An evaluation of flow-routing algorithms for calculating contributing area on regular grids by A. B. Prescott, J. D. Pelletier, S. Chataut, S. Ananthanarayan

“…Here we document the fact that a commonly used multiple-flow-direction algorithm for calculating contributing area, i.e., <span class="inline-formula"><i>D</i>∞</span> of Tarboton (1997), is sufficiently biased along the cardinal and ordinal directions that it is unsuitable for some standard applications of flow-routing algorithms. …”
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A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management by Shih-Che Lo

“…<i>Results</i>: Performance comparisons were made with the Genetic Algorithm (GA) through the experiments of several vehicle routing problems with pickup and delivery benchmark problems to validate the performance of the ePSO procedure. …”
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Data-Driven Model-Free Adaptive Control of Particle Quality in Drug Development Phase of Spray Fluidized-Bed Granulation Process by Zhengsong Wang, Dakuo He, Xu Zhu, Jiahuan Luo, Yu Liang, Xu Wang

“…A novel data-driven model-free adaptive control (DDMFAC) approach is first proposed by combining the advantages of model-free adaptive control (MFAC) and data-driven optimal iterative learning control (DDOILC), and then its stability and convergence analysis is given to prove algorithm stability and asymptotical convergence of tracking error. …”
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A Novel Chaotic Particle Swarm Optimized Backpropagation Neural Network PID Controller for Four-Switch Buck–Boost Converters by Luoyao Ren, Dazhi Wang, Xin Yan, Yupeng Zhang, Jiaxing Wang

“…To address these challenges, chaotic optimization algorithms are integrated with BPNN. The chaotic particle swarm optimization (CPSO) algorithm enhances the global search capability, enabling a faster system response and minimizing overvoltage. …”
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Optimizing Artificial Neural Networks with Particle Swarm Optimization for Accurate Prediction of Insulator Flashover Voltage Under Dry and Rainy Conditions by Abdelhalim Mahdjoubi, lazreg taibaoui, Boubakeur Zegnini

“…A hybrid model combining Artificial Neural Networks (ANN) with Particle Swarm Optimization (PSO) is developed to address these challenges. …”
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Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…To address these challenges, this paper presents an innovative tool wear prediction method that integrates a nonlinear mean function and a multi-kernel function-optimized GPR model combined with an LSTM-enhanced particle filter algorithm. The approach incorporates the LSTM network into the state transition model, utilizing its strong time-series feature extraction capabilities to dynamically adjust particle weight distributions, significantly enhancing the accuracy of state estimation. …”
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Electric Vehicle Charging Load Forecasting Method Based on Improved Long Short-Term Memory Model with Particle Swarm Optimization by Xiaomeng Yang, Lidong Zhang, Xiangyun Han

“…In this context, the present study proposes a Particle Swarm Optimization (PSO)-enhanced Long Short-Term Memory (LSTM) network forecasting model. …”
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UWB Base Station Deployment Optimization Method Considering NLOS Effects Based on Levy Flight-Improved Particle Swarm Optimizer by Shengliang Wang, Ming Gao, Ling’ai Li, Dong Lv, Yingqi Li

“…In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor positioning area as the fitness function, and proposes an improved particle swarm optimization algorithm based on the Levy flight strategy (LPSO) to solve the optimization problem. …”
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Multi-Criteria Optimization of a Hybrid Renewable Energy System Using Particle Swarm Optimization for Optimal Sizing and Performance Evaluation by Shree Om Bade, Olusegun Stanley Tomomewo, Ajan Meenakshisundaram, Maharshi Dey, Moones Alamooti, Nabil Halwany

“…When compared to the Genetic Algorithm (GA) and hybrid GA-PSO, PSO improved cost-effectiveness by 3.4% over GA and reduced ASC by 1.09% compared to GAPSO. …”
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Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler by Yujin Cong, Cheng Meng, Ming Yang, Yong Liu, Ping Yi, Tie Li, Shuai Huang

