Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh by Md. Anwar Uddin, Sumit Roy, Tahsin Tamanna, Rubayet Arafin Rimon

“…The analysis examined the distribution of the TOD index values across the city and identified areas with varying levels of TOD potential. Two optimization algorithms, ant colony optimization (ACO) and particle swarm optimization (PSO), were employed to assess and compare the TOD index values. …”
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Research on Site Selection and Capacity Determination of Electric Vehicle Public Charging Stations by Integrating K-Means++ and Improved RODDPSO by B. Huang, Z. Wang, J. Chen, B. Zhou, Y. Zhu, Y. Liu

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RETRACTED ARTICLE: Intelligent power management based on multi-objective cost function for plug-in biogas hybrid vehicles under uncertain driving conditions by Sameh Abd-Elhaleem, Walaa Shoeib, Abdel Azim Sobaih

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Control of a compliant gripper via least-squares support vector regression (LS-SVR) with particle swarm optimization (PSO) algorithm by Poonnapa Chaichudchaval, Archawin Chaitrekal, Nawin Sutthiprapa, Dung-An Wang, Teeranoot Chanthasopeephan

“…This study focuses on controlling a compliant gripper using least-squares support vector regression (LS-SVR) combined with a particle swarm optimization (PSO) algorithm. The compliant gripper is designed to grip small objects with high precision. …”
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A Hybrid Approach for Reachability Analysis of Complex Software Systems Using Fuzzy Adaptive Particle Swarm Optimization Algorithm and Rule Composition by Nahid Salimi, Seyfollah Soleimani, Vahid Rafe, Davood Khodadad

“…Furthermore, it explored 32.7% fewer states on average than the hybrid method based on Particle Swarm Optimization and Gravitational Search Algorithms, and 57.4% fewer states compared to Genetic Algorithms, indicating improved search efficiency. …”
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Establishment and Solution Test of Wear Prediction Model Based on Particle Swarm Optimization Least Squares Support Vector Machine by Xiao Huang, Yongguo Wang, Yuhui Mao

“…By integrating data collected by multiple sensors, key feature information reflecting the tool wear state is extracted; dimensionality reduction techniques such as principal component analysis (PCA) are used to optimize feature vectors to improve the distinguishability of features. The model parameters are optimized by the two-dimensional coordinates (c and g) of the particle swarm algorithm to adapt to the given training sample set. …”
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Short-term solar irradiance forecasting model based on hyper-parameter tuned LSTM via chaotic particle swarm optimization algorithm by V Ashok Gajapati Raju, Janmenjoy Nayak, Pandit Byomakesha Dash, Manohar Mishra

“…With this incitement, this paper suggests a hybrid deep learning (DL) model via Long Short-Term Memory (LSTM) networks and Chaotic Particle Swarm Optimization (CPSO). The proposed DL architecture leverages the power of LSTM to learn complex temporal patterns in short-wave solar irradiance data. …”
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KMOBPSO-Based High Reliability Controller Placement Algorithm in SDN by Jingting Xu, Hua Qu, Jihong Zhao

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Assessment of energy management and power quality improvement of hydrogen based microgrid system through novel PSO-MWWO technique by Hafiz Ghulam Murtza Qamar, Xiaoqiang Guo, Ehab Seif Ghith, Mehdi Tlija, Abubakar Siddique

“…This study proposed a novel bi-level optimization approach to enhance power quality and cost efficiency of the system. In the quest to improve energy management systems (EMS) and enhance power quality, a bi-level optimization approach named Particle swarm optimization-Modified water wave optimization (PSO-MWWO) has been proposed. …”
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Photovoltaic Global Maximum Power Tracking Based on Improved Dragonfly Algorithm by Fei XUE, Xin MA, Bei TIAN, Hui WU

