{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T16:40:08Z","timestamp":1654101608541},"reference-count":33,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,1,1]]},"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.<\/p>","DOI":"10.4018\/jdsst.2013010102","type":"journal-article","created":{"date-parts":[[2013,6,20]],"date-time":"2013-06-20T16:04:15Z","timestamp":1371744255000},"page":"24-39","source":"Crossref","is-referenced-by-count":8,"title":["A Critical Evaluation of Computational Methods of Forecasting Based on Fuzzy Time Series"],"prefix":"10.4018","volume":"5","author":[{"given":"Prateek","family":"Pandey","sequence":"first","affiliation":[{"name":"Department of Computer Science & Engineering, Jaypee University of Engineering & Technology, Madhya Pradesh, India"}]},{"given":"Shishir","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Jaypee University of Engineering & Technology, Madhya Pradesh, India"}]},{"given":"Sandeep","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Humanities and Social Sciences, Jaypee University of Engineering & Technology, Madhya Pradesh, India"}]}],"member":"2432","reference":[{"key":"jdsst.2013010102-0","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0114(95)00220-0"},{"key":"jdsst.2013010102-1","doi-asserted-by":"publisher","DOI":"10.1080\/019697202753306479"},{"issue":"3","key":"jdsst.2013010102-2","first-page":"234","article-title":"A new method to forecast enrollments using fuzzy time series.","volume":"2","author":"S. M.Chen","year":"2004","journal-title":"International Journal of Applied Science and Engineering"},{"key":"jdsst.2013010102-3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.02.098"},{"key":"jdsst.2013010102-4","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2005.07.004"},{"key":"jdsst.2013010102-5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.12.041"},{"key":"jdsst.2013010102-6","unstructured":"DOFPD. (2011). Retrieved November, 2011 from http:\/\/fcamin.nic.in"},{"key":"jdsst.2013010102-7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.02.052"},{"key":"jdsst.2013010102-8","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-0114(00)00093-2"},{"key":"jdsst.2013010102-9","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-0114(00)00057-9"},{"key":"jdsst.2013010102-10","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2005.857093"},{"key":"jdsst.2013010102-11","unstructured":"ISEC. (2012). Retrieved from http:\/\/www.isecindia.com\/sp.php?p=sugar"},{"key":"jdsst.2013010102-12","unstructured":"ISMA. (2012). Retrieved January, 2012, from http:\/\/www.indiansugar.com"},{"key":"jdsst.2013010102-13","unstructured":"Jayne, T. S., & Rashid, S. (2010). The value of accurate crop production forecasts. African Agricultural Markets Program (AAMP) policy symposium. Lilongwe, Malawi."},{"issue":"1","key":"jdsst.2013010102-14","first-page":"67","article-title":"Modified weighted for enrollment forecasting based on fuzzy time series.","volume":"25","author":"M. H.Lee","year":"2009","journal-title":"MATEMATIKA"},{"key":"jdsst.2013010102-15","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.10.034"},{"key":"jdsst.2013010102-16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2009.01.024"},{"key":"jdsst.2013010102-17","unstructured":"Moller, B., Beer, M., & Reuter, U. (2005). Theoretical basics of fuzzy randomness-application to time series with fuzzy data. In Proceedings of ICOSSAR (pp. 1701\u20131707)."},{"key":"jdsst.2013010102-18","unstructured":"Nabard. (2011). Retrieved December, 2011, from http:\/\/www.nabard.org\/FileUpload\/DataBank\/EvaluationStudy\/Sugarcane_200309.pdf"},{"key":"jdsst.2013010102-19","doi-asserted-by":"publisher","DOI":"10.1080\/01969720591008922"},{"key":"jdsst.2013010102-20","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.02.096"},{"key":"jdsst.2013010102-21","first-page":"375","article-title":"Forecasting enrollment model based on first-order fuzzy time series. World Academy of Science","volume":"1","author":"M.Sah","year":"2005","journal-title":"Engineering and Technology"},{"key":"jdsst.2013010102-22","doi-asserted-by":"publisher","DOI":"10.1080\/019697200124919"},{"key":"jdsst.2013010102-23","doi-asserted-by":"publisher","DOI":"10.1080\/01969720601187354"},{"key":"jdsst.2013010102-24","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2006.07.128"},{"key":"jdsst.2013010102-25","doi-asserted-by":"publisher","DOI":"10.1016\/j.matcom.2008.02.026"},{"issue":"2","key":"jdsst.2013010102-26","first-page":"93","article-title":"A note on fuzzy time series model selection with sample autocorrelation functions. Cybernetics and Systems","volume":"34","author":"Q.Song","year":"2003","journal-title":"International Journal (Toronto, Ont.)"},{"key":"jdsst.2013010102-27","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0114(93)90355-L"},{"key":"jdsst.2013010102-28","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0114(94)90067-1"},{"key":"jdsst.2013010102-29","doi-asserted-by":"publisher","DOI":"10.1016\/j.camwa.2004.07.014"},{"key":"jdsst.2013010102-30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.12.013"},{"key":"jdsst.2013010102-31","doi-asserted-by":"crossref","unstructured":"Yu, H. K. (2005). Weighted fuzzy time series model for TAIEX forecasting. Physica A:Statistical Mechanics and its Applications, 349(3-4), 609\u2013624.","DOI":"10.1016\/j.physa.2004.11.006"},{"key":"jdsst.2013010102-32","doi-asserted-by":"publisher","DOI":"10.1016\/S0019-9958(65)90241-X"}],"container-title":["International Journal of Decision Support System Technology"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=77819","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T16:15:01Z","timestamp":1654100101000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jdsst.2013010102"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2013,1,1]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,1]]}},"URL":"http:\/\/dx.doi.org\/10.4018\/jdsst.2013010102","relation":{},"ISSN":["1941-6296","1941-630X"],"issn-type":[{"value":"1941-6296","type":"print"},{"value":"1941-630X","type":"electronic"}],"subject":["Modeling and Simulation","General Computer Science"],"published":{"date-parts":[[2013,1,1]]}}}