Random Reselection Particle Swarm Optimization for Optimal Design of Solar Photovoltaic Modules

Abstract Renewable energy is becoming more popular due to environmental concerns about the previous energy source. Accurate solar photovoltaic system model parameters substantially impact the efficiency of solar energy conversion to electricity. In this matter, swarm and evolutionary optimization algorithms have been widely utilized in dealing with practical problems due to their more straightforward concepts, efficacy, flexibility, and easy-to-implement procedural frameworks. However, the nonlinearity and complexity of the photovoltaic parameter identification caused swarm and evolutionary optimizers to exhibit Immaturity in the obtained solutions. To deal with such concerns on immature convergence and imbalanced searching trends, in this paper, we proposed the PSOCS algorithm based on the core components of particle swarm optimization (PSO) and the strategy of random reselection of parasitic nests that appeared in the cuckoo search. The parameters of the single-diode model and the double-diode model are identified based on several experiments. Based on the comprehensive comparisons, results indicate that the developed PSOCS algorithm has higher convergence accuracy and better stability than the original PSO, the original cuckoo search, and other studied algorithms. The findings indicate that we suggest the PSOCS algorithm as an enhanced and efficient approach for dealing with parameter extraction of solar photovoltaic modules. We think this new variant of PSO can be employed as a tool for the optimal designing of photovoltaic systems.

[1]  Chandima Gomes,et al.  Parameters extraction of three diode photovoltaic models using boosted LSHADE algorithm and Newton Raphson method , 2021 .

[2]  Cuiping Wei,et al.  An Intuitionistic Fuzzy Stochastic Decision-Making Method Based on Case-Based Reasoning and Prospect Theory , 2017 .

[3]  Xuehua Zhao,et al.  SGOA: annealing-behaved grasshopper optimizer for global tasks , 2021, Engineering with Computers.

[4]  Jiangang Yao,et al.  A Novel Improved Cuckoo Search Algorithm for Parameter Estimation of Photovoltaic (PV) Models , 2018 .

[5]  Qiang Li,et al.  Monotone Iterative Technique for a Class of Slanted Cantilever Beam Equations , 2017 .

[6]  Di Wu,et al.  Binary-coded extremal optimization for the design of PID controllers , 2014, Neurocomputing.

[7]  Kun Zhou,et al.  Parallel Style-Aware Image Cloning for Artworks. , 2015, IEEE transactions on visualization and computer graphics.

[8]  H. Beyer,et al.  Mapping the performance of PV modules, effects of module type and data averaging , 2010 .

[9]  Zhongyi Hu,et al.  Uncertainty Modeling for Multicenter Autism Spectrum Disorder Classification Using Takagi–Sugeno–Kang Fuzzy Systems , 2022, IEEE Transactions on Cognitive and Developmental Systems.

[10]  A. Gandomi,et al.  The Colony Predation Algorithm , 2021, Journal of Bionic Engineering.

[11]  Shouming Zhong,et al.  Dissipative analysis for high speed train systems via looped-functional and relaxed condition methods , 2021 .

[12]  Xuehua Zhao,et al.  An improved grasshopper optimization algorithm with application to financial stress prediction , 2018, Applied Mathematical Modelling.

[13]  Huiling Chen,et al.  Ant colony optimization with horizontal and vertical crossover search: Fundamental visions for multi-threshold image segmentation , 2020, Expert Syst. Appl..

[14]  Jieming Ma,et al.  Comparative performance on photovoltaic model parameter identification via bio-inspired algorithms , 2016 .

[15]  Huang Wei,et al.  Extracting solar cell model parameters based on chaos particle swarm algorithm , 2011, 2011 International Conference on Electric Information and Control Engineering.

[16]  Huiling Chen,et al.  Horizontal and vertical crossover of Harris hawk optimizer with Nelder-Mead simplex for parameter estimation of photovoltaic models , 2020 .

[17]  Lei Xiao,et al.  Diagnosis of Alzheimer's disease based on Deeply-Fused Nets. , 2020, Combinatorial chemistry & high throughput screening.

