Energy models for demand forecasting—A review
Energy is vital for sustainable development of any nation–be it social, economic or
environment. In the past decade energy consumption has increased exponentially globally …
environment. In the past decade energy consumption has increased exponentially globally …
Forecasting methods in energy planning models
KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
Development of regression models to forecast the CO2 emissions from fossil fuels in the BRICS and MINT countries
This study focuses to propose regression models to forecast the fossil fuel-related carbon
dioxide (FFCO 2) emissions in the BRICS (Brazil, the Russian Federation, India, China …
dioxide (FFCO 2) emissions in the BRICS (Brazil, the Russian Federation, India, China …
Multivariate temporal convolutional network: A deep neural networks approach for multivariate time series forecasting
R Wan, S Mei, J Wang, M Liu, F Yang - Electronics, 2019 - mdpi.com
Multivariable time series prediction has been widely studied in power energy, aerology,
meteorology, finance, transportation, etc. Traditional modeling methods have complex …
meteorology, finance, transportation, etc. Traditional modeling methods have complex …
Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm
S Barak, SS Sadegh - International Journal of Electrical Power & Energy …, 2016 - Elsevier
Energy consumption is on the rise in develo** economies. In order to improve present and
future energy supplies, forecasting energy demands is essential. However, lack of accurate …
future energy supplies, forecasting energy demands is essential. However, lack of accurate …
A hybrid approach based on autoregressive integrated moving average and least-square support vector machine for long-term forecasting of net electricity …
F Kaytez - Energy, 2020 - Elsevier
Electricity consumption is on the rise in develo** countries. Most of the research studies in
energy demand forecasting aim to provide that sufficient electricity is produced to meet …
energy demand forecasting aim to provide that sufficient electricity is produced to meet …
A hybrid approach of adaptive wavelet transform, long short-term memory and ARIMA-GARCH family models for the stock index prediction
M Zolfaghari, S Gholami - Expert Systems with Applications, 2021 - Elsevier
Modelling and forecasting the stock price constitute an important area of financial research
for both academics and practitioners. This study seeks to determine whether improvements …
for both academics and practitioners. This study seeks to determine whether improvements …
Forecasting of natural gas consumption with artificial neural networks
J Szoplik - Energy, 2015 - Elsevier
In this study, the results of forecasting of the gas demand obtained with the use of artificial
neural networks are presented. Design and training of MLP (multilayer perceptron model) …
neural networks are presented. Design and training of MLP (multilayer perceptron model) …
An overview of energy demand forecasting methods published in 2005–2015
The importance of energy demand management has been more vital in recent decades as
the resources are getting less, emission is getting more and developments in applying …
the resources are getting less, emission is getting more and developments in applying …
Forecasting the annual electricity consumption of Turkey using an optimized grey model
Energy demand forecasting is an important issue for governments, energy sector investors
and other related corporations. Although there are several forecasting techniques, selection …
and other related corporations. Although there are several forecasting techniques, selection …