A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

“…To address these challenges, this paper introduces a hybrid algorithm that integrates an improved salp swarm algorithm (SSA) with the perturb and observe (P&O) method. …”
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Hybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions by Mohd Nasrul Izzani Jamaludin, Mohammad Faridun Naim Tajuddin, Tarek Younis, Sudhakar Babu Thanikanti, Mohammad Khishe

“…This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques. …”
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Comparative Study of Genetic Algorithms and Particle Swarm Optimization for Flexible Power Point Tracking in Photovoltaic Systems under Partial Shading by Ouatman Hamid, Boutammachte Nour-Eddine

“…This study conducts a comparative analysis of Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) for Flexible Power Point Tracking (FPPT) in photovoltaic (PV) systems. …”
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Discrete multi-objective optimization of particle swarm optimizer algorithm for multi-agents collaborative planning by Xiao-bo SHI, Yin ZHANG, Shan ZHAO, Deng-ming XIAO

“…Although multiple mobile agents(MA)collaboration can quickly and efficiently complete data aggregation in wireless sensor network,the MA carrying data packages extensively increase along with a raise in the number of data source nodes accessed by MA,which causes unbalanced energy load of sensor nodes,high energy consumption of partial source nodes,and shortened lifetime of networks.The existing related works mainly focus on the objective of decreasing total energy consumption of multiple MA,without considering that rapidly energy consumption of partial source nodes has a negative effect on networks lifetime.Therefore,discrete multi-objective optimization of particle swarm algorithm was proposed,which used the total network energy consumption and mobile agent load balancing as fitness function for the approximate optimal itinerary plan in multiple mobile agent collaboration.Furthermore,the simulation result of the proposed algorithm is better than the similar algorithm in total energy consumption and network lifetime.…”
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MPPT Efficiency in PV Arrays under Partial Shading Conditions:A Comparative Analysis of PSO and P&O Algorithms by Rachid Bennia, Cherif Larbes, Faiza Belhachat

“…This investigation presents a comparative analysis of two established algorithms: Particle Swarm Optimization (PSO) and Perturb and Observe (P&O), evaluating their respective capabilities in GMPP identification. …”
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Hybrid precoding method for millimeter-wave massive MIMO systems based on IAFS algorithm by Haoyi CHEN, Guangqiu LI, Hui LI

Subjects: “…improved artificial fish swarm algorithm…”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

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Global MPPT optimization for partially shaded photovoltaic systems by T. Nagadurga, V. Dhana Raju, Abdulwasa Bakr Barnawi, Javed Khan Bhutto, Abdul Razak, Anteneh Wogasso Wodajo

“…The formulation and resolution of a single-objective non-linear optimization problem are carried out, considering different operational scenarios. Recent heuristic algorithms, including Particle Swarm Optimization (PSO), Cat Swarm Optimization (CSO), Teaching Learning Based Optimization (TLBO), Grey Wolf Optimization (GWO) and Chimp Optimization algorithm (ChOA) are employed to address the complexities associated with maximizing power output under partial shading conditions in solar PV systems. …”
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The Application of Compound Control Algorithm in Photovoltaic System MPPT by WANG Shenghui, LI Yilun, ZHENG Hong, GAO Shan

“…Aiming at the problem that the output array exhibits multipeak characteristics when the PV array is partially shaded or unevenly illuminated, the traditional singlepeak MPPT algorithm is difficult to track the maximum power point A hybrid algorithm is proposed to improve the particle swarm combined with the sliding mode search Firstly, the probability judgment criterion of improved simulated annealing algorithm is introduced into the standard particle swarm optimization algorithm; the law of inertia weight change is improved; the disturbance parameter is added to the learning factor Secondly, using the sliding mode extreme value search algorithm, the suspected optimal value obtained by the particle swarm optimization algorithm is continuously optimized, and finally the maximum power point is found The simulation results show that the composite control algorithm can track the maximum power point quickly and accurately under different shadow conditions, and avoid the system falling into the local optimum value…”
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A Comparison of Heuristic Algorithms for Solving the Traveling Salesman Problem by Younes Khdeir, Ahmed Awad

“…This paper presents a comparison between four popular algorithms: steepest ascent hill climbing, simulated annealing, genetic algorithm with partially matched crossover, and Particle Swarm Optimization (PSO). …”
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A Hybrid P&O-Fuzzy-Based Maximum Power Point Tracking (MPPT) Algorithm for Photovoltaic Systems Under Partial Shading Conditions by Hamed Karimi, Alireza Siadatan, Afshin Rezaei-Zare

“…Most MPPT algorithms do not perform well during partial shadow conditions, as they can become trapped in local maxima and fail to identify the absolute Global Maximum Power Point (GMP). …”
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Photovoltaic energy harvesting booster under partially shaded conditions using MPPT based sand cat swarm optimizer by Moch Rafi Damas Abdilla, Novie Ayub Windarko, Bambang Sumantri

“…The suggested SCSO performance is evaluated under a variety of weather situations, including both instances of partially shaded and uniform irradiance. The SCSO results are juxtaposed with other existing bio-inspired algorithms, such as grey wolf optimization (GWO), particle swarm optimization (PSO), and tunicate swarm algorithm (TSA). …”
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Fault localization for automatic train operation based on the adaptive error locating array algorithm by Yanpeng Zhang, Yuxiang Cao

“…Then the Partial Variable Intensity Covering Array (PVICA) algorithm is used to generate the initial set of test cases, and the cases are executed sequentially. …”
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Asset management using an extended Markowitz theorem by Paria Karimi

“…The resulted model is an NP-Hard problem and the proposed study uses two metaheuristics, namely genetic algorithm (GA) and particle swarm optimization (PSO) to find efficient solutions. …”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…To accomplish that, the CCPOA-HDLM method comprises distinct processes such as min-max normalization, improved Salp swarm algorithm (ISSA)-based feature selection, Multi-Channel Convolutional Neural Network - Recurrent Neural Network (MCNN-RNN)-based cybersecurity detection, and crested porcupine optimizer (CPO)-based parameter selection process. …”
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Improved marine predator MPPT algorithm for photovoltaic systems in partial shading conditions by Hanbo Zheng, Qi Du, Shuqin Mo, Tuanfa Qin, Shusheng Wang, Zhe Li

“…To optimize PV array output efficiency under PS conditions, this paper investigates a MPPT algorithm for PV arrays in partial shading environments. …”
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Comparative Evaluation of Traditional and Advanced Algorithms for Photovoltaic Systems in Partial Shading Conditions by Robert Sørensen, Lucian Mihet-Popa

“…The optimization of photovoltaic (PV) systems is vital for enhancing efficiency and economic viability, especially under Partial Shading Conditions (PSCs). This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). …”
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RETRACTED ARTICLE: Intelligent power management based on multi-objective cost function for plug-in biogas hybrid vehicles under uncertain driving conditions by Sameh Abd-Elhaleem, Walaa Shoeib, Abdel Azim Sobaih

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Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms by Sawsan Akram Hassan, Mahir M. Hason, Ammar N. Hanoon, Ali A. Abdulhameed

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An Adaptive Hybrid Chicken Swarm-Particle Swarm Optimization Algorithm by XIAO Yuhe, LI Maojun, QI Zhan, LIU Fu

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