[18]  Qing Li,et al.  Differentiable neural architecture search for optimal spatial/temporal brain function network decomposition , 2021, Medical Image Anal..

[19]  Xiaogang Jin,et al.  Parallel and efficient approximate nearest patch matching for image editing applications , 2018, Neurocomputing.

[20]  Xu Chen,et al.  Parameters identification of photovoltaic models using an improved JAYA optimization algorithm , 2017 .

[21]  Amir H. Gandomi,et al.  RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method , 2021, Expert Syst. Appl..

[22]  Zhijie Wen,et al.  Topology-preserving nonlinear shape registration on the shape manifold , 2020, Multimedia Tools and Applications.

[23]  Xuehua Zhao,et al.  Random learning gradient based optimization for efficient design of photovoltaic models , 2021 .

[24]  Hany M. Hasanien,et al.  Shuffled Frog Leaping Algorithm for Photovoltaic Model Identification , 2015, IEEE Transactions on Sustainable Energy.

[25]  Abderrezak Guessoum,et al.  A simple behavioural model for solar module electric characteristics based on the first order system step response for MPPT study and comparison , 2012 .

[26]  Yuping Li,et al.  Predict the Entrepreneurial Intention of Fresh Graduate Students Based on an Adaptive Support Vector Machine Framework , 2019, Mathematical Problems in Engineering.

[27]  Haodong Liu,et al.  Performance Prediction Using High-Order Differential Mathematical Morphology Gradient Spectrum Entropy and Extreme Learning Machine , 2020, IEEE Transactions on Instrumentation and Measurement.

[28]  Jian Weng,et al.  A Two-Layer Nonlinear Combination Method for Short-Term Wind Speed Prediction Based on ELM, ENN, and LSTM , 2019, IEEE Internet of Things Journal.

[29]  Catherine Soladie,et al.  Local Temporal Pattern and Data Augmentation for Spotting Micro-Expressions , 2023, IEEE Transactions on Affective Computing.

[30]  Yansen Su,et al.  Research on a Covert Communication Model Realized by Using Smart Contracts in Blockchain Environment , 2021, IEEE Systems Journal.

[31]  Jian Weng,et al.  Adaptive population extremal optimization-based PID neural network for multivariable nonlinear control systems , 2019, Swarm Evol. Comput..

[32]  Pan Duan,et al.  A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays , 2017 .

[33]  Xuehua Zhao,et al.  Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine , 2020, IEEE Access.

[34]  Zhennao Cai,et al.  A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices , 2017, PloS one.

[35]  Yong Fan,et al.  Four‐hundred gigahertz broadband multi‐branch waveguide coupler , 2020, IET Microwaves, Antennas & Propagation.

[36]  Huimin Zhao,et al.  A Novel Gate Resource Allocation Method Using Improved PSO-Based QEA , 2020, IEEE Transactions on Intelligent Transportation Systems.

[37]  Junjie Xu,et al.  An effective improved co-evolution ant colony optimisation algorithm with multi-strategies and its application , 2020, Int. J. Bio Inspired Comput..

[38]  Mohamed Abd Elaziz,et al.  A review on meta-heuristics methods for estimating parameters of solar cells , 2019, Journal of Power Sources.

[39]  Wenshu Li,et al.  Dynamic Gaussian bare-bones fruit fly optimizers with abandonment mechanism: method and analysis , 2020, Engineering with Computers.

[40]  Xiangbing Zhou,et al.  Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models , 2021, Complex..

[41]  Yanan Zhang,et al.  Boosted binary Harris hawks optimizer and feature selection , 2020, Engineering with Computers.

[42]  Saad Mekhilef,et al.  Parameter extraction of solar photovoltaic modules using penalty-based differential evolution , 2012 .

[43]  J. Appelbaum,et al.  Parameters extraction of solar cells – A comparative examination of three methods , 2014 .

[44]  S. Zhong,et al.  Dissipative Sampled-Data Control for High-Speed Train Systems With Quantized Measurements , 2021 .