“…In this study, the response surface methodology combined with the multi-objective particle swarm optimization algorithm was used to optimize the fuel pipeline resistance and its space volume, aiming to select the optimal design scheme for an X-type replenishment oiler. …”
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Algorithm of reconstruction combined midface defects after resection malignant tumors by M. V. Bolotin, A. M. Mudunov, V. Yu. Sobolevsky, V. I. Sokorutov

“…In 5 (42 %) cases, the resection was combined and included, in addition to the upper jaw, the skin of the buccal and zygomatic regions. Type III - combined partial resections of the upper jaw (13 (17 %) cases). …”
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Optimization of process parameters in Nano-particle mixed EDM of hardened die steel AISI H13 using RSM and GA by Tasfia Saba, AKM Nurul Amin, Sanjida Islam, Maisha Rahman Chaity, Noshin Tasnim Tuli, Adib Bin Rashid

“…Optimization was conducted utilizing Response Surface Methodology (RSM) and Genetic Algorithm (GA). The execution of a test run facilitated a comparison between the actual outcomes and the optimized results. …”
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Energy Management of a Semi-Autonomous Truck Using a Blended Multiple Model Controller Based on Particle Swarm Optimization by Mohammad Ghazali, Ishaan Gupta, Kemal Buyukkabasakal, Mohamed Amine Ben Abdallah, Caner Harman, Berfin Kahraman, Ahu Ece Hartavi

“…The approach combines a particle swarm optimization algorithm to determine optimal controller gains and a multiple model controller to adapt these gains dynamically based on real-time vehicle mass. …”
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Evaluation of proton and carbon ion beam models in TReatment Planning for Particles 4D (TRiP4D) referring to a commercial treatment planning system by Yinxiangzi Sheng, Lennart Volz, Weiwei Wang, Marco Durante, Christian Graeff

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Remote Sensing of Particle Absorption Coefficient of Pigments Using a Two-Stage Framework Integrating Optical Classification and Machine Learning by Xietian Xia, Shaohua Lei, Hui Lu, Zenghui Xu, Xiang Li, Xing Chen, Niancheng Hong, Jie Xu, Kun Shi, Jiacong Huang

“…The particle absorption coefficient of pigments (<i>a</i>_ph(λ)), a critical indicator of phytoplankton spectral absorption properties, is essential for bio-optical models and water quality monitoring. …”
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Automated Support Generation for Fixed Partial Dentures and Impact of Bone Loss, Bone Quality and Support Types: Parametric Cad and Finite Element Analysis by Hassen Jemaa, Michael Eisenburger, Andreas Greuling

“…<b>Background:</b> This study aimed to develop an algorithm for modelling tooth–tooth or implant–implant support configurations for a given 4-unit fixed partial denture (FPD). …”
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Eel and Grouper Optimizer improvement three-stage algorithm for photovoltaic MPPT by ZiJian Zhou, YanHong Fang

“…Firstly, the chaotic mapping is used to initialize the distribution of particles to improve the search performance. After the EGO as the main algorithm completed the first position update, the GOA was used to redistribute the particles, and finally the tumbling formula was introduced to further improve the ability of particles to jump out of the local optimal solution. …”
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Masterpiece Optimization Algorithm: A New Method for Solving Engineering Problems by Mohammad Reza Ghasemi, Nader Haji Aghajanpour, Hamed Ghohani Arab

“…Due to the importance of seabed fine sand to fish reproduction, the proposed algorithm is based on movement and accumulation of seabed fine sand particles. …”
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Extreme Gradient Boosting Algorithm for Predicting Shear Strengths of Rockfill Materials by Mahmood Ahmad, Ramez A. Al-Mansob, Kazem Reza Kashyzadeh, Suraparb Keawsawasvong, Mohanad Muayad Sabri Sabri, Irfan Jamil, Arnold C. Alguno

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Deep and Domain Specific Feature-Based Cervical Cancer Classification Using Support Vector Machine Optimized With Particle Swarm Optimization by Ritesh Maurya, Lucky Rajput, Satyajit Mahapatra

“…The noisy features have been eliminated by utilising the concept of mutual information whereas, a support vector machine optimized with Particle Swarm Optimization (PSO) was used for the classification. …”
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