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Comparison of Fuzzy Time Series Chen and Cheng to Forecast Indonesia Rice Productivity

Herlinda Nurafwa Sofhya
2022 Eduma Mathematics Education Learning and Teaching  
This research will discuss the comparison of the forecasting results of fuzzy timeseries using chen and cheng models in forecasting rice productivity in Indonesia.  ...  Forecasting method can help the government to reduce uncertainty about the future of rice productivity.  ...  Forecasting time series data using fuzzy models is known as fuzzy time series.  ... 
doi:10.24235/eduma.v11i1.10936 fatcat:6soi6cii3vemtpsna4vw4nsqja

Enhanced Accuracy of High – Order Fuzzy Time Series Forecasting Model Based on Harmony Search Algorithm

Nghiem Van Tinh, Bui Thi Thi
2019 Zenodo  
However, first-order fuzzy time series models have proven to be insufficient for solving these problems.  ...  In recent years, many fuzzy time series models have already been used to solve nonlinear and complexity issues.  ...  Section 3, first gives the details of fuzzy time series forecasting model to forecast rice production and then combines with the HS algorithm to find the effective lengths of intervals in the universe  ... 
doi:10.5281/zenodo.2554014 fatcat:l2wk5bo54fdc3liatzd7ot2ss4

A Higher Order Fuzzy Logic Model with Genetic Algorithm Used to Predict the Rice Production in India

Likewise, the key challenge of the forecasting rice production is to create a realistic model that can able to handle the critical time series data and forecast with minor error.  ...  Specifically, rice production is forecasted for a leading year for overall planning of the crop, utilization of the agricultural resources and the rice production management.  ...  Specifically, rice production is forecasted for a time series forecasting.  ... 
doi:10.35940/ijitee.l3191.1081219 fatcat:gmktby2jqvchhmhqpmfot52yyu

Forecasting Production Values using Fuzzy Logic Interval based Partitioning in Different Intervals

Shubham Aggarwal, Jatin Sokhal, Bindu Garg
2017 International Journal of Advanced Computer Science and Applications  
Fuzzy time series models have been put forward for rice production from many researchers around the globe, but the prediction has not been very accurate.  ...  Fuzzy models are used for prediction in many areas, like enrolments prediction, stock price analysis, weather forecasting, and rice production.  ...  The author would like to thank referees for their valuable comments and constructive suggestions. Their insight and comments led to the better presentation of the ideas expressed in this paper.  ... 
doi:10.14569/ijacsa.2017.080536 fatcat:xkleeaqtcbexrhm4auwekozpta

A computational method based on interval length for fuzzy time series forecasting

Özlem AKAY
2021 NATURENGS MTU Journal of Engineering and Natural Sciences Malatya Turgut Ozal University  
In the literature, there have been a good many different forecasting methods related to forecasting problems of fuzzy time series.  ...  After the intervals are formed, the historical time series data set is fuzzified according to fuzzy time series theory.  ...  Jiang et al. (2017) [16] constructed a novel high-order fuzzy time series (FTS) model to make time series forecasting.  ... 
doi:10.46572/naturengs.882203 fatcat:nzqpkm6cdrdnpg3x52umchjcdq


Nurhayadi Nurhayadi
2022 Media statistika  
The fuzzy Vector Autoregression model obtained was applied to the Farmer's Exchange Rate in Central Java Province. The accuracy of the model is measured based on the Mean Absolute Percentage Error.  ...  The results of model trials on FER Central Java in 2014-2020, show a pretty good forecast, namely forecasting with MAPE around 5%, and not exceeding 10%.  ...  The numerical calculations in this paper have been carried out using the R language computer program, thanks to the developers.  ... 
doi:10.14710/medstat.15.1.94-103 fatcat:sv7nee5lhrh3nlkqcdjclsw7ue

A Soft Computing Model to Predict the Rice Production in India

2019 International Journal of Engineering and Advanced Technology  
The main purpose of this study is to develop a predictive model on Indian rice production.  ...  The vital aspect of this predictive model is the accuracy of the future data prediction on the basis of past time series data.  ...  Other evidence to improve the fuzzy time series prediction arisen from the time variant models by implementing the higher degree procedures of fuzzy time series prediction [6] .  ... 
doi:10.35940/ijeat.f8012.088619 fatcat:kmmbbvdkb5cdhmcw4nvr3wk7pm


Md. Salauddin Khan, Masudul Islam, Md. Rasel Kabir, Lasker Ershad Ali
For this reason, we clarify the stationary and non-stationary series by graphical method. On the basis of that, the stationary model is being set up as the forecasting purpose.  ...  BBS also forecast different sectors such as economics, weather, agriculture etc in different time in this country.  ...  In financial forecasting, Fang combines two methods to develop the fuzzy ARIMA model based upon the works of time-series model and fuzzy regression model.  ... 
doi:10.26782/jmcms.2016.01.00002 fatcat:7kqxxt7qnvehli6inyo2o7cvj4

