Time Series Forecasting through Clustering - A Case Study
نویسندگان
چکیده
!" # $ % & ' ( ) * '!,+ ! -+ !. / $ 0 1+. 2 3 54 +6 $ ' ) % 3 7 / . * '! 8 9 :; . @ " ) % A B C < ?+?D ) !E $ . 6 . 3 "9GFH I4 J K 4 L B * M R A9*:; A R < L%
منابع مشابه
Forecasting flow discharge through time series analysis using SARIMA model for drought conditions, a case study of Jamishan River
Nowadays, water supply is more limited and providing water is more difficult due to increasing population and demand for water. Thus, due to rainfall shortage and impacts of drought, the need for forecasting monthly and annual rainfall and flow discharge through time series analysis is acutely felt. One of the key assumption in time series is their static condition. However, hydrological time s...
متن کاملCombination of Transformed-means Clustering and Neural Networks for Short-Term Solar Radiation Forecasting
In order to provide an efficient conversion and utilization of solar power, solar radiation datashould be measured continuously and accurately over the long-term period. However, the measurement ofsolar radiation is not available to all countries in the world due to some technical and fiscal limitations. Hence,several studies were proposed in the literature to find mathematical and physical mod...
متن کاملOverview and Comparison of Short-term Interval Models for Financial Time Series Forecasting
In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficien...
متن کاملInterpolating time series based on fuzzy cluster analysis problem
This study proposes the model for interpolating time series to use them to forecast effectively for future. This model is established based on the improved fuzzy clustering analysis problem, which is implemented by the Matlab procedure. The proposed model is illustrated by a data set and tested for many other datasets, especially for 3003 series in M3-Competition data. Comparing to the exist...
متن کاملA NEW APPROACH BASED ON OPTIMIZATION OF RATIO FOR SEASONAL FUZZY TIME SERIES
In recent years, many studies have been done on forecasting fuzzy time series. First-order fuzzy time series forecasting methods with first-order lagged variables and high-order fuzzy time series forecasting methods with consecutive lagged variables constitute the considerable part of these studies. However, these methods are not effective in forecasting fuzzy time series which contain seasonal...
متن کاملForecasting Air Pollution Concentrations in Iran, Using a Hybrid Model
The present study aims at developing a forecasting model to predict the next year’s air pollution concentrations in the atmosphere of Iran. In this regard, it proposes the use of ARIMA, SVR, and TSVR, as well as hybrid ARIMA-SVR and ARIMA-TSVR models, which combined the autoregressive part of the autoregressive integrated moving average (ARIMA) model with the support vector regression technique...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2005