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A Short-Term Load Forecasting Model with a Modified Particle Swarm Optimization Algorithm and Least Squares Support Vector Machine Based on the Denoising Method of Empirical Mode Decomposition and Grey Relational Analysis

Dongxiao Niu, Shuyu Dai
2017 Energies  
The models of BP neural network, SVM (Support vector machine), LSSVM (Least squares support vector machine), PSO-LSSVM (Particle swarm optimization-Least squares support vector machine), MPSO-LSSVM (Modified  ...  In this paper, a novel short-term Empirical Mode Decomposition-Grey Relational Analysis-Modified Particle Swarm Optimization-Least Squares Support Vector Machine (EMD-GRA-MPSO-LSSVM) load forecasting model  ...  Acknowledgments: This work was supported by Natural Science Foundation of China (Project No. 71471059).  ... 
doi:10.3390/en10030408 fatcat:4qzwtdlr6ne7hi2iflshlohudm

Industrial Ultra-short-term Load Forecasting with Data Completion

Haoyu Jiang, Angjian Wu, Bo Wang, Peizhe Xu, Gang Yao
2020 IEEE Access  
The proposed model combines the Cubature Kalman filter (CKF) prediction model with good performance in nonlinear dynamic systems and the least square support vector machine (LS-SVM) prediction model with  ...  The grey neural network is used to integrate the two algorithms, which further improves the accuracy of ultra-short-term load forecasting.  ...  ACKNOWLEDGMENT The project was supported by the Young Scientists Fund of the National Natural Science Foundation of China (51806193), China Postdoctoral Science Foundation (No. 2018M630672).  ... 
doi:10.1109/access.2020.3017655 fatcat:dtat2o5ipjfs5l3cruuugwsl4y

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

Wei Sun, Minquan Ye
2015 Journal of Electrical and Computer Engineering  
In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM) which is optimized by fruit fly algorithm (FOA) for short-term  ...  The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.  ...  Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.1155/2015/862185 fatcat:g4lec74nnfb4xph3tabaq32ybm

Power load forecasting algorithm based on nonlinear inertial factor change pattern particle swarm optimization algorithm

Jin Liang, Wang Yongzhi, Bao Xiaodong, J. Heled, A. Yuan
2018 MATEC Web of Conferences  
The common method of power load forecasting is the least squares support vector machine, but this method is very dependent on the selection of parameters.  ...  In this paper, we propose a new particle swarm optimization algorithm, it uses non-linear inertial factor change that is used to optimize the algorithm least squares support vector machine to avoid falling  ...  At present, the algorithms based on Least squares support vector machine (LS-SVM) are widely used in short-term power load forecasting.  ... 
doi:10.1051/matecconf/201817302016 fatcat:zpvpequ5xzblnfm2ozgveekgcu

Survey on short-term load forecasting using hybrid neural network techniques

Shaive Dalela, Aditya Verma, A L.Amutha
2018 International Journal of Engineering & Technology  
The paper investigates the application of artificial neural networks (ANN) with fuzzy logic (FL), Genetic Algorithm(GA), Particle Swarm Optimization(PSO) and Support Vector Machines(SVM) as forecasting  ...  In the current work, several latest methodologies based on artificial neural networks along with other techniques have be discussed, in order to obtain short-term load forecasting.  ...  Afshin, M.; Sadeghi an, A, "PCA-based Least Squares Support Vector Machines in Week-Ahead Load Forecasting,"(2007) [14] .This paper lays down the operation of principal component analysis (PCA) to least  ... 
doi:10.14419/ijet.v7i2.8.10486 fatcat:cl5nj5dgazhzppmxkrhwxgywcu

Uncertain Machine Load Forecasting Based on Least Squares Support Vector Machine [chapter]

Qiaofeng Meng
2021 Frontiers in Artificial Intelligence and Applications  
Machine state is a very important constraint for job shop scheduling. For the uncertainty machine state, the paper proposes a machine load forecasting method based on support vector machine.  ...  The efficiency of the algorithm is verified by the production workshop instance.  ...  Meng / Uncertain Machine Load Forecasting Based on Least Squares Support Vector Machine Q. Meng / Uncertain Machine Load Forecasting Based on Least Squares Support Vector Machine 257 Q.  ... 
doi:10.3233/faia210410 fatcat:c4tqj5spj5bdvn4xk3x3vynbuq

Load forecasting considering multiple influencing factors

Xin Ning, Liang Jin
2020 Journal of Physics, Conference Series  
Finally, the effectiveness of the Least squares support vector machine algorithm load prediction after considering various factors is verified by comparison with the traditional neural network algorithm  ...  The LSSVM algorithm is used for short-term load forecasting. Firstly, the invalid data is eliminated by data preprocessing, the missing data is completed, and the data of the content is included.  ...  Considering the advantages of least squares support vector machine in the accuracy and efficiency of prediction, this paper based on the actual data, through the least squares support vector machine algorithm  ... 
doi:10.1088/1742-6596/1449/1/012042 fatcat:4f3my5ho5rejlde5ry42ym2rxi

Long-term load forecasting using grey wolf optimizer -least-squares support vector machine