[45]  Mingjing Wang,et al.  Modified Whale Optimization Algorithm for Solar Cell and PV Module Parameter Identification , 2021, Complex..

[46]  Jon Atli Benediktsson,et al.  Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning , 2019, 1912.01240.

[47]  N. Rajasekar,et al.  Bacterial Foraging Algorithm based solar PV parameter estimation , 2013 .

[48]  Jing Liang,et al.  Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models , 2018, Applied Energy.

[49]  Jun Li,et al.  Grey wolf optimization evolving kernel extreme learning machine: Application to bankruptcy prediction , 2017, Eng. Appl. Artif. Intell..

[50]  Fuh-Der Chou,et al.  A scatter simulated annealing algorithm for the bi-objective scheduling problem for the wet station of semiconductor manufacturing , 2018, Comput. Ind. Eng..

[51]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[52]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[53]  Weijie Mao,et al.  BACKBONE GUIDED EXTREMAL OPTIMIZATION FOR THE HARD MAXIMUM SATISFIABILITY PROBLEM , 2012 .

[54]  Xuehua Zhao,et al.  Delayed dynamic step shuffling frog-leaping algorithm for optimal design of photovoltaic models , 2021 .

[55]  Amir H. Gandomi,et al.  Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts , 2021, Expert Syst. Appl..

[56]  Huiling Chen,et al.  Chaotic multi-swarm whale optimizer boosted support vector machine for medical diagnosis , 2020, Appl. Soft Comput..

[57]  J. Phillips,et al.  A comparative study of extraction methods for solar cell model parameters , 1986 .

[58]  Feiping Nie,et al.  Supervised Feature Selection With Orthogonal Regression and Feature Weighting , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[59]  Jianhua Gu,et al.  Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy , 2019, Expert Syst. Appl..

[60]  Ying Chen,et al.  Towards augmented kernel extreme learning models for bankruptcy prediction: Algorithmic behavior and comprehensive analysis , 2020, Neurocomputing.

[61]  Hong Zhu,et al.  New study on fixed-time synchronization control of delayed inertial memristive neural networks , 2021, Appl. Math. Comput..

[62]  Long Wang,et al.  A Fast Abnormal Data Cleaning Algorithm for Performance Evaluation of Wind Turbine , 2021, IEEE Transactions on Instrumentation and Measurement.

[63]  Huiling Chen,et al.  Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy , 2020, Knowl. Based Syst..

[64]  Mingjing Wang,et al.  Orthogonal Nelder-Mead moth flame method for parameters identification of photovoltaic modules , 2020 .

[65]  Huiling Chen,et al.  Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review , 2021, Renewable and Sustainable Energy Reviews.

[66]  Xiaoqin Zhang,et al.  Pyramid Channel-based Feature Attention Network for image dehazing , 2020, Comput. Vis. Image Underst..

[67]  Prudence W. H. Wong,et al.  Parameter Estimation of Photovoltaic Models via Cuckoo Search , 2013, J. Appl. Math..

[68]  Kusum Deep,et al.  Harmonized salp chain-built optimization , 2019, Engineering with Computers.

[69]  A. K. Al-Othman,et al.  Simulated Annealing algorithm for photovoltaic parameters identification , 2012 .

[70]  Huimin Zhao,et al.  An Improved Quantum-Inspired Differential Evolution Algorithm for Deep Belief Network , 2020, IEEE Transactions on Instrumentation and Measurement.

[71]  Richard Binns,et al.  Cascaded Sagnac Loops Embedded With Two Polarization Maintaining Photonic Crystal Fibers for Highly Sensitive Strain Measurement , 2021, IEEE Transactions on Instrumentation and Measurement.

[72]  Li Zhao,et al.  Haze concentration adaptive network for image dehazing , 2021, Neurocomputing.

[73]  Ying Chen,et al.  Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection , 2020, Knowl. Based Syst..

