Next 24-Hours Load Forecasting for the Western Area of Saudi Arabia Using Artificial Neural Network and Particle Swarm Optimization
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Summary
An effective load forecasting model for the western area of Saudi Arabia (WESA) and an optimization process to improve the results to be at least better than existing results are presented.
- Type
- article
- Published
- 2010-04-02
- Cited by
- 3
- References
- 32
- OpenAlex
- https://openalex.org/W79405497
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:107411691
Keywords
Particle swarm optimization, Artificial neural network, Computer science, Process (computing), Demand forecasting
References
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- Comparison of very short-term load forecasting techniques
- Short-term load forecasting by a neuro-fuzzy based approach
- Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data
- Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks
- Hybrid ellipsoidal fuzzy systems in forecasting regional electricity loads
- Fuzzy and neuro-fuzzy computing models for electric load forecasting
- Fuzzy short-term electric load forecasting using Kalman filter
- Short-term forecasting of wind speed and related electrical power
- A regression-based approach to short-term system load forecasting
- Gauss-Newton approximation to Bayesian learning
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