A Survey of Nature-Inspired Meta-Heuristic Algorithms in Network Alignment by Anagh Awal, Farsuram Pandit

“…It explores a wide range of nature-inspired algorithms, including genetic algorithms, particle swarm optimization, ant colony optimization, and simulated annealing. …”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…In this paper, a combination of Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) is proposed to optimize the Backpropagation Neural Network (BP) model (PSO-GWO-BP) and a pressure drop prediction model for the joint station export system is established using PSO-GWO-BP. …”
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Allocation of Interline Power Flow Controller-Based Congestion Management in Deregulated Power System by Muhammad Safdar Sial, Qinghua Fu, Talles Vianna Brugni

“…By examining the obtained results, the performance of the proposed algorithm is better than the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. It causes a further reduction in the generation cost, congestion costs, and power losses and improves the voltage profile. …”
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Damage Identification in Bars with a Wave Propagation Approach and a Hybrid Optimization Method by R.A. Tenenbaum, K.M. Fernandes, L.T. Stutz, A.J. Silva Neto

“…In the identification process, different optimization methods are investigated: the deterministic Levenberg-Marquardt; the stochastic Particle Swarm Optimization; and a hybrid technique combining the aforementioned methods. …”
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A Wideband and Polarization-Independent Metasurface Based on Phase Optimization for Monostatic and Bistatic Radar Cross Section Reduction by Jianxun Su, Yao Lu, Zengrui Li, Rongrong Zhang, Yaoqing (Lamar) Yang

“…Optimizing phase layout through particle swarm optimization (PSO) together with far field pattern prediction can produce a lot of scattering lobes, leading to a great reduction of bistatic RCS. …”
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Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion by Ying Chen, Yuanning Liu, Xiaodong Zhu, Fei He, Hongye Wang, Ning Deng

“…Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region’s weights and then weighted different subregions’ matching scores to generate the final decision. …”
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PAPR Reduction Using Fireworks Search Optimization Algorithm in MIMO-OFDM Systems by Lahcen Amhaimar, Saida Ahyoud, Ali Elyaakoubi, Abdelmoumen Kaabal, Kamal Attari, Adel Asselman

“…Moreover, it turns out from the results that the proposed PTS scheme-based FWA clearly outperforms the hottest and most important evolutionary algorithm in the literature like simulated annealing (SA), particle swarm optimization (PSO), and genetic algorithm (GA).…”
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A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution by Qing Xiong, Weihua Zhang, Tianwei Lu, Guiming Mei, Shulin Liang

“…Thirdly, the KPCFFs served as the input of Least Squares Support Vectors Machine (LSSVM) based on Particle Swarm Optimization (PSO) to assess rolling bearings’ fault position and damage severity. …”
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Deep Learning-Based Energy Consumption Prediction Model for Green Industrial Parks by Chaoan Lai, Yina Wang, Jianhua Zhu, Xuequan Zhou

“…These components are then predicted using a multi-factor LSTM model optimized by improved particle swarm optimization, with the results aggregated for the final forecast. …”
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani, Ruqayya Haider, Samir Brahim Belhaouari

“…All these developed algorithms have some merits and also demerits. Particle swarm optimization (PSO), firefly algorithm, ant colony optimization (ACO), and bat algorithm (BA) have gained much popularity and they have successfully tackled various test suites of benchmark functions and real-world problems. …”
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Shallow Foundation Settlement Quantification: Application of Hybridized Adaptive Neuro-Fuzzy Inference System Model by Mariamme Mohammed, Ahmad Sharafati, Nadhir Al-Ansari, Zaher Mundher Yaseen

“…This research emphasis on the implementation of newly developed machine learning models called hybridized Adaptive Neuro-Fuzzy Inference System (ANFIS) with Particle Swarm Optimization (PSO) algorithm, Ant Colony optimizer (ACO), Differential Evolution (DE), and Genetic Algorithm (GA) as efficient approaches to predict settlement of shallow foundation over cohesion soil properties. …”
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Performance evaluation of an optimized simplified nonlinear active disturbance rejection controller for rotor current control of DFIG-based wind energy system by Ahmed Sobhy, Medhat Hegazy Elfar, Ahmed Refaat, Mahmoud Fawzi

“…To address these challenges, an optimized simplified nonlinear active disturbance rejection (SNADR) control strategy, enhanced through the Particle Swarm Optimization (PSO) algorithm for parameter tuning, is proposed. …”
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Modeling and Solving Multi-Objective Path Planning Problem for Cooperative Cable-Suspended Load Transportation Considering the Time Variable Risk by Amir Arslan Haghrah, Sehraneh Ghaemi, Mohammad Ali Badamchizadeh

“…In addition, we propose an improved hybrid fuzzy particle swarm optimization (PSO) and whale optimization algorithm (WOA) to solve the introduced path planning problem efficiently. …”
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Identification of Vibration Signal for Residual Pressure Utilization Hydraulic Unit Using MRFO-BP Neural Network by Qingjiao Cao, Liying Wang, Jiajie Zhang, Tengfei Guo, Xiyuan Liu

“…Compared with Particle Swarm Optimization-BP (PSO-BP) neural network, Bat Algorithm-BP (BA-BP) neural network, and BP neural network, the results show that the identification rate of each measuring point from the MRFO-BP neural network is greatly improved. …”
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Ship-Borne Phased Array Radar Using GA Based Adaptive α-β-γ Filter for Beamforming Compensation and Air Target Tracking by J. Mar, Chen-Chih Liu, M. B. Basnet

“…The genetic algorithm (GA) and the particle swarm optimization (PSO) methods are applied to estimate the gain parameters of adaptive α-β-γ filters, while achieving the optimum objective of minimum root mean square error (RMSE). …”
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Advanced machine learning approach with dynamic kernel weighting for accurate electrical load forecasting by C. Jeevakarunya, V. Manikandan

“…The first step in preparing the dataset is to perform preprocessing, which involves conducting correlation analysis, scaling, and normalization followed by initial hyperparameter tuning using the multiswarm Levy flight particle swarm optimization technique. Compared with traditional methods, EDW-MKSVR offers greater adaptability to shifting load patterns since it makes use of dynamic kernel weight modifications that are dependent on data attributes. …”
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Fault Diagnosis of Piezoelectric Sensor Patches for Vibration Control Based on Multifeature Fusion and Improved SVM by Tian-bing Ma, Zhou Qing, Du Fei, Liu Jian

“…In order to improve the accuracy of fault self-diagnosis of piezoelectric sensor patches, singular value decomposition (SVD) and Hilbert marginal spectrum method are proposed to extract multiple features of each IMF component and conduct feature fusion, and a support vector machine (SVM) based on particle swarm optimization (PSO) is designed for fault identification of different eigenvalues. …”
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Using crafted features and polar bear optimization algorithm for short-term electric load forecast system by Mansi Bhatnagar, Gregor Rozinaj, Radoslav Vargic

“…PBO was compared with commonly used optimization algorithms like particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Power Prioritization and Load Shedding in an Island with RESs Using ABC Algorithm by L. O. Mogaka, G. N. Nyakoe, M. J. Saulo

“…The results are then compared with those of Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and GA-PSO hybrid. Both generation and overload contingencies are considered on a standard IEEE 30-bus system on a MATLAB platform. …”
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Parameter Optimization Study of Gas Hydrate Reservoir Development Based on a Surrogate Model Assisted Particle Swarm Algorithm by Le Zhang, Xin Huang, Jiayuan He, Xueqi Cen, Yongge Liu

“…Firstly, an improved surrogate model assisted particle swarm optimization (PSO) algorithm was proposed in this paper. …”
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