A Practical Real‐Time Observer‐Based Radiation Prediction Algorithm for Solar Plants
Energy Science &Engineering, EarlyView.A novel radiation prediction method is proposed. The model's existence is verified by applying real data to an offline identifier. An adaptive state/parameter estimator is developed to identify the model. The identification process occurs in real‐time, independent of specific situations. The method offers universal radiation prediction.
S. Sepehr Tabatabaei +2 more
wiley +1 more source
Studi Peramalan Beban Rata – Rata Jangka Pendek Menggunakan Metoda Autoregressive Integrated Moving Average (Arima [PDF]
, 2017 Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State Electricity Company (PLN) as a provider of energy must be able to predict daily electricity needs. Short-term forecasting is the prediction of electricity
Jurnal, R. T. (Redaksi)
core
Neural Network Models for Solar Irradiance Forecasting in Polluted Areas: A Comparative Study
Energy Science &Engineering, EarlyView.Pollution‐aware hybrid ensemble model is proposed to forecast solar irradiance across eight diverse cities. The model integrates MLP, RNN, and NARX to handle varying atmospheric pollution levels. The model outperforms state‐of‐the‐art methods with enhanced accuracy and interpretability on standard solar irradiance data set.
Mujtaba Ali +6 more
wiley +1 more source
Prediksi Jumlah Kasus COVID-19 menggunakan Metode Autoregressive Integrated Moving Average (ARIMA) (Studi Kasus Kabupaten Sidoarjo) [PDF]
, 2021 Lailatul Ainiyah, Muflihah Bansori
openalex +1 more source
Energy Science &Engineering, EarlyView.The wind energy potential of Khaf was evaluated for 2025 using 15 years of wind data combined with advanced forecasting models, SARIMAX and Prophet. This integrated framework enables precise estimation of wind power density and optimal turbine selection, paving the way for the efficient and sustainable development of wind farms in the region.
Mohammad Amin Valizadeh +3 more
wiley +1 more source
On the Estimation and Performance of One-dimensional Autoregressive Integrated Moving Average Bilinear Time Series Models [PDF]
, 2010 J. F. Ojo
openalex +1 more source
A Multivariate Time Series Approach to Modelling Macroeconomic Sequences [PDF]
, 1977 In this paper we discuss a multivariate generalization of autoregressive integrated moving average models. A methodology for constructing multivariate time series models is developed and the derivation of forecasts from such models is considered.
Ledolter, J.
core
Energy Science &Engineering, EarlyView.Forecasts peak electricity demand in Jordan for grid expansion over the next decade. Introduces a comparative method combining ARIMA, ARIMA‐X, and regression models. Projections show a 41% peak load increase by 2035, reaching around 5300 MW. The findings support capacity planning, pricing strategies, and network expansion.
Rafat Aljarrah +5 more
wiley +1 more source
Fuzzy Auto-Regressive Integrated Moving Average (FARIMA) Model for Forecasting the Gold Prices
Journal of Smart Economic Growth, 2020 In this study, the Fuzzy Auto-Regressive Integrated Moving Average (FARIMA) Model has been used to predict gold prices, The main objective was to estimate the fractional parameters by using the fuzzy regression method of TANAKA.
Abdelkader Sahed +2 more
doaj
An Autoregressive Integrated Moving Average Model for Predicting Varicella Outbreaks - China, 2019. [PDF]
China CDC Wkly, 2023 Wang M +7 more
europepmc +1 more source