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 …
Survey of electricity demand forecasting and demand side management techniques in different sectors to identify scope for improvement
Electricity demand is increasing at a rapid rate. Sustainability related challenges are posing
an immediate cause of concern for the planet. Smart Grid provides an efficient way to …
an immediate cause of concern for the planet. Smart Grid provides an efficient way to …
[HTML][HTML] Electricity demand forecasting with hybrid classical statistical and machine learning algorithms: Case study of Ukraine
TG Grandón, J Schwenzer, T Steens, J Breuing - Applied Energy, 2024 - Elsevier
This article presents a novel hybrid approach using classic statistics and machine learning
to forecast the national demand of electricity. As investment and operation of future energy …
to forecast the national demand of electricity. As investment and operation of future energy …
Machine learning-based electricity load forecast for the agriculture sector
A large section of the population has a source of income from the agriculture sector, but their
share in the Indian GDP is low. Thus, there is a need to forecast energy to improve and …
share in the Indian GDP is low. Thus, there is a need to forecast energy to improve and …
Long-term sector-wise electrical energy forecasting using artificial neural network and biogeography-based optimization
J Kumaran, G Ravi - Electric Power Components and Systems, 2015 - Taylor & Francis
This article presents a hybrid model involving artificial neural networks and biogeography-
based optimization for long-term forecasting of India's sector-wise electrical energy demand …
based optimization for long-term forecasting of India's sector-wise electrical energy demand …
Insider employee-led cyber fraud (IECF) in Indian banks: from identification to sustainable mitigation planning
NC Roy, S Prabhakaran - Behaviour & Information Technology, 2024 - Taylor & Francis
This paper explores the different insider employee-led cyber frauds (IECF) based on the
recent large-scale fraud events of prominent Indian banking institutions. Examining the …
recent large-scale fraud events of prominent Indian banking institutions. Examining the …
Development of adaptive artificial neural network security assessment schema for malaysian power grids
The mission of the power system operator has become more complicated than before due to
increasing load demand, which causes power systems to operate near their security limits …
increasing load demand, which causes power systems to operate near their security limits …
Artificial neural network-based model for predicting moisture content in rice using UAV remote sensing data
TK Sarkar, CS Ryu, JG Kang, YS Kang… - Korean Journal of …, 2018 - koreascience.kr
The percentage of moisture content in rice before harvest is crucial to reduce the economic
loss in terms of yield, quality and drying cost. This paper discusses the application of artificial …
loss in terms of yield, quality and drying cost. This paper discusses the application of artificial …
Electricity demand forecasting with hybrid statistical and machine learning algorithms: Case study of ukraine
TG Grandon, J Schwenzer, T Steens… - arxiv preprint arxiv …, 2023 - arxiv.org
This article presents a novel hybrid approach using statistics and machine learning to
forecast the national demand of electricity. As investment and operation of future energy …
forecast the national demand of electricity. As investment and operation of future energy …
Energy demand forecasting: avoiding multi-collinearity
MN Morgül Tumbaz, M İpek - Arabian Journal for Science and Engineering, 2021 - Springer
As having one of the major economies and rising population, Turkey's energy demand is
increasing substantially. The main objective of this research was to apply ridge regression to …
increasing substantially. The main objective of this research was to apply ridge regression to …