Forecasting rice production in Jigawa State, Nigeria using fuzzy inference system

Ali Maianguwa Shuaibu, Maryam Nuraini Muhammad, Yusuf Abu-Safyan
2022 Dutse Journal of Peace and Applied Science  
In this work, we used fuzzy inference system to forecast rice production covering the period 2021-2030 in Jigawa state, Nigeria. This is done by designing a fuzzy inference system using MATLAB.  ...  The variables are rainfall, land and rice production. Furthermore, linguistic variables were defined on each input.  ...  Algorithm for Forecasting Rice Production In this work, a fuzzy inference system for production of rice is designed and the implementation is done on MATALB using the following steps: 1.  ... 
doi:10.4314/dujopas.v7i4b.21 fatcat:cjdfk2rdz5fcbb2cmod5jwjnx4

Forecasting Rice Production in West Bengal State in India

Arindam Chaudhuri
2013 International Journal of Agricultural and Environmental Information Systems  
Determination of nature of rice production time series data is difficult, expensive, time consuming and involves tedious tests. In this paper, we use Interval Type n Fuzzy  ...  Forecasting rice production is a challenging problem in agricultural statistics.  ...  conventional Statistical techniques with better performance have paved the road for increased usage of these techniques in areas of time series forecasting.  ... 
doi:10.4018/ijaeis.2013100104 fatcat:4dzfiofxy5fe3harhztjsmqnhy


Pham Đinh Phong
2021 Journal of Computer Science and Cybernetics  
The fuzzy time series (FTS) forecasting models have been being studied intensively over the past few years.  ...  Hieu et al. proposed a linguistic time series by utilizing the hedge algebras quantification to converse the numerical time series data to the linguistic time series.  ...  ACKNOWLEDGMENTS The author thanks the reviewers for their valuable comments and suggestions to improve the paper quality.  ... 
doi:10.15625/1813-9663/37/1/15852 fatcat:xfptqkmgpvbajhexfp57waqzqu

Prediction of Indian Monsoon Rainfall by Interval based Simplified High Order Fuzzy Time Series Model

2020 International Journal of Engineering and Advanced Technology  
In this paper rainfall prediction by fuzzy time series model is proposed in which two difference values of the interval corresponding to the fuzzified forecasted value is proposed.  ...  Rainfall forecasting involves high degree of uncertainty and for such conditions fuzzy time series and other soft computing techniques are best to deal with.  ...  Singh [7] presented a review in which FTS based modeling techniques are discussed. Rana [1] studied on the rice production FTS Forecasting model.  ... 
doi:10.35940/ijeat.d7527.049420 fatcat:4w7zaz77n5gq3hw4ejcfpcmqqi

Fish Production Forecasting in India using Nested Interval Based Fuzzy Time Series Model

2020 International journal of recent technology and engineering  
Fuzzy time series (FTS) is of great importance for such forecasting. But the problem with FTS forecast lies with the accuracy.  ...  The forecasted values shows better result compared to Chen model.  ...  Financial forecasting is another thrilling field for researchers, Bose and Mali [6] [1] studied on the rice production FTS Forecasting model.  ... 
doi:10.35940/ijrte.f9412.038620 fatcat:jodhiefsxvevzmx6y57zzpmcwe

Applications of Machine Learning Techniques in Agricultural Crop Production: A Review Paper

Subhadra Mishra, Debahuti Mishra, Gour Hari Santra
2016 Indian Journal of Science and Technology  
Time series analysis, Markov chain model, k-means clustering, k nearest neighbor, and support vector machine are applied in the domain of agriculture were presented.  ...  Accurate and timely forecasts of crop production are necessary for important policy decisions like import-export, pricing marketing distribution etc. which are issued by the directorate of economics and  ...  Time series forecasting is a model to predict future values based on previously observed values.  ... 
doi:10.17485/ijst/2016/v9i38/95032 fatcat:wssmaerlavhk7eiymp23uzxvge

Fuzzy Time Series based method for Wheat production Forecasting

Sachin Kumar, Narendra Kumar
2012 International Journal of Computer Applications  
We are using the data of previous years and proposing a new method by using the fuzzy time series forecasting technique. General Terms Fuzzy system and Agriculture.  ...  Present study provides some modified techniques for time series based forecasting for the yield of any crop year.  ...  Fuzzy Time Series: in normal time series we use statistical methods and forecast or analyze data according to those methods.  ... 
doi:10.5120/6313-8651 fatcat:nhq6s5ay4bfrldf2hyd5diqsxa
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