[PDF] Top 20 A Computational Method for Rice Production Forecasting Based on High-Order Fuzzy Time Series

... of fuzzy time series forecasting and Markov ...a fuzzy time series prediction method based on consecutive ...a time invariant relation matrix for ... See full document

... Crop production is considered as one of the real world complex problem due to its non-deterministic nature and uncertain ...Particularly, forecasting of rice production for a lead year is ... See full document

... the computational method of forecasting based on fuzzy time series have been developed to provide improved forecasting results to deal with the situation containing ... See full document

... on fuzzy time series forecasting (TSF) and several studies indicating superior performance, an appropriate computationally efficient method have not been developed to predict various ... See full document

... as forecasting stock market, forecasting enrolments, temperature prediction, population growth prediction, ...used fuzzy time series to handle prediction ...When forecasting ... See full document

... IMKB time series as the test set, the fuzzy set numbers that give the best results were determined as 9 in Song and Chissom method [21], 37 (the interval length is 300) in Chen 's ... See full document

... The fuzzy time series (FTS) is capable in dealing deal with historical data in the form of linguistic ...for time series. Initially, the fuzzy set theory was introduced by [5] ... See full document

... for fuzzy forecasting [1]-[2], [6], [7]either to find a better forecasting result or to-do faster ...of fuzzy time series was proposed by Song and ...existing fuzzy ... See full document

... High order fuzzy time series forecasting methods are more suitable than first order fuzzy time series forecasting methods in dealing with ... See full document

... modified method to predict total number of annual car road accidents based on the m- factors high-order fuzzy time ...This method provides a general framework for ... See full document

... Abstract Fuzzy time series forecasting models are used to overcome traditional time series methods when the historical data of traditional time series approaches ... See full document

... existing fuzzy forecasting models partition historical training time series into fuzzy time series and build fuzzy-trend logical relationship groups to generate ... See full document

... Abstract—Most fuzzy forecasting methods are based on modelling fuzzy logical relationships according to the past ...hybrid forecasting model based on two computational ... See full document

... (one-hour) forecasting Group I-II 88 ...(one-hour) forecasting Group III-IV 88 ...(six-hour) forecasting Group I-II 89 ...(six-hour) forecasting Group III-IV 89 ... See full document

... income of consumers, he studied from the point of con- sumer’s structure and consumption characteristics; Peter M. L., John S. A., William H. D. [3] and Mao [1] also car- ried out similar studies. Bai Y, Liang Y. L. and ... See full document

... proposed method, the forecasting is also used the weighted method and combined with difference actual data and midpoint ...The Forecasting rule on fuzzy time series as ... See full document

... A fuzzy time series Markov chain model with an application to forecast the exchange rate between the Taiwan and US dollar, International Journal of Innovative Computing Information and Control, 8, ... See full document

... better forecasting accuracy rate than ...average based length as a way to solve the ...a method of partitioning the universe of ...of fuzzy time series that are linguistic ... See full document

... same time. But the prediction accuracy of prediction model of fuzzy time series forecasting models of the set SDR is not all higher, some of the forecasting model is standard, ... See full document

... Here we give a forecasting method based on F-transforms for seasonal time series analysis. 87[r] ... See full document