Results 1 to 10 of about 105,549 (303)

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO) [PDF]

Journal of Physics: Conference Series, 2018
The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this
Ahmar, Ansari Saleh, Guritno, Suryo, Abdurakhman, Rahman, Abdul, Awi, Alimuddin, Minggi, Ilham, Tiro, M. Arif, Aidid, M. Kasim, Annas, Suwardi, Sutiksno, Dian Utami, Dewi, S. Ahmar, Kurniawan, H. Ahmar, Ahmar, A. Abqary, Zaki, Ahmad, Abdullah, Dahlan, Rahim, Robbi, Nurdiyanto, Heri, Hidayat, Rahmat, Napitupulu, Darmawan, Simarmata, Janner, Kurniasih, Nuning, Abdillah, Leon Andretti, Pranolo, Andri, Haviluddin, Albra, Wahyudin, Arifin, A. Nurani M   +26 more
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Enhancing drought prediction precision with EEMD-ARIMA modeling based on standardized precipitation index [PDF]

Water Science and Technology
This study introduces ensemble empirical mode decomposition (EEMD) coupled with the autoregressive integrated moving average (ARIMA) model for drought prediction. In the realm of drought forecasting, we assess the EEMD-ARIMA model against the traditional
Reza Rezaiy, Ani Shabri
doaj   +2 more sources

Peramalan Harga Emas Saat Pandemi Covid-19 Menggunakan Model Hybrid Autoregressive Integrated Moving Average - Support Vector Regression

Jambura Journal of Mathematics, 2021
ABSTRAK Investasi emas merupakan salah satu investasi yang menjadi favorit dimasa pandemi Covid 19 seperti sekarang ini. Hal ini dikarenakan harga emas yang nilainya relatif fluktuatif tetapi menunjukkan tren peningkatan.
Drajat Indra Purnama
doaj   +1 more source

Prediction of COVID-19 Data Using an ARIMA-LSTM Hybrid Forecast Model

Mathematics, 2022
The purpose of this study is to study the spread of COVID-19, establish a predictive model, and provide guidance for its prevention and control. Considering the high complexity of epidemic data, we adopted an ARIMA-LSTM combined model to describe and ...
Yongchao Jin, Renfang Wang, Xiaodie Zhuang, Kenan Wang, Honglian Wang, Chenxi Wang, Xiyin Wang   +6 more
doaj   +1 more source

Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing [PDF]

, 2021
Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in ...
A. Rahman, Nur H., Hassan, Siti F., Kamisan, Nur A., Lee, Muhammad H., Nor, Maria E., Norrulashikin, Siti M.   +5 more
core   +1 more source

PENERAPAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) UNTUK PREDIKSI BILANGAN SUNSPOT

Barekeng, 2021
Peristiwa magnetik pada matahari ditandai dengan salah satu tanda yaitu munculnya sunspot atau bintik matahari. Sunspot terletak di fotosfer matahari yang memiliki warna lebih gelap dari pancaran sekitarnya.
Felia Dria Yuliawanti, Dian C. Rini Novitasari, Nanang Widodo, Abdulloh Hamid, Wika Dianita Utami   +4 more
doaj   +1 more source

Research on gas concentration prediction driven by ARIMA-SVM combined model

Gong-kuang zidonghua, 2022
The single gas prediction model has weak capability in mining all characteristics of the mine gas concentration time sequence. In order to solve the problem, a combined prediction model based on autoregressive intergrated moving average (ARIMA) model and
FAN Jingdao, HUANG Yuxin, YAN Zhenguo, LI Chuan, WANG Chunlin, HE Yanpeng   +5 more
doaj   +1 more source

Drought forecasting using W-ARIMA model with standardized precipitation index

Journal of Water and Climate Change, 2023
Climate change and water supply shortages are paramount global concerns. Drought, a complex and often underestimated phenomenon, profoundly affects various aspects of human life. Thus, early drought forecasting is crucial for strategic planning and water
Reza Rezaiy, Ani Shabri
doaj   +1 more source

Application of ARIMA-RTS optimal smoothing algorithm in gas well production prediction

Petroleum, 2022
Gas field production forecast is an important basis for decision-making in the gas industry. How to accurately predict the dynamic production during gas field development is an important content of reservoir engineering research.
Yonggang Duan, Huan Wang, Mingqiang Wei, Linjiang Tan, Tao Yue   +4 more
doaj   +1 more source

Prediction Intervals for ARIMA Models [PDF]

Journal of Business & Economic Statistics, 2001
The problem of constructing prediction intervals for linear time series (ARIMA) models is examined. The aim is to find prediction intervals which incorporate an allowance for sampling error associated with parameter estimates. The effect of constraints on parameters arising from stationarity and invertibility conditions is also incorporated.
Snyder, Ralph D., Ord, J. K., Koehler, A. B.   +2 more
openaire   +1 more source