A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Electrical load forecasting models: A critical systematic review
C Kuster, Y Rezgui, M Mourshed - Sustainable cities and society, 2017 - Elsevier
Electricity forecasting is an essential component of smart grid, which has attracted
increasing academic interest. Forecasting enables informed and efficient responses for …
increasing academic interest. Forecasting enables informed and efficient responses for …
A hybrid load forecasting model based on support vector machine with intelligent methods for feature selection and parameter optimization
Y Dai, P Zhao - Applied energy, 2020 - Elsevier
Accurate power load forecasting contributes to guaranteeing safe dispatch and stable
operation of a power system. As a great forecasting tool, support vector machine is widely …
operation of a power system. As a great forecasting tool, support vector machine is widely …
A review on applications of ANN and SVM for building electrical energy consumption forecasting
The rapid development of human population, buildings and technology application currently
has caused electric consumption to grow rapidly. Therefore, efficient energy management …
has caused electric consumption to grow rapidly. Therefore, efficient energy management …
Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
Accurate and reliable forecasting models for electricity demand (G) are critical in
engineering applications. They assist renewable and conventional energy engineers …
engineering applications. They assist renewable and conventional energy engineers …
Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review
It is important for building owners and operators to manage the electrical energy
consumption of their buildings. As electrical energy is the major form of energy consumed in …
consumption of their buildings. As electrical energy is the major form of energy consumed in …
[PDF][PDF] Recurrent neural networks and nonlinear prediction in support vector machines
JS Raj, JV Ananthi - Journal of Soft Computing Paradigm (JSCP), 2019 - academia.edu
The nonlinear regression estimation issues are solved by successful application of a novel
neural network technique termed as support vector machines (SVMs). Evaluation of …
neural network technique termed as support vector machines (SVMs). Evaluation of …
A strategy for short-term load forecasting by support vector regression machines
This paper presents a generic strategy for short-term load forecasting (STLF) based on the
support vector regression machines (SVR). Two important improvements to the SVR based …
support vector regression machines (SVR). Two important improvements to the SVR based …
Time series prediction using support vector machines: a survey
NI Sapankevych, R Sankar - IEEE computational intelligence …, 2009 - ieeexplore.ieee.org
Time series prediction techniques have been used in many real-world applications such as
financial market prediction, electric utility load forecasting, weather and environmental state …
financial market prediction, electric utility load forecasting, weather and environmental state …
A data-driven strategy for short-term electric load forecasting using dynamic mode decomposition model
The electric load forecasting is extremely important for energy demand management,
stability and security of power systems. A sufficiently accurate, robust and fast short-term …
stability and security of power systems. A sufficiently accurate, robust and fast short-term …