[74]  Shihui Ying,et al.  Projective parameter transfer based sparse multiple empirical kernel learning Machine for diagnosis of brain disease , 2020, Neurocomputing.

[75]  Huaguo Liang,et al.  Architecture of Cobweb-Based Redundant TSV for Clustered Faults , 2016, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[76]  Hong Zhu,et al.  Novel Finite-Time Reliable Control Design for Memristor-Based Inertial Neural Networks With Mixed Time-Varying Delays , 2021, IEEE Transactions on Circuits and Systems I: Regular Papers.

[77]  Kaibo Shi,et al.  Robust H∞ control for uncertain delayed T-S fuzzy systems with stochastic packet dropouts , 2020, Appl. Math. Comput..

[78]  Dayou Liu,et al.  Evolving support vector machines using fruit fly optimization for medical data classification , 2016, Knowl. Based Syst..

[79]  Xuehua Zhao,et al.  Evaluation of constraint in photovoltaic models by exploiting an enhanced ant lion optimizer , 2020 .

[80]  Yong Fan,et al.  A Novel 220-GHz GaN Diode On-Chip Tripler With High Driven Power , 2019, IEEE Electron Device Letters.

[81]  Marcelo Gradella Villalva,et al.  Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays , 2009, IEEE Transactions on Power Electronics.

[82]  Bhaskar Nautiyal,et al.  Improved Salp Swarm Algorithm with mutation schemes for solving global optimization and engineering problems , 2021, Engineering with Computers.

[83]  Li Zhao,et al.  Self-filtering image dehazing with self-supporting module , 2021, Neurocomputing.

[84]  J. Jervase,et al.  Solar cell parameter extraction using genetic algorithms , 2001 .

[85]  Dacheng Tao,et al.  Top-k Feature Selection Framework Using Robust 0–1 Integer Programming , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[86]  Qiang Li,et al.  An Enhanced Grey Wolf Optimization Based Feature Selection Wrapped Kernel Extreme Learning Machine for Medical Diagnosis , 2017, Comput. Math. Methods Medicine.

[87]  Wenxiang Zhao,et al.  Parameters identification of solar cell models using generalized oppositional teaching learning based optimization , 2016 .

[88]  Guoqiang Zeng,et al.  Modified extremal optimization for the hard maximum satisfiability problem , 2011, Journal of Zhejiang University SCIENCE C.

[89]  Zhong-qiang Wu,et al.  Parameter identification of photovoltaic cell model based on improved ant lion optimizer , 2017 .

[90]  Rabeh Abbassi,et al.  Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach , 2020, Energy.

[91]  Xu Chen,et al.  Hybridizing cuckoo search algorithm with biogeography-based optimization for estimating photovoltaic model parameters , 2019, Solar Energy.

[92]  Zhang Zhijie,et al.  A Covert Communication Method Using Special Bitcoin Addresses Generated by Vanitygen , 2020, Computers, Materials & Continua.

[93]  Xuehua Zhao,et al.  Chaotic oppositional sine–cosine method for solving global optimization problems , 2020, Engineering with Computers.

[94]  Yansen Su,et al.  Resource allocation and trust computing for blockchain-enabled edge computing system , 2021, Comput. Secur..

[95]  Zhiyong Feng,et al.  Value Entropy: A Systematic Evaluation Model of Service Ecosystem Evolution , 2022, IEEE Transactions on Services Computing.

[96]  A. Ortiz-Conde,et al.  New method to extract the model parameters of solar cells from the explicit analytic solutions of their illuminated I–V characteristics , 2006 .

[97]  Guijian Xiao,et al.  Prediction and experimental research of abrasive belt grinding residual stress for titanium alloy based on analytical method , 2021, The International Journal of Advanced Manufacturing Technology.

[98]  J. Dreher,et al.  Prediction of trust propensity from intrinsic brain morphology and functional connectome , 2020, Human brain mapping.

[99]  Yan Wei,et al.  Predicting Entrepreneurial Intention of Students: An Extreme Learning Machine With Gaussian Barebone Harris Hawks Optimizer , 2020, IEEE Access.