“…The convergence rate and global search ability of the algorithm are improved by optimizing particle roles and introducing the Lévy flight model. …”
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Detecting Floating-Point Expression Errors Based Improved PSO Algorithm by Hongru Yang, Jinchen Xu, Jiangwei Hao, Zuoyan Zhang, Bei Zhou

“…This paper proposes characteristic particle swarm optimization (CPSO) algorithm based on particle swarm optimization (PSO) algorithm. …”
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WSN clustering routing algorithm based on PSO optimized fuzzy C-means by Aijing SUN, Shichang LI, Yicai ZHANG

“…Aimed at the problems of limited energy and unbalanced load in wireless sensor network, POFCA based on particle swarm optimization fuzzy C-means was proposed.POFCA was respectively optimized from the cluster stage and the data transmission stage.In the clustering stage, the particle swarm optimization fuzzy C-means was firstly used to overcome the sensitivity to the initial clustering center.And the cluster head was dynamically updated according to the remaining power and the relative distance of the nodes to balance the network load.Then in the data transfer phase, a path evaluation function was designed based on the distance factor, the energy factor and the nodal load.Besides, the cat swarm optimization was used to search the optimal routing path for the cluster head to balance the load of the cluster head without increasing the load of the relay node.The simulation result shows that compared with algorithms of LEACH and LEACH-improved, POFCA can effectively balance the network load, reduce the energy consumption of nodes and extend the lifetime of the entire network.…”
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Multi-Objective Evolution and Swarm-Integrated Optimization of Manufacturing Processes in Simulation-Based Environments by Panagiotis D. Paraschos, Georgios Papadopoulos, Dimitrios E. Koulouriotis

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Improved DV-Hop Node Localization Algorithm in Wireless Sensor Networks by Xiao Chen, Benliang Zhang

“…Finally, we use the particle swarm optimization to correct the position estimated by the 2D hyperbolic localization algorithm, which makes the result closer to the actual position. …”
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Trajectory Optimization of Hypersonic Periodic Cruise Using an Improved PSO Algorithm by Hesong Li, Yi Wang, Shangcheng Xu, Yunfan Zhou, Dan Su

“…In this paper, hypersonic periodic cruise trajectory is analyzed theoretically and optimized by an improved Particle Swarm Optimization algorithm. Firstly, through theoretical analysis, it is determined that the optimal throttle curve can be parameterized as a switching function. …”
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Key Transmission Section Search Strategy Based on Improved Clustering Algorithm by Jie WANG, Ming DING, Lei SUN, Liubing WANG

“…Firstly, an improved particle swarm optimization algorithm is employed to update the clustering center, so that the problem that the clustering algorithm is sensitive to the initial clustering center can be solved. …”
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Improved Grey Wolf Algorithm: A Method for UAV Path Planning by Xingyu Zhou, Guoqing Shi, Jiandong Zhang

“…Compared to Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), GWO, and MP–GWO algorithms, the NI–GWO algorithm can achieve the optimal fitness value and has significant advantages in terms of average path length, time, number of collisions, and obstacle avoidance capabilities.…”
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Guided Particle Swarm Optimization for Feature Selection: Application to Cancer Genome Data by Simone A. Ludwig

“…This paper presents a feature selection method based on Particle Swarm Optimization (PSO). The proposed algorithm makes use of a guided particle scheme whereby three filter-based methods are incorporated. …”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…Results Simulation results demonstrate that the ISSA significantly outperforms the original SSA and other state-of-the-art algorithms, such as particle swarm optimization (PSO), differential evolution (DE), artificial bee colony (ABC), and whale optimization algorithm (WOA). …”
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Recovering 3D Basin Basement Relief Using High-Precision Magnetic Data Through Particle Swarm Optimization and Back Propagation Algorithm by Shen Yan, Xinjun Zhang, Zhongda Shang, Kai Wang, Yixin Ma

“…This paper proposes a new method for the inversion of magnetic basement interfaces using a particle swarm optimization algorithm that combines potential field processing and machine learning techniques. …”
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