Research on cooperative control strategy for high efficiency and energy saving in virtually coupled train sets based on two-layer optimization by JIANG Sidun, FENG Jianghua, ZHANG Zhengfang, SHI Ke, LUO Qinyang

“…The lower layer concentrates on energy-saving optimization, establishing an objective function for energy saving and utilizing a multi-objective particle swarm algorithm to optimize cruising curves. …”
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Optimized ensemble learning for non-destructive avocado ripeness classification by Panudech Tipauksorn, Prasert Luekhong, Minoru Okada, Jutturit Thongpron, Chokemongkol Nadee, Krisda Yingkayun

“…Five machine learning models Random Forest, Decision Tree, XGBoost, Gradient Boosting, and Gaussian Mixture Model were trained separately and then merged into an ensemble. Four algorithms were used to optimize the model weight distribution: Bayesian Optimisation, Differential Evolution, Particle Swarm Optimisation, and Grid Search. …”
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Optimizing Outdoor Micro-Space Design for Prolonged Activity Duration: A Study Integrating Rough Set Theory and the PSO-SVR Algorithm by Jingwen Tian, Zimo Chen, Lingling Yuan, Hongtao Zhou

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Optimizing LoRaWAN Gateway Placement in Urban Environments: A Hybrid PSO-DE Algorithm Validated via HTZ Simulations by Kanar Alaa Al-Sammak, Sama Hussein Al-Gburi, Ion Marghescu, Ana-Maria Claudia Drăgulinescu, Cristina Marghescu, Alexandru Martian, Nayef A. M. Alduais, Nawar Alaa Hussein Al-Sammak

“…This study investigates how to optimize the placement of LoRaWAN gateways by using a combination of Particle Swarm Optimization (PSO) and Differential Evolution (DE). …”
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Optimized deep neural network architectures for energy consumption and PV production forecasting by Eghbal Hosseini, Barzan Saeedpour, Mohsen Banaei, Razgar Ebrahimy

“…This paper introduces a novel hybrid optimization approach that integrates Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) to enhance the DNN architecture for more accurate energy forecasting. …”
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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. …”
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Adaptive hybrid optimization for integrated project scheduling and staffing problem with time/resource trade-offs by Muhai Hu, Yao Wang, Wendi Tian

“…To solve this problem, we introduce an adaptive hybrid algorithm combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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A cluster based routing for maximizing the lifetime of underwater wireless sensor network using gravitational search algorithm by Shyamsundar R, Harshavarthan M, Shankar Thangavelu

“…The proposed GSA has been compared with competitive meta-heuristic algorithms, including Particle Swarm Optimization, Whale Optimization Algorithm, and Moth Flame Optimizer.…”
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Optimization Design of Lazy-Wave Dynamic Cable Configuration Based on Machine Learning by Xudong Zhao, Qingfen Ma, Jingru Li, Zhongye Wu, Hui Lu, Yang Xiong

“…A high-fidelity surrogate model based on a backpropagation (BP) neural network was trained to accurately predict cable dynamic responses. Three optimization algorithms—Particle Swarm Optimization (PSO), Ivy Optimization (IVY), and Tornado Optimization (TOC)—were evaluated for their effectiveness in optimizing the arrangement of buoyancy and weight blocks. …”
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An optimized public opinion communication system in social media networks based on K-means cluster analysis by Mingchao Qi, JunQiang Zhao, Yan Feng

“…This study proposes a public opinion monitoring model that combines the K-means clustering algorithm with Particle Swarm Optimization (PSO) to enhance the accuracy and effectiveness of public opinion monitoring on social media. …”
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Research on path planning for mine rescue UAV based on improved Artificial Jellyfish Search algorithm by ZHENG Xuezhao, DIAO Chengze, CAI Guobin, WEN Hu, YANG Bo, HOU Zongxuan, MOU Haowei

