Optimizing solar maximum power point tracking with adaptive PSO: A comparative analysis of inertia weight and acceleration coefficient strategies by Denesh Sooriamoorthy, Aaruththiran Manoharan, Siva Kumar Sivanesan, Soon Kian Lun, Alexander Chee Hon Cheong, Sathish Kumar Selva Perumal

“…Metaheuristic algorithms such as Particle Swarm Optimization (PSO) are explored extensively for MPPT applications. …”
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A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading by Mohammed Taha Kaaitan, Rashid Ali Fayadh, Zuhair S. AL-sagar, Salam J. Yaqoob, Mohit Bajaj, Mebratu Sintie Geremew

“…Performance evaluation against benchmark algorithms—Perturb & Observe (P&O), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—revealed that STOA consistently outperformed its counterparts. …”
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Enhanced MPP Tracking in Partial Shading Conditions for Solar PV Systems: A Metaheuristic Approach Utilizing Projectile Search Algorithm by Md Tahmid Hussain, Mohammed Shahabuddin, Liang-Yin Huang, Adil Sarwar, Mohammed Asim, Shafiq Ahmad, Hwa-Dong Liu, Mohd Tariq

“…To assess the performance of the proposed PSA-based approach, comparisons are made with Jaya, Cuckoo Search, Particle Swarm Optimization (PSO) and Perturb and Observe (P&O) algorithms. …”
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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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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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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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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

“…Therefore, achieving efficient maximum power point tracking (MPPT) in a photovoltaic (PV) system under PS is an important element in enhancing PV system efficiency. 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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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

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Task Offloading and Data Compression Collaboration Optimization for UAV Swarm-Enabled Mobile Edge Computing by Zhijuan Hu, Shuangyu Liu, Dongsheng Zhou, Chao Shen, Tingting Wang

“…To minimize the total energy and time cost of the system, we utilize Markov Decision Process (MDP) for modeling and construct a deep deterministic policy gradient offloading algorithm with a prioritized experience replay mechanism (PER-DDPG) to jointly optimize compression ratio, task offloading rate, resource allocation and swarm positioning. …”
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Fault localization for automatic train operation based on the adaptive error locating array algorithm by Yanpeng Zhang, Yuxiang Cao

“…These cases are designed to locate the MFS more easily in the given parameter range using the Adaptive Particle Swarm Optimization (APSO) algorithm. Finally, the MFS is determined. …”
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Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques by S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, R. Gandhi Raj, K. Kalaivani, N. Kopperundevi, M. Chinnadurai, M. Nuthal Srinivasan, L. Ramachandran

“…To select the best optimization model for MPPT under PSC, the nature-inspired dragonfly algorithm (DA), moth flame optimization algorithm (MFOA), grasshopper optimization algorithm (GOA), and salp swarm optimization algorithm (SSOA) are used in this work to evaluate the tracking efficiency (TE) of the solar PV systems. …”
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Enhanced Harmony Search Algorithm for Maximum Power Point Tracking Under Partial Shading in PV Systems by Geon Hee Lee, Zong Woo Geem, Jehyuk Won

“…The results show that the proposed algorithm outperforms conventional HS and particle swarm optimization algorithms in terms of the number of iterations and convergence time, while maintaining a similar level of accuracy.…”
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A modified particle swarm optimization-based adaptive maximum power point tracking approach for proton exchange membrane fuel cells by Bhukya Laxman, Ramesh Gugulothu, Surender Reddy Salkuti

“…In this paper, a Modified Particle Swarm Optimization (MPSO) method is proposed for maximum power point tracking (MPPT) to optimize the power output of Proton Exchange Membrane Fuel Cells (PEMFCs). …”
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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…To overcome these issues, this paper introduces new Particle Swarm Optimization (PSO)-improved partial transmit sequence (PTS) and Selective Mapping (SLM) schemes that optimally choose phase factors with much lower search complexity. …”
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Complexity Reduction in the Use of Evolutionary Algorithms to Function Optimization: A Variable Reduction Strategy by Guohua Wu, Witold Pedrycz, Haifeng Li, Dishan Qiu, Manhao Ma, Jin Liu

“…Discovering and utilizing problem domain knowledge is a promising direction towards improving the efficiency of evolutionary algorithms (EAs) when solving optimization problems. …”
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Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete by Muhammad Izhar Shah, Shazim Ali Memon, Muhammad Sohaib Khan Niazi, Muhammad Nasir Amin, Fahid Aslam, Muhammad Faisal Javed

“…In this research, multiexpression programming (MEP) has been employed to model the compressive strength, splitting tensile strength, and flexural strength of waste sugarcane bagasse ash (SCBA) concrete. Particle swarm optimization (PSO) algorithm was used to fine-tune the hyperparameter of the proposed MEP. …”
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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar, Taha Selim Ustun, Chiranjit Sain, Ahmet Onen

“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”
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Battle Royale Optimization for Optimal Band Selection in Predicting Soil Nutrients Using Visible and Near-Infrared Reflectance Spectroscopy and PLSR Algorithm by Jagadeeswaran Ramasamy, Anand Raju, Kavitha Krishnasamy Ranganathan, Muthumanickam Dhanaraju, Backiyathu Saliha, Kumaraperumal Ramalingam, Sathishkumar Samiappan

“…In order to select optimum bands (wavelength) from the soil spectra, we have employed metaheuristic algorithms i.e., Particle Swarm Optimization (PSO), Moth–Flame optimization (MFO), Flower Pollination Optimization (FPO), and Battle Royale Optimization (BRO) algorithm. …”
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Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions by Oğuzhan Timur, Bayram Kaan Uzundağ

“…The classical Maximum Power Point Tracking (MPPT) algorithm fails to determine the global maximum operating point to prevent power losses under partial shading conditions. …”
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HYBRID GENETIC ALGORITHM VERSUS PSO FOR TRACKING THE MPP OF PV MODULE by Sabin POPESCU

“…This paper proposes a hybrid genetic algorithm (HGA) for tracking the maximum power point when multiple local maximum power points can be found and a comparison with a biological algorithm for tracking the maximum power point: Particle Swarm Optimization (PSO).…”
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