[100]  Huiling Chen,et al.  A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features , 2019, BMC Bioinformatics.

[101]  Qian Zhang,et al.  An efficient chaotic mutative moth-flame-inspired optimizer for global optimization tasks , 2019, Expert Syst. Appl..

[102]  Hui Huang,et al.  Toward an optimal kernel extreme learning machine using a chaotic moth-flame optimization strategy with applications in medical diagnoses , 2017, Neurocomputing.

[103]  Tong Liu,et al.  A fast approach for detection of erythemato-squamous diseases based on extreme learning machine with maximum relevance minimum redundancy feature selection , 2015, Int. J. Syst. Sci..

[104]  Rahim Ali Abbaspour,et al.  Efficient boosted grey wolf optimizers for global search and kernel extreme learning machine training , 2019, Appl. Soft Comput..

[105]  Shouming Zhong,et al.  Fuzzy quantized sampled-data control for extended dissipative analysis of T-S fuzzy system and its application to WPGSs , 2020, J. Frankl. Inst..

[106]  Xuehua Zhao,et al.  Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts , 2020 .

[107]  Xu Cai,et al.  Crossing Thyristor Branches-Based Hybrid Modular Multilevel Converters for DC Line Faults , 2021, IEEE Transactions on Industrial Electronics.

[108]  Huiling Chen,et al.  Predicting Intentions of Students for Master Programs Using a Chaos-Induced Sine Cosine-Based Fuzzy K-Nearest Neighbor Classifier , 2019, IEEE Access.

[109]  A. R. Jordehi.  Enhanced leader particle swarm optimisation (ELPSO): An efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules , 2018 .

[110]  Huiling Chen,et al.  Levy-based antlion-inspired optimizers with orthogonal learning scheme , 2020, Engineering with Computers.

[111]  Rabeh Abbassi,et al.  An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models , 2019, Energy Conversion and Management.

[112]  Changcheng Huang,et al.  Orthogonally adapted Harris hawks optimization for parameter estimation of photovoltaic models , 2020 .

[113]  Daoliang Li,et al.  Feature selection based on improved ant colony optimization for online detection of foreign fiber in cotton , 2014, Appl. Soft Comput..

[114]  Ying Huang,et al.  Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients , 2019, Comput. Biol. Chem..

[115]  Hamza Turabieh,et al.  Laplacian Nelder-Mead spherical evolution for parameter estimation of photovoltaic models , 2021 .

[116]  Xiao-Zhi Gao,et al.  MPPCEDE: Multi-population parallel co-evolutionary differential evolution for parameter optimization , 2021 .

[117]  Xuehua Zhao,et al.  Evolutionary shuffled frog leaping with memory pool for parameter optimization , 2021 .

[118]  Xiankun Lin,et al.  Parameters identification of photovoltaic models using niche-based particle swarm optimization in parallel computing architecture , 2020 .

[119]  Guowei Cai,et al.  An integrated control algorithm of power distribution for islanded microgrid based on improved virtual synchronous generator , 2021, IET Renewable Power Generation.

[120]  Xiao Xue,et al.  Social Learning Evolution (SLE): Computational Experiment-Based Modeling Framework of Social Manufacturing , 2019, IEEE Transactions on Industrial Informatics.

[121]  Huiling Chen,et al.  A multi-strategy enhanced salp swarm algorithm for global optimization , 2020, Engineering with Computers.

[122]  Xuejiao Zhao,et al.  Matching Model of Energy Supply and Demand of the Integrated Energy System in Coastal Areas , 2020, Journal of Coastal Research.

[123]  Lihua You,et al.  Semantic portrait color transfer with internet images , 2015, Multimedia Tools and Applications.

[124]  Gonzalo Pajares,et al.  Parameter identification of solar cells using artificial bee colony optimization , 2014 .

[125]  Binbin Yu.  Urban spatial structure and total-factor energy efficiency in Chinese provinces , 2021, Ecological Indicators.

