A modified particle swarm optimization for combining forecasting

被引：0

作者：

Feng, XY ^{[1
]}

Wan, LM ^{[1
]}

Liang, YC ^{[1
]}

Sun, YF ^{[1
]}

Lee, HP ^{[1
]}

Wang, Y ^{[1
]}

机构：

[1] Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China

来源：

PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年

关键词：

Particle Swarm Optimization (PSO); combining forecasting; hybrid algorithm;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A modified particle swarm optimization (PSO) algorithm is proposed. Linear constraints in the PSO are added to satisfy normalization conditions for different problems. A hybrid algorithm based on the modified PSO and combining forecasting is presented. Combining forecasting can improve the forecasting accuracy through combining different forecasting methods. The effectiveness of the algorithm is demonstrated through the prediction on the sunspots and the stocks data. Simulated results show that the hybrid algorithm can improve the forecasting accuracy to a great extent.

引用

页码：2384 / 2389

页数：6

共 50 条

[41] Streamflow forecasting by SVM with quantum behaved particle swarm optimization
Sudheer, Ch
Anand, Nitin
Panigrahi, B. K.
Mathur, Shashi
NEUROCOMPUTING, 2013, 101 : 18 - 23
[42] Extreme Learning Machine and Particle Swarm Optimization for Inflation Forecasting
Alfiyatin, Adyan Nur
Rizki, Agung Mustika
Mahmudy, Wayan Firdaus
Ananda, Candra Fajri
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (04) : 473 - 478
[43] Combined modeling for electrical load forecasting with particle swarm optimization
Xiao, Liye
Xiao, Liyang
2014 IEEE WORKSHOP ON ELECTRONICS, COMPUTER AND APPLICATIONS, 2014, : 395 - 400
[44] Particle Swarm Optimization for Long-Term Demand Forecasting
Hafez, Ahmed A. A.
Elsherbiny, Mohamed K.
PROCEEDINGS OF 2016 EIGHTEENTH INTERNATIONAL MIDDLE EAST POWER SYSTEMS CONFERENCE (MEPCON), 2016, : 179 - 183
[45] A new chaos particle swarm optimization combining the chaotic perturbation
Mengxia, Li
Ruiquan, Liao
International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (04) : 41 - 48
[46] A Novel Multiobjective Particle Swarm Optimization Combining Hypercube and Distance
Shu, Xiaoli
Liu, Yanmin
Zhang, Qian
Yang, Meilan
SCIENTIFIC PROGRAMMING, 2022, 2022
[47] Combining technical trading rules using particle swarm optimization
Wang, Fei
Yu, Philip L. H.
Cheung, David W.
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (06) : 3016 - 3026
[48] Hybrid algorithm combining ant colony optimization algorithm with particle swarm optimization
Gao Shang
Jiang Xin-zi
Tang Kezong
Yang Jingyu
2006 CHINESE CONTROL CONFERENCE, VOLS 1-5, 2006, : 481 - +
[49] A Modified Particle Swarm Optimization with an Adaptive Acceleration Coefficients
Tang Ziyu
Zhang Dingxue
2009 ASIA-PACIFIC CONFERENCE ON INFORMATION PROCESSING (APCIP 2009), VOL 2, PROCEEDINGS, 2009, : 330 - +
[50] Modified particle swarm optimization with novel population initialization
Khajeh, Atieh
Ghasemi, Mohammad Reza
Arab, Hamed Ghohani
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, 2019, 40 (06): : 1167 - 1179

← 1 2 3 4 5 →