Short-term load forecasting utilizing a PSO and LSTM combination model:a brief review

QR Code

Short-term load forecasting utilizing a PSO and LSTM combination model:a brief review

In order to provide electricity to customers in a safe and economical manner, power companies face many economic and technical challenges in their operations. Power flow analysis, planning, and control of power systems stand out among these issues. Over the last several years, one of the most develo...

Full description

Bibliographic Details
Main Authors:	Ahmad @ Mohd Yusoff, Faisul Arif, Samsudin, Khairulmizam, Hashim, Fazirulhisyam, Liu, Junchen
Format:	Article
Language:	English
Published:	Faculty of Engineering, Universitas Indonesia 2024
Online Access:	http://psasir.upm.edu.my/id/eprint/117767/ http://psasir.upm.edu.my/id/eprint/117767/1/117767.pdf

Similar Items

Short-term load forecasting utilizing a combination model: a brief review
by: Ahmad, Faisul Arif, et al.
Published: (2024)

Performance evaluation of activation functions in deep residual networks for short-term load forecasting
by: Liu, Junchen, et al.
Published: (2025)

Optimising LSTM and BiLSTM models for time series forecasting through hyperparameter tuning
by: Nur Haizum, Abd Rahman, et al.
Published: (2025)

Autoregressive method in short term load forecast
by: N.S., Kamel, et al.
Published: (2008)

Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach
by: Majeed, Mokhalad A., et al.
Published: (2023)

Hybrid Metaheuristic Algorithm for Short Term Load Forecasting
by: Zuriani, Mustaffa, et al.
Published: (2016)

Short term load forecast using burg autoregressive technique
by: Z., Baharudin, et al.
Published: (2007)

Short Term Load Forecasting Using Data Mining Technique
by: Intan Azmira , binti Wan Abdul Razak, et al.
Published: (2008)

Structural damage quantification using long short-term memory (LSTM) auto-encoder and impulse response functions
by: Chencho,, et al.
Published: (2024)

Analysis of short term load forecasting techniques / Tan Vy Luoh
by: Tan, Vy Luoh
Published: (2019)

A novel hybrid metaheuristic algorithm for short term load forecasting
by: Zuriani, Mustaffa, et al.
Published: (2017)

Case study of short-term electricity load forecasting with temperature dependency
by: Tai, Hein Fong
Published: (2009)

Green energy forecasting using multiheaded convolutional LSTM model for sustainable life
by: Liu, Peng, et al.
Published: (2024)

Electrocorticography based motor imagery movements classification using long short-term memory (LSTM) based on deep learning approach
by: Rashid, Mamunur, et al.
Published: (2020)

A hybrid prediction model for short-term load forecasting in power systems
by: Zuriani, Mustaffa, et al.
Published: (2024)

Battery electric vehicle charging load forecasting using LSTM on STL trend, seasonality, and residual decomposition
by: Syahrizal, Salleh, et al.
Published: (2024)

Econometric Forecasting Models for Short Term Natural Rubber Prices
by: Khin, Aye Aye
Published: (2010)

Composite Models for Short Term Forecasting for Natural Rubber Prices
by: Shamsudin, Mad Nasir, et al.
Published: (1990)

Using sentiment analysis to forecast stock short-term trend
by: Tan, Lin
Published: (2024)

An Application of Radial Basis Function Neural Network for Short Term Load Forecasting Solution
by: Nurul Faezah, Othman, et al.
Published: (2018)

Optimization of power utilization in multi-mobile robot foraging behavior inspired by honeybees system
by: Ahmad, Faisul Arif, et al.
Published: (2014)

Modelling possibility of short-term forecasting of market parameters for portfolio selection
by: Dokuchaev, Nikolai
Published: (2015)

Comparative forecasting models accuracy of short-term natural rubber prices.
by: Aye, Aye Khin, et al.
Published: (2011)

Estimation methodology of short term natural rubber price forecasting models
by: Khin, Aye Aye, et al.
Published: (2011)

Sequential process of feature extraction methods for artificial neural network in short term load forecasting
by: Othman, Muhammad Murtadha, et al.
Published: (2015)

Very short-term photovoltaic power forecasting with cloud modeling: A review
by: Barbieri, F., et al.
Published: (2015)

Hybrid Deep Learning Model for Accurate Short-Term Electricity Price Forecasting
by: Moradzadeh, A., et al.
Published: (2025)

Short term forecasting based on hybrid least squares support vector machines
by: Zuriani, Mustaffa, et al.
Published: (2018)

Multi-convolution feature extraction and recurrent neural network dependent model for short-term load forecasting
by: Goh, Hui Hwang, et al.
Published: (2021)

Improving Ann-Based Short-Term and Long-Term Seasonal River Flow Forecasting with Signal Processing Techniques
by: Badrzadeh, H., et al.
Published: (2016)

Short-term forecasting of rooftop retrofitted photovoltaic power generation using machine learning
by: Mohd Herwan, Sulaiman, et al.
Published: (2024)

Short-Term forecasting of floating photovoltaic power generation using machine learning models
by: Mohd Herwan, Sulaiman, et al.
Published: (2024)

Selecting the relevant forecasts for forecast combination
by: Chan, Felix, et al.
Published: (2023)

A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot
by: Samsudin, Khairulmizam, et al.
Published: (2011)

Optimization of neural network configurations for short-term traffic flow forecasting using orthogonal design
by: Chan, Kit Yan, et al.
Published: (2012)

Combining risk forecasts
by: Soltyk, Sylvia, et al.
Published: (2023)

An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for cryptocurrency forecasting
by: Hitam, Nor Azizah, et al.
Published: (2019)

Deep learning-based hybrid short-term solar forecast using sky images and meteorological data
by: Zhang, Liwenbo
Published: (2023)

Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking
by: Barbieri, Florian Benjamin Eric
Published: (2019)

Selection of Significant On-Road Sensor Data for Short-Term Traffic Flow Forecasting Using the Taguchi Method
by: Chan, Kit, et al.
Published: (2012)