Optimization of the heat recovery performance of enhanced geothermal system based on PSO-GA-BP neural networks and analytic hierarchy process by Ling Zhou, Jingchao Sun, Yanjun Zhang, Yunjuan Chen, Honglei Lei

“…Based on the numerical simulation data, optimized Back-Propagation Neural Network (BPNN) prediction models combining the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) were developed to investigate the impact of various factors on the heat recovery performance of a three-horizontal-well EGS in the Zhacang geothermal field. …”
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Interactive optimization scheduling method for distribution network and charging stations based on fuzzy logic and multi-strategy serial implementation mechanism by Ping Dong, Kunming Sui, Mingbo Liu, Run He, Shiqi Liu, Wu Xie, Sai Zhang

“…Secondly, to avoid the shortage of response volume and ensure effective response volume, three scheduling strategies are designed, and a multi-strategy serial implementation mechanism is established, enabling the electric vehicle aggregator to dispatch electric vehicles according to the scheduling tasks of each period and adjust the scheduling strategy in real-time based on the response completion. Next, the PSO (Particle Swarm Optimization) algorithm is used to minimize the difference between the optimized total load and peak load control targets and the aggregator’s incentive cost, resulting in the optimized charging power of each electric vehicle and the corresponding incentive price. …”
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Priority-Aware SDN Orchestration for Surgical IoMT: A Joint Optimization of Hit Ratio and Latency With Dynamic Resource Reallocation by Yalda Safaei, Pouria Arefijamal, Mahdi Siamaki, Bardia Safaei

“…Comparative simulations against Random, Particle Swarm Optimization (PSO), Simulated Annealing (SA), and a Deep Reinforcement Learning (DRL) agent as baselines demonstrate PASO’s substantial effectiveness. …”
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Performance Enhancement of Gulf of El Zayt Wind Farm in Egypt Using a Novel Optimized Seconded Sliding Mode Control by Mohamed Ebeed, Nagwa Elbadry, Khairy Sayed, Ahmed Rashad, Sulaiman Z. Almutairi, Ahmed T. Hachemi, Emad A. Mohamed, Shazly A. Mohamed

“…The Slime Mould Algorithm (SMA) and the particle swarm optimization (PSO) methods are applied to assign the optimal gains of proposed OSSMC-PI controller. …”
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A Mixed Integer Linear Formulation and a Grouping League Championship Algorithm for a Multiperiod-Multitrip Order Picking System with Product Replenishment to Minimize Total Tardin... by Morteza Farhadi Sartangi, Ali Husseinzadeh Kashan, Hassan Haleh, Abolfazl Kazemi

“…A mixed integer linear programming formulation is proposed for this new problem. The model is optimally solved for small-size problems. For larger instances, grouping metaheuristic algorithms are proposed based on particle swarm optimization and the league championship algorithm that use group-based operators to generate reasonable batches of orders. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…Multi-Objective Particle Swarm Optimization (MOPSO) is employed to address the inner-stage issue. …”
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Hybrid geometry optimization to mitigate maximum temperature gradient in solid oxide fuel cells without lowering the net output performance by Hongkun Li, Tongyu Dai, Tiantian Hu, Weiqun Liu, Qiao Zhu, Dawei Dong

“…By performing multiple simulations with 48 groups of geometry parameters, we find that the wave-shape perturbed fluid structure with a height of 0.8 mm and a width of 4 mm can achieve the lowest maximum temperature gradient in the reaction zone. On the basis of the optimal perturbed fluid structure, the optimal anode diffusion layer thickness, cathode diffusion layer thickness and electrolyte layer thickness are identified based on particle swarm optimization (PSO) algorithm, which are 621.82 μm, 80 μm and 15.61 μm, respectively. …”
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FinSafeNet: securing digital transactions using optimized deep learning and multi-kernel PCA(MKPCA) with Nyström approximation by Ahmad Raza Khan, Shaik Shakeel Ahamad, Shailendra Mishra, Mohd Abdul Rahim Khan, Sunil Kumar Sharma, Abdullah AlEnizi, Osama Alfarraj, Majed Alowaidi, Manoj Kumar

“…FinSafeNet draws attention to the attack and reproductive phases of Hierarchical Particle Swarm Optimization (HPSO) feature selection technique simulating it in a battle for extreme time performance called the Improved Snow-Lion optimization Algorithm (I-SLOA). …”
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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

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A numerical framework for enhancing the seismic resilience of urban infrastructure in clayey basins using finite element modeling and AI optimization by Kaveh Dehghanian

