A Computational Method for Rice Production Forecasting Based on High-Order Fuzzy Time Series

Abhishekh, Sanjay Kumar
{"title":"A Computational Method for Rice Production Forecasting Based on High-Order Fuzzy Time Series","authors":"Abhishekh, Sanjay Kumar","doi":"10.22457/ijfma.v13n2a5","DOIUrl":null,"url":null,"abstract":"This paper presents a new method of forecasting based on high-order fuzzy logical relationships in the fuzzy time series. The objective of the present study is to develop a computational method for various high orders forecasting to remove the computational drawback of the existing high-order fuzzy time series forecasting methods. The developed method has been presented in form of computational algorithm. This algorithm has been implemented in forecasting of the rice production to examine suitability of these proposed high-order forecasting models on the basis of its average forecasting errors. The forecasting accuracy of the proposed computational method is better than that of existing methods and the forecasted production is much closer to the actual production.","PeriodicalId":385922,"journal":{"name":"International Journal of Fuzzy Mathematical Archive","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Mathematical Archive","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22457/ijfma.v13n2a5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

This paper presents a new method of forecasting based on high-order fuzzy logical relationships in the fuzzy time series. The objective of the present study is to develop a computational method for various high orders forecasting to remove the computational drawback of the existing high-order fuzzy time series forecasting methods. The developed method has been presented in form of computational algorithm. This algorithm has been implemented in forecasting of the rice production to examine suitability of these proposed high-order forecasting models on the basis of its average forecasting errors. The forecasting accuracy of the proposed computational method is better than that of existing methods and the forecasted production is much closer to the actual production.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于高阶模糊时间序列的水稻产量预测计算方法
本文提出了一种基于模糊时间序列中高阶模糊逻辑关系的预测方法。本研究的目的是开发一种各种高阶预测的计算方法,以消除现有高阶模糊时间序列预测方法的计算缺陷。所开发的方法以计算算法的形式给出。将该算法应用于水稻产量的预测,在平均预测误差的基础上检验了所提出的高阶预测模型的适用性。该计算方法的预测精度优于现有方法,预测产量更接近实际产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Neutrosophic Refined Sets in Medical Diagnosis Pareto Optimal Solutions of the Fuzzy Multi-Index, Bi-Criteria Fixed Charge Transportation Problem A New Approach on Multiple Attribute Decision Making with Interval-Valued Knowledge Measure Equitable Regular Total Semi-µ Strong (Weak) Edge Domination in Intuitionistic Fuzzy Graph Common Fixed Point Theorem of two Self Mappings in Fuzzy Normed Spaces
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1