Comparative Study on Fuzzy Models for Crop Production Forecasting
نویسندگان
چکیده
منابع مشابه
A Comparative Study of Neural-Network & Fuzzy Time Series Forecasting Techniques – Case Study: Wheat Production Forecasting
Summery Various forecasting methods have been developed on the basis of fuzzy time series data, but accuracy has been matter of concern in these forecasts. As in fuzzy time series methods forecasted values depend to some degree on our interpretation of the output of the forecasting model thus different interpretation may lead to different results, this makes the process quite subjective. An obj...
متن کاملA Comparative Study of Different Fuzzy Time Series Forecasting Techniques – Case Study: Marine Fish Production Forecasting
Various forecasting methods have been developed on the basis of fuzzy time series data, but accuracy has been matter of concern in these forecasts. The historical data of marine fish production of India have been taken to implement the model; as such time series data obtained through sample survey are likely to be imprecise. The study uses the fuzzy sets theory of Zadeh [1] and fuzzy time serie...
متن کاملa study on thermodynamic models for simulation of 1,3 butadiene purification columns
attempts have been made to study the thermodynamic behavior of 1,3 butadiene purification columns with the aim of retrofitting those columns to more energy efficient separation schemes. 1,3 butadiene is purified in two columns in series through being separated from methyl acetylene and 1,2 butadiene in the first and second column respectively. comparisons have been made among different therm...
Comparative Study Among Different Time Series Models for Monthly Rainfall Forecasting in Shiraz Synoptic Station, Iran
In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software. Results showed that the ARMA (1,12) model based on Hannan-Rissanen method was the best model which fitted to the data. Then, to assess the verification and accuracy of the model, the monthly rainfall for 60 months (from March 2011 to Feb...
متن کاملForecasting Industrial Production in Iran: A Comparative Study of Artificial Neural Networks and Adaptive Nero-Fuzzy Inference System
Forecasting industrial production is essential for efficient planning by managers. Although there are many statistical and mathematical methods for prediction, the use of intelligent algorithms with desirable features has made significant progress in recent years. The current study compared the accuracy of the Artificial Neural Networks (ANN) and Adaptive Nero-Fuzzy Inference System (ANFIS) app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematics and Statistics
سال: 2020
ISSN: 2332-2071,2332-2144
DOI: 10.13189/ms.2020.080412