“…The study considers the construction’s structural displacement, stress, and failure modes under seismic loading and optimizes retrofitting and soil stabilization strategies using genetic algorithms and particle swarm optimization. …”
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Optimized Spectral and Spatial Design of High-Uniformity and Energy-Efficient LED Lighting for Italian Lettuce Cultivation in Miniature Plant Factories by Zihan Wang, Haitong Huang, Mingming Shi, Yuheng Xiong, Jiang Wang, Yilin Wang, Jun Zou

“…To address spatial light heterogeneity, a particle swarm optimization (PSO) algorithm was employed to determine the optimal LED arrangement, which increased the photosynthetic photon flux density (PPFD) uniformity from 83% to 93%. …”
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New PSO-GWO-based model for enhancing power quality in electrical networks interconnected with photovoltaic sources by Mehdi Sanaei, Hamidreza Akbari, Zohreh Beheshtipour, Somayeh Mousavi

“…This research endeavors to elucidate how achieving a more refined power pattern in electric networks is attainable by considering the power quality of PV sources. A hybrid Particle Swarm Optimization-Gray Wolf Optimization (PSO-GWO) algorithm is proposed to obtain optimal solutions. …”
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Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

“…Binary particle swarm optimization plays a crucial role in hybrid feature selection; the purpose of this Algorithm is to obtain the suitable output with the least features. …”
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Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making by Zihan Sun, Jian Chen, Yang Chen, Wen Zhang, Tingting Zhang, Yicheng Zhang, Guangsheng Pan

“…Furthermore, an angle preference-based multi-objective particle swarm optimization algorithm is introduced to incorporate the preferences of decision-makers and yield flexible and tailored optimal sizing solutions. …”
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Optimized physics-informed neural networks for deciphering of external source pollutants in a swirling flow induced by a constant torsional motion by Shridhar M, Umair Khan, Rahul Makwana, Ankur Kulshreshta, N.B. Naduvinamani

“…The flow, heat and mass transport attributes are assessed using the Physics-informed neural network (PINN). This model is optimized by a hybrid genetic algorithm and particle swarm optimization to address the flow, heat and mass transport attributes via neural networks. …”
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Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach by Noorulden Basil, Hamzah M. Marhoon, Bayan Mahdi Sabbar, Abdullah Fadhil Mohammed, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohamad Sharaf, Amare Merfo Amsal, Mahrous Ahmed, Enas Ali, Sherif S. M. Ghoneim

“…The proposed algorithm combines the strengths of particle swarm optimization (PSO) and the ant lion optimizer (ALO), which are enhanced by the Eagle strategy to systematically fine-tune the FOPID controller parameters. …”
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Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

“…Furthermore, a parallel PSO-RF algorithm combining Particle Swarm Optimization (PSO) and Random Forest (RF) is designed to enhance classification performance and computational efficiency. …”
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Research on the Range of Stiffness Variation in a 2D Biomimetic Spinal Structure Based on Tensegrity Structures by Xiaobo Zhang, Zhongcai Pei, Zhiyong Tang

“…Ultimately, the PSO (Particle Swarm Optimization) algorithm is employed to identify the optimal combination of structural parameters for maximizing the stiffness ratio, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>K</mi></mrow><mrow><mi>θ</mi><mo>_</mo><mi>t</mi><mi>i</mi><mi>m</mi><mi>e</mi></mrow></msub></mrow></semantics></math></inline-formula>, of SBTDTS under different constraint conditions. …”
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Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…Therefore, in order to solve the AMT vibration monitoring problem and enhance the diagnostic efficiency, this study proposes an AMT fault diagnosis model based on particle swarm optimization (PSO) to optimize the parameters of wavelet packet transform (WPT) and support vector machine (SVM).The optimal vibration signal acquisition point is determined by finite element analysis to ensure high signal quality. …”
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Deployment scheme of RSU based on connection time in VANET by Zhengchao DING, Zhenchun WEI, Lin FENG

“…For the roadside unit (RSU) placement problem in vehicular Ad Hoc network (VANET),the deployment scheme of RSU based on connection time was proposed.The scheme find the optimal positions of RSU for maximizing the number of vehicles while ensuring a certain level of connection time under the limited number of RSU.The problem was modeled as a maximum coverage problem,and a binary particle swarm algorithm was designed to solve it.The simulation experiment was carried out with the real Beijing road network map and taxi GPS data.The simulation results show that the algorithm is convergent,stable and feasible.Compared with the greedy algorithm,the proposed scheme can provide continuous network service for more vehicles.…”
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