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Optimal Design Method of a Hybrid CSP-PV Plant Based on Genetic Algorithm Considering the Operation Strategy
Published 2018-01-01“…In this paper, the operation strategy of the CSP-PV system is proposed for parabolic trough CSP system and PV system which are now commercially operated. Genetic algorithm is used to optimize the design of the system and calculate PV-installed capacity, battery capacity, and storage capacity of CSP system, making the system to achieve the lowest cost of electricity generation. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition
Published 2024-12-01“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid
Published 2025-05-01“…EMS is a control system integrated within MGs for managing the operations of these DGs effectively to fulfill a power balance between power production and load demand in the most optimal way, especially in island MGs. In this paper, an EMS based on Multiple Adaptive Neuro-Fuzzy Inference System optimized by Genetic Algorithm (MANFIS-GA) is proposed for PV/Wind/Diesel Generator/Battery (PWDB) island MG system, to optimize the output power of diesel generator, manage charging-discharging operation of MG Battery Storage keeping its State of Charge (SOC) in acceptable limits, and improve the MG system reliability and stability by mitigating the effects of sudden changes in the electrical loading and Renewable energy sources (RES) Power. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction
Published 2024-04-01“…Feature selection is often used by some researchers to overcome these problems, because these methods have an important function in the process of reducing data dimensions and eliminating uncorrelated attributes that can cause noisy. Naive Bayes algorithm is used to support the process of determining the most optimal class. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization
Published 2025-08-01“…Abstract Multi-access edge computing (MEC) addresses the constraints of limited computing resources and battery-limited devices by deploying computing resources at the network edge. However, most existing works on task offloading focus on single optimization objectives or simple tasks, neglecting the complexity of task types and diverse requirements in real-world applications. …”
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229
Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence
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IoT driven healthcare monitoring with evolutionary optimization and game theory
Published 2025-04-01“…As most of the existing approaches face challenges in establishing real-time connectivity, optimizing decision-making processes, and minimizing latency in Internet of Things (IoT)-based healthcare applications the limitations needs to be addressed. …”
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A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization
Published 2025-04-01“…A modified Grey Wolf Optimization algorithm with three significant adjustments improves feature selection and redundancy removal over the previous approach. …”
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Optimal ecological restoration strategy development based on value-cost trade-offs
Published 2025-04-01“…In addition, we searched for Pareto-optimal solutions using the nondominated sorting genetic algorithm II (NSGA-II) to balance the trade-offs between different objectives. …”
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Optimizing laser powder bed fusion parameters for enhanced hardness of Ti6Al4V alloys: A comparative analysis of metaheuristic algorithms for process parameter optimization
Published 2025-04-01“…Given its simplicity alongside its accuracy and robust performance, the JAYA algorithm proves the most appropriate method for LPBF parameter optimization. …”
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Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks
Published 2025-05-01“…The methodology consists of three key phases: (1) Data preprocessing, where missing values are handled using the multiple imputations by chain equation (MICE) technique and feature scaling is applied using standard and min-max scalers; (2) Feature selection, where the FFXO algorithm reduces feature dimensionality to enhance classification efficiency; and (3) Lung tumor classification, utilizing Bi-GAN to improve predictive accuracy. …”
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Beyond boundaries: AI-optimized global landslide susceptibility mapping
Published 2025-12-01“…This study addresses these gaps by developing an optimized framework using support vector regression (SVR) enhanced with meta-heuristic algorithms (grey wolf optimizer [GWO] and bat algorithm) to refine model hyper-parameters. …”
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A novel feature selection algorithm using decomposition based multi-objective guided honey badger algorithm (MO-GHBA) and NSGA-III
Published 2023-04-01“…In most of the MOEAs based feature selection algorithms, more optimal solutions are obtained around the Pareto front's center because of the deficiency in selection features. …”
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Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks
Published 2025-09-01“…This optimization enhances the network coverage, data acquisition efficiency, and energy conservation, ultimately prolonging the network lifetime and improving overall system reliability. …”
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A Study on the Design of a New Three-Dimensional Seismic Isolation Bearing Based on an Improved Genetic Algorithm for Bridge Engineering
Published 2024-10-01“…However, passive seismic isolation devices, due to their non-adjustable performance parameters, struggle to achieve effective seismic isolation across a wide frequency range of 0 Hz to 20 Hz in response to random and varying seismic loads. (2) Methods: The sensitivity of the design parameters of the seismic isolation bearing was analyzed using the optimization center gradient method, and an improved genetic algorithm was employed to quickly optimize and obtain the optimal design parameters. (3) Results: The effectiveness of the three-dimensional seismic isolation bearing was validated through experiments. (4) Conclusions: The multi-factor sensitivity analysis approach used in this study for designing novel isolation bearings is applicable not only to seismic design in bridges but also serves as a reference for parameter design in isolation bearings requiring medium to high precision in seismic performance.…”
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Mathematical Modeling of Cyberattack Defense Mechanism Using Hybrid Transfer Learning With Snow Ablation Optimization Algorithm in Critical Infrastructures
Published 2025-01-01“…In addition, the snow ablation optimization (SAO) algorithm can be exploited for the optimum choice of feature subsets. …”
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