Routing Optimization for Shared Electric Vehicles with Ride-Sharing by Chuanxiang Ren, Jinbo Wang, Yongquan You, Yu Zhang

“…The results show that the proposed routing optimization model achieves the optimal SEVs route, realizes the MSEVRS, and improves the utilization rate of SEVs. …”
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Data-Enabled Predictive Control for Optimal Pressure Management by Gal Perelman, Avi Ostfeld

“…Recent developments in control theory coupled with the growing availability of real-time data have paved the way for improved data-driven control methodologies. This study explores the application of a data-enabled predictive control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). …”
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Kinematics Analysis and Trajectory Optimization of the Hybrid Welding Robot by Cai Ganwei, Ban Caixia, Tian Junwei, Zhang Kechen

“…At the same time, a trapezoidal function with parabolic transition is used to plan the end effector of the hybrid welding robot, and the multi-objective trajectory optimization scheme is proposed. The particle swarm optimization algorithm is used to optimize the time parameters, and the optimal time parameters that meet the positioning accuracy of the end of the welding machine manipulator are solved. …”
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Predicting Wear Rate and Friction Coefficient of Li₂Si₂O₅ Dental Ceramic Using Optimized Artificial Neural Networks by Marko Pantić, Saša Jovanović, Aleksandar Djordjevic, Suzana Petrović Savić, Milan Radenković, Živče Šarkoćević

“…This study explores the application of artificial neural networks (ANNs) to predict the tribological behavior of dental ceramic lithium disilicate (IPS e.max Cad). A genetic algorithm (GA) was used to optimize the ANN’s hyperparameters, improving its ability to model complex, nonlinear relationships between input variables, including normal load and velocity and output properties such as wear rate and friction coefficients. …”
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Implementation of Apriori Algorithm in Identifying Purchase Relationships at Bluder Cokro Pakuwon Mall by Angeline Ivana, Indra Maryati

“…This study aims to identify consumer purchasing patterns at the store to enhance promotional strategies and optimize product placement. The research applies the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, which includes phases such as business understanding, data understanding, data preparation, modeling, evaluation, and deployment. …”
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Study of In-Vehicle Ethernet Message Scheduling Based on the Adaptive Frame Segmentation Algorithm by Jiaoyue Chen, Yujing Wu, Yihu Xu, Kaihang Zhang, Yinan Xu

“…Experimental results indicate that the AFS algorithm achieves an average local bandwidth utilization of 94.16%, improving by 4.35%, 5.65%, and 30.48% over Frame Pre-Emption, Packet-Size Aware Scheduling (PAS), and Improved Qbv algorithms, respectively. …”
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Solution of a flexible jobshop scheduling problem using an Estimation of Distribution Algorithm. by R. Pérez, S. Jöns, A. Hernández

“…In the algorithm, three graphical models were used to find better solutions. …”
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Optimal Design of Variable-Stiffness Fiber-Reinforced Composites by Evangelos P. Hadjigeorgiou, Christos A. Patsouras, Vassilios K. Kalpakides

“…The fiber orientation is assumed to be constant within each element of the model but varies from element to element. The optimal design problem is solved numerically using a global optimization method based on a genetic algorithm. …”
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Machine learning based crystal collimator alignment optimization by Gianmarco Ricci, Marco D’Andrea, Mario Di Castro, Eloise Matheson, Daniele Mirarchi, Andrea Mostacci, Stefano Redaelli

“…This advancement represents a crucial step toward refining the process of identifying the optimal channeling orientation. The algorithm has been tested for the fist time in operation with Pb ion beams at the record energy of 6.8 Z TeV demonstrating its reliability.…”
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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…To address these issues, this paper proposes a novel small-object detection algorithm. Firstly, a more efficient backbone network is introduced, and a composite scaling method is employed to optimize the balance among network depth, width, and image resolution. …”
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Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

“…Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss analysis and predictive models based on Random Forest (RF) and K-Nearest Neighbors (KNN) algorithms. …”
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Validation and Optimization of Suspension Design for Testing Platform Vehicle by Luhang Li, Lin Xu, Hao Cui, Mohamed A. A. Abdelkareem, Zihao Liu, Jingyu Chen

“…The nondominated sorting genetic algorithm (NSGA-II) is used to optimize the damping, stiffness, and installation position of the suspension system. …”
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A novel economic load dispatch method of microgrid based on hybrid slime mould and genetic algorithm by Wei Ba, Wei Sun, Chunjiang Zhao, Qi Li

“…For performance evaluation, GSMA is compared with slime mould algorithm (SMA), grey wolf optimizer (GWO), sparrow search algorithm (SSA), Harris Hawks optimization (HHO), whale optimization algorithm (WOA) and particle swarm optimization (PSO) using standard optimization functions. …”
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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…This study presents a novel control strategy that integrates the Groupers and Moray Eels Optimization (GMEO) algorithm with a Dual-Stream Multi-Dependency Graph Neural Network (DMGNN) to optimize PID controller parameters. …”
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Adaptive Hybrid PSO-Embedded GA for neuroevolutionary training of multilayer perceptron controllers in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

“…The algorithm’s performance is evaluated against conventional optimization methods, demonstrating significant improvements in accuracy, convergence speed, and consistency across multiple runs. …”
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Machine Learning for Decision Support and Automation in Games: A Study on Vehicle Optimal Path by Gonçalo Penelas, Luís Barbosa, Arsénio Reis, João Barroso, Tiago Pinto

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Forest canopy closure estimation in mountainous southwest China using multi-source remote sensing data by Wenwu Zhou, Wenwu Zhou, Qingtai Shu, Cuifen Xia, Li Xu, Qin Xiang, Lianjin Fu, Zhengdao Yang, Shuwei Wang

“…Combined with 54 measured plot data, the improved machine learning model of the Bayesian optimization (BO) algorithm was used to obtain the FCC in the footprint-scale ATLAS footprint. …”
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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…The downer of a GLSCFB bioreactor provided experimental data on TKN, NH4-N, NO3-N, and TCOD removal. The hybrid optimal intelligence algorithm (BOA-SVR) has improved model accuracy across multiple domains by combining BOA and SVR. …”
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Hybrid AE and Bi-LSTM-Aided Sparse Multipath Channel Estimation in OFDM Systems by Vijayakumar Kondepogu, Budhaditya Bhattacharyya

“…Further, an efficient Grasshopper Electric Fish Optimization Algorithm (G-EFOA) is developed to optimize the parameters of AE and Bi-LSTM, resulting in superior solutions. …”
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The data analysis of sports training by ID3 decision tree algorithm and deep learning by Kaigong Wang, Lei Wang, Jiduo Sun

“…Abstract In order to improve the accuracy and efficiency of sports training data analysis, this paper proposes an optimized analysis model by combining Iterative Dichotomiser 3 (ID3) decision tree algorithm and deep learning model. …”
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