An experimental optimization environment for developing an intracycle pitch control in cross flow turbines by Stefan Hoerner, Roberto Leidhold, Shokoofeh Abbaszadeh, Karla Ruiz-Hussmann, Timo Bennecke, Zhao Zhao, Paul Joedecke, Christian-Thoralf Weber, Pierre-Luc Delafin, Cyrille Bonamy, Yves Delannoy

“…A superimposed governing system performs an experimental optimization process. Evolutionary algorithms are to be employed to solve two objectives: (1) maximizing the efficiency and (2) minimizing the structural loads. …”
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Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design by Raquel Busqué, Matias Bossio, Raimon Fabregat, Francesc Bonada, Héctor Maicas, Jordi Pijuan, Albert Brigido

“…The method integrates CFD simulations in Ansys Fluent with a Monte Carlo-driven optimization algorithm, modeling the design of a heat sink domain as a porous medium. …”
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A multi objective optimization framework for smart parking using digital twin pareto front MDP and PSO for smart cities by Dinesh Sahu, Priyanshu Sinha, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Lu Wang

“…Evaluation outcomes also show that the proposed algorithm is better than Round Robin, Random Allocation, and Threshold Based algorithms in terms of 25% improvement in the search time, 18% better energy usage, and 30% less traffic congestion. …”
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Integrated Optimization on Train Control and Timetable to Minimize Net Energy Consumption of Metro Lines by Yuhe Zhou, Yun Bai, Jiajie Li, Baohua Mao, Tang Li

“…This paper developed an integrated optimization model on train control and timetable to minimize the net energy consumption. …”
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Production Sequencing and Layout Optimization of Precast Concrete Components under Mold Resource Constraints by Junyong Liang, Zhifang Cao, Qingzhi Zu, Hua Huang, Shunsheng Guo

“…The research results show that the proposed model and optimization algorithm can help production managers to efficiently formulate more reasonable precast component production sequence and layout schemes, especially for those enterprises that are struggling to improve the efficiency of precast concrete component production.…”
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Enhanced Artificial Rabbit Optimization with attention-based deep learning for leukemia cancer classification by Sabita Rani Behera, Bibudhendu Pati, Devee Sivaprasad Dulam

“…Finally, an improved temporal convolution network (ITCN) model is applied for classification purposes. …”
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Detection and Recognition Algorithm for 100-Meter Signage in Urban Rail Transit Based on Connected Domain Segmentation and SVM by YUAN Xiaojun, TIAN Ye, SU Zhen, LIU Xinwu, LI Chen, ZHANG Huiyuan

“…Finally, the extracted characters are input into the SVM model for recognition. The optimized algorithm demonstrated significant improvements, with detection accuracies increasing by approximately 34.4 percentage points and recognition accuracies by approximately 25.6 percentage points for 100-meter signage in subsequent experiments.…”
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A comparative analysis of photovoltaic system using three algorithms: P&O, Hill Climbing and Fuzzy Logic by Benkirane Yassine, Benhala Bachir, Raihani Abdelhadi

“…We focus on the following algorithms: Perturb and Observe (A simple and highly responsive algorithm with a quick response that adjusts the voltage), Hill Climbing (It is a simple algorithm to implement and is effective for solving combinatorial problems by adjusting the duty cycle), and fuzzy logic (Using linguistic rules, it is possible to intelligently adjust the parameters, improving the connection between the photovoltaic generator and the load to ensure optimal operation). …”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…By using this method, the project cost prediction error reduced to 30–80 yuan, which demonstrated the accuracy of building information modeling technology. Compared with the efficiency value of the algorithm in the first 10s, the traditional single objective optimization algorithm was 0.28, while the proposed algorithm was 0.40. …”
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LEVERAGING MACHINE LEARNING ALGORITHMS TO IDENTIFY POTENTIAL GEOSITES FOR GEOTOURISM PROMOTION IN ZIZ UPPER WATERSHED IN SOUTHEASTERN MOROCCO by Lahbib NAIMI, Mohamed MANAOUCH, Abdeslam JAKIMI

