Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (7): 354-361.doi: 10.11896/jsjkx.230600181

• Artificial Intelligence • Previous Articles     Next Articles

Adaptive Grey Wolf Optimizer Based on IMQ Inertia Weight Strategy

YU Mingyang1, LI Ting2,3, XU Jing1   

  1. 1 College of Artificial Intelligence,Nankai University,Tianjin 300350,China
    2 College of Computer Science,Nankai University,Tianjin,300350,China
    3 Tianjin Jinhang Institute of Technical Physics,Tianjin,300350,China
  • Received:2023-06-24 Revised:2023-11-06 Online:2024-07-15 Published:2024-07-10
  • About author:YU Mingyang,born in 2000,postgra-duate.His main research interests include deep learning and intelligent optimization algorithm.
    LI Ting,born in 1988,master,senior engineer.Her main research interests include image big data governance,algorithm parity and intelligent recognition algorithm.
  • Supported by:
    Natural Science Foundation of Tianjin,China(21JCYBJC00110).

PDF (PC)

419

Abstract: Aiming at the problems of low optimization accuracy and slow convergence speed of grey wolf optimizer(GWO),this paper proposes an adaptive grey wolf optimization algorithm(ISGWO) based on IMQ inertia weighting strategy.This algorithm utilizes the properties of the IMQ function to achieve a nonlinear adjustment of the inertia weights,which better balances the global exploration ability and local exploitation ability of the algorithm.At the same time,it adaptively updates the position of individuals based on the Sigmoid exponential function to better search and optimize the solution space of the problem.Six basic functions and 29 CEC2017 functions are used to test ISGWO and compare it with six commonly used algorithms,and the experimental results show that ISGWO has superior convergence accuracy and speed.

Key words: IMQ function, Inertia weight, Adaptive, Grey wolf optimizer, Convergence speed, Optimization accuracy

CLC Number: 

