comparison of Fuzzy AHP and Fuzzy TOPSIS Methods for plant species selection (Case study: Reclamation Plan of Sungun Copper Mine; Iran), Australian Journal of Basic and Applied Sciences, 5 (12), (2011) 1104-1113.
  7. Hwang.C.L., &Yoon.K, Multiple Attributes Decision Making Methods and Applications, Springer, Berlin Heidelberg, 1981.
  8. MortezaPakdinAmiri, Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods, Elsevier, Expert Systems with Applications 37 (2010) 6218-6224.
  9. SahayaSudha.A, Rachel InbaJeba.J, Selection of Planting of Crops by Rotation Using TOPSIS, Journal of Global Research in Mathematical Archives, Vol.2, No.6, (2014) 15-20.
  10. Thamraiselvi.A and Santhi.R, On Intuitionistic Fuzzy Transportation Problems Using Hexagonal Intuitionistic Fuzzy Numbers, International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.1, January 2015.
  11. Zadeh.L.A., Fuzzy Sets, Inform and control 8 (1965) 338-353.
Index Terms

Computer Science
Information Sciences

Keywords

TOPSIS Fuzzy TOPSIS Triangular Fuzzy Numbers.