“…Subsequently, the machine learning algorithm, namely Bagging was employed to develop predictive model. …”
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Enhancing flood susceptibility mapping in Sana’a, Yemen with random forest and eXtreme gradient boosting algorithms by Yahia Alwathaf, Ahmed M. Al-Areeq, Yousef A. Al-Masnay, Ali R. Al-Aizari, Nabil M. Al-Areeq

“…The study’s methodology involved optimizing the algorithms through grid search and cross-validation techniques, followed by validation using historical flood data. …”
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Research on inter-plant weeding control in peanut at LADRC based on IACO-PSO optimization by Xiaolong Zhang, Hongzhen Xu, Jiaodi Liu, Longzhe Quan, Lichang Zhang, Bang Zhang

“…By controlling the angular velocity of the stepper motor, we were able to regulate seedling avoidance along the weeding knife’s operational path. A mathematical model for inter-plant seedling avoidance and weeding was established, and an improved hybrid algorithm combining the ant colony algorithm and particle swarm optimization was proposed to optimize the key parameters of the LADRC system. …”
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A Distributed Collaborative Navigation Strategy Based on Adaptive Extended Kalman Filter Integrated Positioning and Model Predictive Control for Global Navigation Satellite System/... by Wanqiang Chen, Yunpeng Jing, Shuo Zhao, Lei Yan, Quancheng Liu, Zichang He

“…This framework predicts and optimizes each robot’s kinematic model, thereby improving the system’s collaborative operations and dynamic decision-making capabilities. …”
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The Evaluation and Promotion Strategy of TSC for Distribution System with New Energy under Power Market Environment by BAI Hao, WANG Yu-shan, ZHOU Chang-cheng, PAN Shu-hui, YE lin-hao, CAI Jian-yi

“…Finally, for scenarios where the TSC does not meet the standard, the improved PSO optimization algorithm is used to re-dispatch and improve TSC. …”
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Optimization of Central Pattern Generator-Based Torque-Stiffness-Controlled Dynamic Bipedal Walking by William Suliman, Chadi Albitar, Lama Hassan

“…Finally, we expanded our neural model by adding connections that work only when the robot walks on uneven terrains, which improved the robot’s performance against this kind of perturbation.…”
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A robust multi-scale clustering framework for single-cell RNA-seq data analysis by Songrun Jiang, Chunyan Wang, Qiucheng Sun, Zhi Zhang

“…To address these challenges, we introduce a new method, single-cell Multi-Scale Clustering Framework (scMSCF), which combines multi-dimensional PCA for dimensionality reduction, K-means clustering, and a weighted ensemble meta-clustering approach, enhanced by a self-attention-driven Transformer model to optimize clustering performance. scMSCF constructs an initial clustering framework using a multi-layer dimensionality reduction strategy to establish a robust consensus on clustering structure. …”
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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…This algorithm adeptly balances resource expenditures with model quality, employing Lyapunov-driven optimization theory to convert long-term stochastic challenges into short-term deterministic resolutions. …”
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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…The optimized VToMe-BiGRU algorithm combines the Transformer model and the BiGRU network, which effectively captures the critical features in the electric drive system data, thus improving the fault prediction performance. …”
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Underwater Acoustic Signal Prediction Based on MVMD and Optimized Kernel Extreme Learning Machine by Hong Yang, Lipeng Gao, Guohui Li

“…Based on the prediction model of kernel extreme learning machine (KELM), this paper uses grey wolf optimization (GWO) algorithm to optimize and select its regularization parameters and kernel parameters and proposes an optimized kernel extreme learning machine OKELM. …”
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Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost by Sonam Tyagi, Ishwari Singh Rajput, Bhawnesh Kumar, Harendra Singh Negi

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