Z. M. Yasin, N. A. Salim, N.F.A. Aziz, Y.M. Ali, H. Mohamad
2020 IAES International Journal of Artificial Intelligence (IJ-AI)  
In this paper, Least-Square Support Vector Machine (LSSVM) is used to predict the long-term load demand.  ...  The performance of GWO-LSSVM is compared with other methods such as LSSVM and Ant Lion OptimizerLeast-Square Support Vector Machine (ALO-LSSVM).  ...  ACKNOWLEDGEMENTS This research is fully supported by Universiti Teknologi MARA Malaysia and the Ministry of Higher Education (MOHE) Malaysia through research grant 600-IRMI/FRGS 5/3 (157/2019).  ... 
doi:10.11591/ijai.v9.i3.pp417-423 fatcat:zu2mm36r5nhc5gqk5ywxsunqze

A Novel Short-term Multi-input-multi-output Prediction Model of Wind Speed and Wind Power with LSSVM Based on Quantum-behaved Particle Swarm Optimization Algorithm

Jingxian Yang, Yifan Cheng, Jingtao Huang
2017 Chemical Engineering Transactions  
to optimize the most important parameters which influence the least squares support vector machine regression model.  ...  In this paper, the least squares support vector machine (LSSVM) is chosen as the wind speed and the wind power prediction model and quantum-behaved particle swarm optimization (QPSO) algorithm is used  ...  Internal logic section: MIMO prediction model of wind farm based on QPSO-LSSVM is built and relevant program is carried out in this section. firstly, the parameters of least squares support vector machine  ... 
doi:10.3303/cet1759146 doaj:91b2b8391b6b4508bd244d9addc7f52a fatcat:3zh5houw2va4lfn4xifekephom

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Improved Cuckoo Search

Yi Liang, Dongxiao Niu, Minquan Ye, Wei-Chiang Hong
2016 Energies  
To end this, this paper proposes a hybrid model based on wavelet transform (WT) and least squares support vector machine (LSSVM), which is optimized by an improved cuckoo search (CS).  ...  Vandewalle proposed least squares support vector machine (LSSVM) as a classifier in 1999.  ...  Acknowledgments: This work is supported by the Natural Science Foundation of China (Project No. 71471059).  ... 
doi:10.3390/en9100827 fatcat:4bualijngnayti3xr33r7k76cu

Application of the Least Square Support Vector Machine for point-to-point forecasting of the PV Power

Mahdi Farhadi, Nader Mollayi
2019 International Journal of Electrical and Computer Engineering (IJECE)  
In this paper, a novel algorithm for point to point prediction of the generated power based on the least squares support vector machine (LS-SVM) has been proposed which can handle the large training database  ...  of the algorithms used for training the models.  ...  ACKNOWLEDGEMENTS The present paper is based on the data of a 20 KW solar powerplant and the aerial data located in University of Birjand.  ... 
doi:10.11591/ijece.v9i4.pp2205-2211 fatcat:epjmrvlp75f3rdxermpaew2vba

Short-term Load Forecasting of Smart Grid Systems by Combination of General Regression Neural Network and Least Squares-Support Vector Machine Algorithm Optimized by Harmony Search Algorithm Method

Ming Zeng, Song Xue, Zhijie Wang, Xiaoli Zhu, Ge Zhang
2013 Applied Mathematics & Information Sciences  
The new approach employs generalized regression neural network (GRNN) to select influence factors of short-term load, and then a least squares-support vector machine (LS-SVM) based on harmony search algorithm  ...  This paper presents an optimization algorithm to solve the short-term load forecasting problem more quickly and accurately in progress of smart grid development.  ...  Acknowledgement The work described in this paper was supported by National Science  ... 
doi:10.12785/amis/071l38 fatcat:aa3ulnfx4ffo5c7kx54wt5pami

Short-Term Load Forecasting for Electrical Dispatcher of Baghdad City based on SVM-FA

Aqeel S. Jaber, Koay A., Nadheer A.
2018 International Journal of Advanced Computer Science and Applications  
This research deals with the use of a regression forecast model (Support Vector Machine, SVM) for the prediction of the vector data for electrical power loading and temperature in Baghdad city.  ...  The improvement of load forecasting accuracy is an important issue in the scientific optimization of power systems.  ...  Xing et al suggested many hybrid prediction methods based on SVM, and one of the methods depend on the use of least squares support vector machine [12] .  ... 
doi:10.14569/ijacsa.2018.091141 fatcat:mhzv4duibrcdtlthqdo5ddib44

The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection

Jin-peng Liu, Chang-ling Li
2017 Sustainability  
To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm.  ...  In paper [11] , an effective short-term load forecasting model based on the generalized regression neural network with decreasing step fruit fly optimization algorithm was proposed.  ...  Conclusions This paper proposed a short-term load forecasting system based on wavelet least square support vector machine (W-LSSVM) and sperm whale algorithm (SWA).  ... 
doi:10.3390/su9071188 fatcat:2bsh23zvofedjhcqohblym6dom

Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm

Hongze Li, Sen Guo, Huiru Zhao, Chenbo Su, Bao Wang
2012 Energies  
The least squares support vector machine (LSSVM) has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values  ...  Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters  ...  the Ministry of Education of China (Project number: 11YJA790217).  ... 
doi:10.3390/en5114430 fatcat:uzlhqws3qbdpnhllliu3eh2xdy
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