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Reseach Article

A Study of Applications of Fuzzy Logic in Various Domains of Agricultural Sciences

Published on May 2015 by Philomine Roseline T, N. Ganesan, Clarence J M Tauro
An Architectural Framework for Workload Demand Prediction in Scalable Federated Clouds
Foundation of Computer Science USA
ICCTAC2015 - Number 1
May 2015
Authors: Philomine Roseline T, N. Ganesan, Clarence J M Tauro
931db306-7e7b-4a43-b26d-d7c6dfc4e232

Philomine Roseline T, N. Ganesan, Clarence J M Tauro . A Study of Applications of Fuzzy Logic in Various Domains of Agricultural Sciences. An Architectural Framework for Workload Demand Prediction in Scalable Federated Clouds. ICCTAC2015, 1 (May 2015), 15-18.

@article{
author = { Philomine Roseline T, N. Ganesan, Clarence J M Tauro },
title = { A Study of Applications of Fuzzy Logic in Various Domains of Agricultural Sciences },
journal = { An Architectural Framework for Workload Demand Prediction in Scalable Federated Clouds },
issue_date = { May 2015 },
volume = { ICCTAC2015 },
number = { 1 },
month = { May },
year = { 2015 },
issn = 0975-8887,
pages = { 15-18 },
numpages = 4,
url = { /proceedings/icctac2015/number1/20919-2006/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 An Architectural Framework for Workload Demand Prediction in Scalable Federated Clouds
%A Philomine Roseline T
%A N. Ganesan
%A Clarence J M Tauro
%T A Study of Applications of Fuzzy Logic in Various Domains of Agricultural Sciences
%J An Architectural Framework for Workload Demand Prediction in Scalable Federated Clouds
%@ 0975-8887
%V ICCTAC2015
%N 1
%P 15-18
%D 2015
%I International Journal of Computer Applications
Abstract

Fuzzy logic (FL) has emerged as an important branch of Expert system which has proved to provide solution to real life problems that had remained unsolvable otherwise. It has found wide range of applications in diversified areas. In this paper, we study how the methods of fuzzy logic have been effectively used to solve a myriad of problems in the field of agricultural sciences. This paper reviews a few of the applications of fuzzy logic integrated with expert systems which had been applied in the field of agricultural sciences. This study could be considered as a part of the literature survey done for research work in future for developing expert system for a particular crop for a given region in our country. It can serve as the baseline for further work to be carried out in this domain.

References
  1. Jang, R. J. S. , 1993. ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE Transactions on Systems, Man and Cybernetics 23 (3), 665–685.
  2. Philomine Roseline, Clarence J m Tauro and N Ganesan. Article: Design and Development of Fuzzy Expert System for Integrated Disease Management in Finger Millets. International Journal of Computer Applications 56(1):31-36, October 2012.
  3. Dubey, Sonal, R. K. Pandey, and S. S. Gautam. "Literature Review on Fuzzy Expert System in Agriculture. " International Journal of Soft Computing and Engineering (IJSCE) ISSN (2013): 2231-2307.
  4. Yang, C. C. , et al. "Recognition of weeds with image processing and their use with fuzzy logic for precision farming. " Canadian Agricultural Engineering 42. 4 (2000): 195-200.
  5. van der Werf, Hayo MG, and Christophe Zimmer. "An indicator of pesticide environmental impact based on a fuzzy expert system. " Chemosphere 36. 10 (1998): 2225-2249.
  6. MacMillan, R. A. , et al. "A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. " Fuzzy sets and Systems 113. 1 (2000): 81-109.
  7. Marks, L. A. , et al. "Multiple criteria decision making (MCDM) using fuzzy logic: an innovative approach to sustainable agriculture. " Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA-NAFIPS'95. , Third International Symposium on. IEEE, 1995.
  8. Papageorgiou, Elpiniki I. , Athanasios T. Markinos, and T. A. Gemtos. "Fuzzy cognitive map based approach for predicting yield in cotton crop production as a basis for decision support system in precision agriculture application. " Applied Soft Computing 11. 4 (2011): 3643-3657.
  9. Chen, Yun, Shahbaz Khan, and Zahra Paydar. "To retire or expand? A fuzzy GIS-based spatial multi-criteria evaluation framework for irrigated agriculture. " Irrigation and drainage 59. 2 (2010): 174-188.
  10. Prakash, T. N. "Land suitability analysis for agricultural crops: A fuzzy Multicriteria Decision Making Approach. " MS Theses international institute for geo-information science and earth observation enschede, the netherland (2003).
  11. Roussel, Olivier, Alain Cavelier, and Hayo MG van der Werf. "Adaptation and use of a fuzzy expert system to assess the environmental effect of pesticides applied to field crops. " Agriculture, ecosystems & environment 80. 1 (2000): 143-158.
  12. Kolhe, Savita, et al. "A web-based intelligent disease-diagnosis system using a new fuzzy-logic based approach for drawing the inferences in crops. " Computers and Electronics in Agriculture 76. 1 (2011): 16-27.
  13. Hartati, Sri, and Imas SM Sitanggang. "A fuzzy based decision support system for evaluating land suitability and selecting crops. " Journal of Computer Science 6. 4 (2010): 417.
  14. Gottschalk, Klaus, László Nagy, and István Farkas. "Improved climate control for potato stores by fuzzy controllers. " Computers and electronics in agriculture 40. 1 (2003): 127-140.
  15. Brunt, A. A. , and S. Phillips. "'Fuzzy vein', a disease of tomato (Lycopersicon esculentum) in Western Nigeria induced by cowpea mild mottle virus. " Tropical Agriculture 58. 2 (1981): 177-180.
Index Terms

Computer Science
Information Sciences

Keywords

Expert System Fuzzy Logic Soft Computing