[126]  Alireza Rezazadeh,et al.  Parameter identification for solar cell models using harmony search-based algorithms , 2012 .

[127]  Hossam Faris,et al.  Harris hawks optimization: Algorithm and applications , 2019, Future Gener. Comput. Syst..

[128]  Huiling Chen,et al.  Boosted mutation-based Harris hawks optimizer for parameters identification of single-diode solar cell models , 2020 .

[129]  Anis Sakly,et al.  Particle swarm optimisation with adaptive mutation strategy for photovoltaic solar cell/module parameter extraction , 2018, Energy Conversion and Management.

[130]  Ali Asghar Heidari,et al.  Boosting Slime Mould Algorithm for Parameter Identification of Photovoltaic Models , 2021 .

[131]  Meiying Ye,et al.  Parameter extraction of solar cells using particle swarm optimization , 2009 .

[132]  Xiaolan Fu,et al.  MESNet: A Convolutional Neural Network for Spotting Multi-Scale Micro-Expression Intervals in Long Videos , 2021, IEEE Transactions on Image Processing.

[133]  Liming Zhang,et al.  Parallel LSTM-Based Regional Integrated Energy System Multienergy Source-Load Information Interactive Energy Prediction , 2019, Complex..

[134]  Chengye Li,et al.  Gaussian mutational chaotic fruit fly-built optimization and feature selection , 2020, Expert Syst. Appl..

[135]  Guoqiang Zeng,et al.  Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization , 2015, Neurocomputing.

[136]  Arabi Keshk,et al.  A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique , 2021, IEEE Access.

[137]  Ahmad Rezaee Jordehi,et al.  Time varying acceleration coefficients particle swarm optimisation (TVACPSO): A new optimisation algorithm for estimating parameters of PV cells and modules , 2016 .

[138]  Daoliang Li,et al.  A two-stage feature selection method with its application , 2015, Comput. Electr. Eng..

[139]  Fuh-Der Chou,et al.  A modified particle swarm optimization algorithm for a batch-processing machine scheduling problem with arbitrary release times and non-identical job sizes , 2018, Comput. Ind. Eng..

[140]  Xuehua Zhao,et al.  Dimension decided Harris hawks optimization with Gaussian mutation: Balance analysis and diversity patterns , 2021, Knowl. Based Syst..

[141]  Xiaohong Guan,et al.  Risk-Averse Storage Planning for Improving RES Hosting Capacity Under Uncertain Siting Choices , 2021, IEEE Transactions on Sustainable Energy.

[142]  Katarzyna Musial,et al.  A Scalable Redefined Stochastic Blockmodel , 2021, ACM Trans. Knowl. Discov. Data.

[143]  Ming Xu,et al.  A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models , 2020, Energy Conversion and Management.

[144]  Hui Huang,et al.  Developing a new intelligent system for the diagnosis of tuberculous pleural effusion , 2018, Comput. Methods Programs Biomed..

[145]  T. Easwarakhanthan,et al.  Nonlinear Minimization Algorithm for Determining the Solar Cell Parameters with Microcomputers , 1986 .

[146]  Huiling Chen,et al.  Slime mould algorithm: A new method for stochastic optimization , 2020, Future Gener. Comput. Syst..

[147]  Shaocheng Qu,et al.  Design and Implementation of a Fast Sliding-Mode Speed Controller With Disturbance Compensation for SPMSM System , 2021, IEEE Transactions on Transportation Electrification.

[148]  Wei Li,et al.  Robust hand tracking via novel multi-cue integration , 2015, Neurocomputing.

[149]  Wu Deng,et al.  An effective improved co-evolution ant colony optimisation algorithm with multi-strategies and its application , 2020, Int. J. Bio Inspired Comput..

[150]  D. Tao,et al.  Adaptive Data Structure Regularized Multiclass Discriminative Feature Selection , 2021, IEEE Transactions on Neural Networks and Learning Systems.

[151]  Xu Chen,et al.  An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models , 2019, Energy Conversion and Management.