  • TP301
[1]KENNEDY J,EBERHART R.Particle Swarm Optimization[C]//International Conference on Neural Networks.New York:IEEE Press,1995:1-2.
[2]YANG X S.Firefly algorithms for multimodal optimization[C]//International symposium on stochastic algorithms.Berlin,Heidelberg:Springer,2009:169-178.
[3]MIRJALILI S.SCA:a sine cosine algorithm for solving optimization problems[J].Knowledge-Based Systems,2016,96:120-133.
[4]BAYRAKTAR Z,KOMURCU M,WERNER D H.Wind Driven Optimization(WDO):A novel nature-inspired optimization algorithm and its application to electromagnetics[C]//2010 IEEE Antennas and Propagation Society International Symposium.New York:IEEE Press,2010:1-4.
[5]PAN W T.A new fruit fly optimization algorithm:taking the financial distress model as an example[J].Knowledge-Based Systems,2012,26:69-74.
[6]MIRJALILI S,MIRJALILI S M,LEWIS A.Grey wolf optimizer[J].Advances in Engineering Software,2014,69:46-61.
[7]FAN X Z,YU M.Coverage Optimization of WSN Based on lmproved Grey Wolf Optimizer[J].Computer Science,2022,49(S1):628-631.
[8]MAO M X,XU Z,CUI L C,et al.Research on Multi-PeakMPPT of Photovoltaic Array Based on Modified Gray Wolf Optimization Algorithm[J].Acta Energiae Solaris Sinica(Journal of Solar Energy),2023,44(3):450-456.
[9]ZHANG W N,ZHOU Q L,JIAO Z Y,et al.Hybrid Algorithm of Grey Wolf Optimizer and Arithmetic Optimization Algorithm for Class Integration Test Order Generation[J].Computer Science,2023,50(5):72-81.
[10]XI L,HE M,ZHOU B Q,et al.Research on False Data Injection Attack Detection in Power System Based on Improved Multi Layer Extreme Learning Machine[J].Acta Automatica Sinica(Acta Automatica),2023,49(4):881-890.
[11]ZHANG A,YANG M,BI W H,et al.Task allocation of heterogeneous multi-UAVs in uncertain environment based on multi-strategy integrated GWO[J].Acta Aeronautica et Astronautica Sinica(Journal of Aeronautics),2023,44(8):148-164.
[12]KANG Y,WANG H N,TAO L,et al.Hybrid Improved Flower Pollination Algorithm and Gray Wolf Algorithm for Feature Selection[J].Computer Science,2022,49(S1):125-132.
[13]LIU Y,LIU D P,MU Y,et al.Power Distribution Strategy of Hybrid Energy Storage System Based on GWO Optimization of ICEEMDAN Decomposition[J].Journal of Electrical Enginee-ring,2022,17(4):257-267.
[14]LIU Y,JIANG Y,ZHANG X,et al.An improved grey wolf optimizer algorithm for identification and location of gas emission[J].Journal of Loss Prevention in the Process Industries,2023,82:105003.
[15]WANG H,ZOU Q,LIN H.A Quasi-Optimal Shape DesignMethod for Electromagnetic Scatterers Based on NURBS Surfaces and Filter-Enhanced GWO[J].IEEE Transactions on Antennas and Propagation,2023,71(5):4236-4245.
[16]LU M,QU L D,HE D X.Pathfinder Grey Wolf Algorithm for Solving Multiple-roots Nonlinear Equations[J].Chinese Journal of Engineering Mathematics,2022,39(6):957-968.
[17]LIU Z Q,HE L,YUAN L,et al.Path Planning of Mobile Robot Based on TGWO Algorithm[J].Journal of Xi'an Jiaotong University,2022,56(10):49-60.
[18]XIE S P,WU B S,ZHAO X T,et al.Structural damage identification based on improved gray wolf optimization algorithm[J].Chinese Journal of Computational Mechanics,2024,41(2):256-262.
[19]ZHANG L,ZHENG L D,LENG X B,et al.Research on Multi-Objective Optimization Strategy of Wind-Photovoltaic-Pumped Storage Combined System Based on Gray Wolf Algorithm[J/OL].Journal of Shanghai Jiao Tong University.https://doi.org/10.16183/j.cnki.jsjtu.2023.049.
[20]YU X,XU W Y,WU X,et al.Reinforced exploitation and exploration grey wolf optimizer for numerical and real-world optimization problems[J].Applied Intelligence,2022,52(8):8412-8427.
[21]RATHAN S,SHAH D,KUMAR T H,et al.Adaptive IQ and IMQ-RBFs for solving Initial Value Problems:Adam-Bashforth and Adam-Moulton methods[J].arXiv:2302.06113,2023.
[22]E J T,LIU J,WAN Z.A novel adaptive algorithm of particle swarm optimization based on the human social learning intelligence[J].Swarm and Evolutionary Computation,2023,80:101336.
[23]BANAIE-DEZFOULI M,NADIMI-SHAHRAKI M H,BE-HESHTI Z.BEGWO:Binary extremum-based grey wolf optimizer for discrete optimization problems[J].Applied Soft Computing,2023,146:110583.
[1] HUANG Weijie, GUO Xianwei, YU Zhiyong, HUANG Fangwan. Active Sampling of Air Quality Based on Compressed Sensing Adaptive Measurement Matrix [J]. Computer Science, 2024, 51(7): 116-123.
[2] TAN Peng, OU Bo. Medical Image Reversible Contrast Enhancement Based on Adaptive Histogram Equalization [J]. Computer Science, 2024, 51(6A): 230700124-7.
[3] LIU Heng, LIN Hongyu, WU Tao. Detection Method for Workers’ Illegal Operation Behavior in PackagingWorkshop of CigaretteFactory [J]. Computer Science, 2024, 51(6A): 230700123-8.
[4] WANG Zhongxiao, PENG Qinglan, SUN Ruoxiao, XU Xifeng, ZHENG Wanbo, XIA Yunni. Delay and Energy-aware Task Offloading Approach for Orbit Edge Computing [J]. Computer Science, 2024, 51(6A): 240100188-9.
[5] YIN Baosheng, ZHOU Peng. Chinese Medical Named Entity Recognition with Label Knowledge [J]. Computer Science, 2024, 51(6A): 230500203-7.
[6] LI Zhibo, LI Qingbao, LAN Mingjing. Method of Generating Test Data by Genetic Algorithm Based on ART Optimal Selection Strategy [J]. Computer Science, 2024, 51(6): 95-103.
[7] LI Zhiqian, ZHENG Jiali, CHEN Yijun, ZHANG Jiangbo. Enhanced Snake Optimizer Based RFID Network Planning [J]. Computer Science, 2024, 51(6): 375-383.
[8] YUAN Rong, PENG Lilan, LI Tianrui, LI Chongshou. Traffic Flow Prediction Model Based on Dual Prior-adaptive Graph Neural ODE Network [J]. Computer Science, 2024, 51(4): 151-157.
[9] YAN Wenjie, YIN Yiying. Human Action Recognition Algorithm Based on Adaptive Shifted Graph Convolutional Neural
Network with 3D Skeleton Similarity [J]. Computer Science, 2024, 51(4): 236-242.
[10] WANG Jiahao, YAN Hang, HU Xin, ZHAO Dexin. Study on Open Set Activity Recognition Technology Based on Wearable Devices [J]. Computer Science, 2024, 51(4): 291-298.
[11] ZHENG Cheng, SHI Jingwei, WEI Suhua, CHENG Jiaming. Dual Feature Adaptive Fusion Network Based on Dependency Type Pruning for Aspect-basedSentiment Analysis [J]. Computer Science, 2024, 51(3): 205-213.
[12] XU Maolong, JIANG Gaoxia, WANG Wenjian. Label Noise Filtering Framework Based on Outlier Detection [J]. Computer Science, 2024, 51(2): 87-99.
[13] LIU Xuanyu, ZHANG Shuai, HUO Shumin, SHANG Ke. Microservice Moving Target Defense Strategy Based on Adaptive Genetic Algorithm [J]. Computer Science, 2023, 50(9): 82-89.
[14] ZHOU Bo, JIANG Peifeng, DUAN Chang, LUO Yuetong. Study on Single Background Object Detection Oriented Improved-RetinaNet Model and Its Application [J]. Computer Science, 2023, 50(7): 137-142.
[15] DAI Xuesong, LI Xiaohong, ZHANG Jingjing, QI Meibin, LIU Yimin. Unsupervised Domain Adaptive Pedestrian Re-identification Based on Counterfactual AttentionLearning [J]. Computer Science, 2023, 50(7): 160-166.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.