Computational Intelligence 9802 This repository contains the final projects of the course Computational Intelligence lectured at the university of Guilan in Spring 2020 This page is still being updated Note that due to the spread of the coronavirus (COVID-19) classes are held online through this link This course presents an introduction to the concepts and algorithms of Computational • Propositioning NARX for short-term load forecasting with the inclusion of special days In the literature computational-intelligence-based methods are usually used for long-term forecasting Only a few papers have examined the effectiveness of NARX models for short-term load forecasting and none of them applied NARX to more than

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Short-term Electric Load Forecasting Using Computational Intelligence Methods Sergio Jurado∗ Juan Peralta† Angela Nebot` ‡ Francisco Mugica and Paulo Cortez ∗Sensing Control Systems Arago 208-210 08011 Barcelona Spain Email: sergio juradosens-ingcontrol

Jan 01 2007Free Online Library: A new approach for the short-term load forecasting with autoregressive and artificial neural network models by International Journal of Computational Intelligence Research Computers and office automation Computers and Internet Electric power system protection Technology application Electric power systems Protection and preservation Turkey Neural

Seyedeh Narjes Fallah Mehdi Ganjkhani Shahaboddin Shamshirband Kwok-wing Chau 2019 Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview Energies MDPI Open Access Journal vol 12(3) pages 1-21 January Ritwik Haldar Ashraf Hossain Kirtan Gopal Panda 2019

Seyedeh Narjes Fallah Mehdi Ganjkhani Shahaboddin Shamshirband Kwok-wing Chau 2019 Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview Energies MDPI Open Access Journal vol 12(3) pages 1-21 January Ritwik Haldar Ashraf Hossain Kirtan Gopal Panda 2019

Jul 15 2016The treatment of bus load characteristics is held with computational intelligence techniques such as clustering and ANN Neural network based systems are a favorable scheme in recent years in price and load predictions over traditional time series models

Supplier Short Term Load Forecasting Using Support Vector

Supplier Short Term Load Forecasting Using Support Vector Regression and Exogenous Input In power systems task of load forecasting is important for keeping equilibrium between production and consumption With liberalization of electricity markets task of load forecasting changed because each market participant has to forecast their own load

computational intelligence dynamic system economic load dispatch emission fossil fuel fuzzy logic 1 Introduction Computing accuracy is vital to determine the best outcomes when solving economic dispatch problem [1] Precise economic dispatch requires several consideration such as generators limits

Computational Intelligence Techniques of Long-Term Electric Power Load Forecasting on Iraqi National Grid Hanan Mikhael Dawood Lecturer Younis Muhhy Nsaif College of Engineering University of Baghdad Baghdad Iraq Abstract Load forecasting has played an important role in generation transmission and distribution system planning

computational intelligence dynamic system economic load dispatch emission fossil fuel fuzzy logic 1 Introduction Computing accuracy is vital to determine the best outcomes when solving economic dispatch problem [1] Precise economic dispatch requires several consideration such as generators limits

Seyedeh Narjes Fallah Mehdi Ganjkhani Shahaboddin Shamshirband Kwok-wing Chau 2019 Computational Intelligence on Short-Term Load Forecasting: A Methodological Overview Energies MDPI Open Access Journal vol 12(3) pages 1-21 January Ritwik Haldar Ashraf Hossain Kirtan Gopal Panda 2019

Applied Computational Intelligence and Soft Computing provides a forum for research that connects the disciplines of computer science engineering and mathematics using the technologies of computational intelligence and soft computing

Research Reseach Projects Swarm Intelligence We have done a lot of work on novel approaches in the filed of swarm intelligence Recently we proposed Generative Adeversarial Optimization (GAO) which combines neural network and black-box optimization And we proposed Fireworks Algorithm (FWA) in 2010 which is a powerful swarm intelligence algorithm and attracted lots of attention

Computational Intelligence Theory and Applications International Conference 9th Fuzzy Days in Dortmund Germany Sept 18-20 2006 Proceedings Short-Term Load Forecasting in Power System Using Least Squares Support Vector Machine Pages 117-126 LV Ganyun (et al )

Data

We present our data-driven supervised machine-learning (ML) model to predict heat load for buildings in a district heating system (DHS) Even though ML has been used as an approach to heat load prediction in literature it is hard to select an approach that will qualify as a solution for our case as existing solutions are quite problem specific For that reason we compared and evaluated three

Oct 24 2019Zheng J Xu C Zhang Z Li X : Electric load forecasting in smart grids using long-short-term-memory based recurrent neural network In: 2017 51st Annual Conference on Information Sciences and Systems (CISS) pp 1–6 (2017) Google Scholar

May 11 2019Short-term wind energy forecasting can be improved using this model to enhance the wind power quality 12 h ahead b) No previous studies applied computational intelligence for short-term wind speed forecasting for such heights in Uruguay which is a humid subtropical climate region

computational intelligence methods and econometric techniques have largely dominated literature that is more recent The choice of the appropriate technique for load forecasting depends largely upon the forecast horizon Short-term load forecasts (STLF) which forecast one hour to one week ahead have

At a district level [21] addresses the problem of accurate short-term load forecasting including both meteorological and technical variables The proposed model is based on a DL algorithm that combines di erent backpropagation techniques to ease its computational burden Similarly a DL

Computational Intelligence: Principles Techniques and Applications 2005 Abstract Ghanbari A Hadavandi E and Abbasian-Naghneh S An intelligent ACO-SA approach for short term electricity load prediction Proceedings of the Advanced intelligent computing theories and applications and 6th international conference on Intelligent computing