Paper Info
Title
A Critical Evaluation of Computational Methods of Forecasting Based on Fuzzy Time Series
Abstract
The agricultural production is a process, which being nonlinear in nature, due to various influential parameters like weather, rainfall, diseases, disaster, area of cultivation etc., is not governed by any deterministic process. Fuzzy time series forecasting is one of the approaches for predicting the future values where neither a trend is viewed nor a pattern is followed, for example, in case of sugar, Lahi and rice production. Various forecasting methods have been developed on the basis of fuzzy time series data, but accuracy has been a mercurial factor in these forecasts. In this paper, performance analysis of different fuzzy time series FTS models has been carried out. The analysis is applicable to any available time series data of product. In this paper performance analysis is done on the data of Indian agro products that include sugarcane, Lahi and rice. The suitability of different FTS models have been critically examined over the production data of the three agro products. The paper establishes the applicability of FTS methods also in the agriculture industry.
Year
DOI
Venue
2013
10.4018/jdsst.2013010102
IJDSST
Keywords
DocType
Volume
fuzzy time series forecasting,different fuzzy time series,paper performance analysis,critical evaluation,fts method,fuzzy time series,agricultural production,fts model,available time series data,different fts model,production data,fuzzy time series data,computational methods
Journal
5
Issue
ISSN
Citations 
1
1941-6296
0
PageRank 
References 
Authors
0.34
19
3
Name
Order
Citations
PageRank
Prateek Pandey121.05
Shishir Kumar27817.06
Sandeep Srivastava300.34