“…UAV path planning simulation experiments showed that, when the obstacle ratio was 14.56%, compared with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, and JS algorithm, the IJS algorithm reduced the path planning time by 72.27%, 66.12%, and 70.87%, respectively; shortened the path length by 2.67%, 3.95%, and 1.36%, respectively; and reduced the number of turning points by 47.37%, 50%, and 28.57%, respectively. …”
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Multi-energy System Planning and Configuration Study for Low-Carbon Parks Based on Comprehensive Optimization Objectives by Yang WANG, Fei LU, Ji LI, Zhukui TAN, Zongyu SUN, Wei XU, Zihong SONG, Zhenpeng LIU

“…Firstly, based on the energy-demand fast prediction method for park and the composite energy system dynamic simulation platform, this paper proposed an optimal planning and configuration method for low-carbon park composite energy system, and established a hybrid optimization algorithm combining Hook-Jeff algorithm and particle swarm optimization. …”
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New Design of Smooth PSO-IPF Navigator With Kinematic Constraints by Mahsa Mohaghegh, Hedieh Jafarpourdavatgar, Samaneh-Alsadat Saeedinia

“…Smooth path planning is crucial for mobile robots to ensure stable and efficient navigation, as it minimizes jerky movements and enhances overall performance Achieving this requires smooth collision-free paths. Partial Swarm Optimization (PSO) and Potential Field (PF) are notable path-planning techniques, however, they may struggle to produce smooth paths due to their inherent algorithms, potentially leading to suboptimal robot motion and increased energy consumption. …”
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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

“…The MAPPO-H enables the CHs to decide cluster selection and moving position, while CMs utilize IPPO-M to cluster autonomously under the condition of certain partial channel distribution information (CDI). Adequate experimental evidence has confirmed that the HMDRL-UC algorithm proposed in this paper is not only capable of managing dynamic drone swarm scenarios in the presence of partial CDI, but also has a clear advantage over the other existing three algorithms in terms of average throughput, intra-cluster communication delay, and minimum signal-to-noise ratio (SNR).…”
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Model updating method for detect and localize structural damage using generalized flexibility matrix and improved grey wolf optimizer algorithm (I-GWO) by Sina Sadraei, Majid Gholhaki, Omid Rezaifar

“…Furthermore, they show that when compared to grey wolf optimizer (GWO) and particle swarm optimizer (PSO), I-GWO can offer a dependable method for precisely detecting damage.…”
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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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AquaCrop Plug-in-PSO: A novel irrigation scheduling optimization framework for maize to maximize crop water productivity using in-season weather forecast and crop yield estimation by Mahdi Gholami Sharafkhane, Ali Naghi Ziaei, Seyed Mohammadreza Naghedifar, Amir Akbari, Amir Verdi

“…The main objective of this study was to develop a novel irrigation scheduling optimization framework (AquaCrop plug-in-PSO) for maize, based on in-season weather forecasts integrated with the AquaCrop plug-in model and the particle swarm optimization (PSO) algorithm. …”
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A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression by Tingkai Hou, Zonghong Zhou, Yonggang Zhang, Jing Zhang

“…Secondly, the DE-GWO, particle swarm optimization (PSO), genetic algorithm (GA), and SVR are integrated to identify the optimal superparameters, while the nonlinear mapping relationship between inversion parameters and displacements is established. …”
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Optimization of Transmission Power in a 3D UAV-Enabled Communication System by Jorge Carvajal-Rodríguez, David Vega-Sánchez, Christian Tipantuña, Luis Felipe Urquiza, Felipe Grijalva, Xavier Hesselbach

“…To this end, using the particle swarm optimization evolution (PSO-E) algorithm, this paper analyzes the impact of user-truncated distribution models for suburban, urban and dense urban environments. …”
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A Two-Stage Optimization Framework for UAV Fleet Sizing and Task Allocation in Emergency Logistics Using the GWO and CBBA by Yongchao Zhang, Wei Xu, Helin Ye, Zhuoyong Shi

“…Subsequently, at the tactical level, the CBBA performs decentralized, real-time task allocation for the optimally sized fleet. We validated our GWO-CBBA framework through extensive simulations against three benchmarks: a standard CBBA with a fixed fleet, a centralized Particle Swarm Optimization (PSO) approach, and a Greedy Heuristic algorithm. …”
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