Search Results - (( model validation focus algorithm ) OR ( panel optimization swarm algorithm ))

Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…In this study, MATLAB models of a DRL-based MPPT algorithm were developed, tested, and compared to simulation based on two established MPPT algorithms-the Particle Swarm Optimization (PSO), and the Perturb and Observe (P&O). …”

Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

“…The MPPT method applied to track maximum power from PV panel is particle swarm optimization (PSO). Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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PARTICLE SWARM OPTIMIZATION MAXIMUM POWER POINT TRACKING FOR PARTIALLY SHADED SOLAR PV by Alvin, Ngu Tien Leong

“…This study proposes a particle swarm optimization (PSO) algorithm based on MPPT for the PGS to operate under PSC. …”
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Hybrid MPPT algorithm for mismatch photovoltaic panel application / Muhammad Iqbal Mohd Zakki by Mohd Zakki, Muhammad Iqbal

“…On the other hand, the implementation of conventional direct MPPT technique causes oscillation in MPP tracking due to the perturbative nature of the algorithms. Otherwise, the soft-computation MPPT methods by evolutionary algorithms such as Particle Swarm Optimization (PSO) algorithm require longer tracking time to prevent the false MPP tracking convergence. …”
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Comparative analysis of two-step GA-based PV array reconfiguration technique and other reconfiguration techniques by Muhammad Ajmal A., Ramachandaramurthy V.K., Naderipour A., Ekanayake J.B.

Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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ANT colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul affendy, Abdul Muthalif, Asan Gani, Walid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system by Roslan M.F., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Zuhdi A.W.M.

Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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NSGA-II and MOPSO Based Optimization for Sizing of Hybrid PV/ Wind / Battery Energy Storage System by Hlal, Mohamed Izdin, Ramachandaramurthya, Vigna K., Padmanaban, Sanjeevikumar, Kaboli, Hamid Reza, Pouryekta, Aref, Tuan Abdullah, Tuan Ab Rashid

“…The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. …”
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NSGA-II and MOPSO based optimization for sizing of hybrid PV / wind / battery energy storage system by Mohamad Izdin Hlal A., Ramachandaramurthya V.K., Sanjeevikumar Padmanaban B., Hamid Reza Kaboli C., Aref Pouryekta A., Tuan Ab Rashid Bin Tuan Abdullah D.

“…The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. …”

An intelligent maximum power point tracking algorithm for Photovoltaic System by Iman M.I., Roslan M.F., Ker P.J., Hannan M.A.

“…This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. …”

Design a photovoltaic system based on maximum power point tracking under partial shading by Ma’allin, Usama Abdullahi

“…The voltage and current of MSX60 PV module are subjected to various insolation conditions. The Particle Swarm Optimization (PSO) algorithm based MPPT has been implemented to track maximum power partial shading condition. …”
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Dynamic reconfiguration of large-scale PV plant using based on specified switching matrix and genetic algorithm to mitigate partial shading by Aidha Muhammad Ajmal

“…In the second stage, Genetic Algorithm (GA) is applied to optimize the output, via rearranging the columns in PV plants to find the optimal solution of reconfiguration. …”

Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

“…Lastly, a study of the industrial case was performed as a validation of the developed model and algorithm. An automotive company is selected, and the collected actual data is used for validation purposes. …”
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Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves by Feng L., Zhang J., Kiong T.S., Ding K., Amin N., Hamelmann F.U.

Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.] by Abdul Majid, M. M., Salleh, M. S., Abu Hashim, M. A., Ismail, N. H., Mansor, S., Abu Bakar, S. A.

“…The experimental data used for simulation model correlation and validation. New controller algorithm (SALC) was than developed in Matlab/Simulink and integrate with correlated vehicle plant model for handling performance validation against passive suspension and Skyhook. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

“…This study underscores the importance of combining machine learning techniques to improve prediction accuracy and provides a robust framework for advancing smORF discovery. While the focus was on comparing standalone and hybrid models, the study identifies opportunities for future benchmarking against external tools to further validate its contributions. …”
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A novel MPPT approach for photovoltaic system using Pelican optimization and high-gain DC–DC converter by Akter, Khadiza, Motakabber, S. M. A., Alam, A. H. M. Zahirul, Yusoff, Siti Hajar, Pachauri, Rupendra Kumar, Malik, Hasmat, Jadoun, Vinay Kumar

“…The performance of the POA is benchmarked against three other Metaheuristics MPPT techniques: Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO),Gray Wolf Optimization (GWO), and Cuckoo Search (CS). …”
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