Design and Dimension Optimization of Rigid–Soft Hand Function Rehabilitation Robots by Rui Zhang, Meng Ning, Yuqian Wang, Jun Yang

“…Hierarchical constraint modeling and an improved artificial bee colony algorithm optimize linkage dimensions and control strategies, achieving enhanced human–robot kinematic matching. …”
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Shape optimization of non-uniform parametric piezoelectric energy harvester beam by Milad Hasani, Hossein Shahverdi

“…The model, validated through finite element method (FEM) simulations and experimental data, enables rapid analysis and optimization of PEHs. …”
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A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle by Jianhui Mou, Bo Shi, Bo Wang, Chengcheng Yu, Yangwei Wang, Fusheng Zhong, Li Zheng, Jian Wang, Junjie Li

“…Subsequently, an optimized deep neural network with a reward-averaging strategy is constructed to effectively enhance the learning and convergence speed of the algorithm, thus further improving the global search capability and interface performance of USV path planning. …”
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Multi-objective optimization of integrated energy system considering customer satisfaction by YU Wuyue, JIA Yuchen, HUO Limin, WEN Peng, GAO Liai

“…A multi-objective optimization function with improved customer satisfaction, economy and carbon emission is constructed, and MAPSO (multi-group adaptive particle swarm optimization) algorithm is used for optimization analysis, and the Pareto optimal frontier solution sets in different scenarios are obtained. …”
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Stability Evaluation Method for Rock Slope-Anchorage Systems Based on Genetic Algorithms and Discrete Element Analysis by Peng Xia, Bowen Zeng, Yiheng Pan

“…The findings indicate that (1) the proposed evaluation method effectively accounts for the interaction between the anchorage structure and the rock slope, ensuring accurate results; (2) the method leverages the discrete element numerical model to quantitatively assess deformation and stress distribution within the system; (3) the integration of genetic algorithms significantly enhances the efficiency of identifying the most representative numerical model, and thereby the efficiency of stability evaluation is improved; and (4) the evaluation framework is capable of performing dynamic analyses of the stability evolution throughout the entire operational lifecycle of the rock slope anchorage system.…”
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Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

“…The estimated subsurface parameters closely match with well data and prior studies, emphasizing the algorithm’s practical effectiveness. This integrated approach significantly advances the interpretation of magnetic datasets by improving both the accuracy and resolution of subsurface parameters estimation within the framework of idealized geometric models.…”
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Automatic detection and classification of drill bit damage using deep learning and computer vision algorithms by Xiongwen Yang, Xiao Feng, Chris Cheng, Jiaqing Yu, Qing Zhang, Zilong Gao, Yang Liu, Bo Chen

“…The experimental results demonstrate that the proposed method significantly enhances the accuracy of bit damage detection and classification while also providing substantial improvements in processing speed and computational efficiency, offering a valuable tool for optimizing drilling operations and reducing costs.…”
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Dynamic Analysis and Efficient Numerical Algorithm for Rocking Response of Freestanding Packages Under Transportation Excitations by Zhenmin Qi, Dapeng Zhu

“…Experimental validation under sinusoidal and numerical analysis with random excitations confirms the algorithm’s effectiveness in predicting rocking behavior. …”
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM by Ahmed Mohammed Ahmed Alsarori, Mohd Herwan Sulaiman

“…Cardiovascular diseases (CVD) remain the leading cause of mortality worldwide, emphasizing the urgent need for accurate and efficient predictive models. This study proposes a dual-output deep learning model based on a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, optimized using the Evolutionary Mating Algorithm (EMA). …”
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Frequency Optimization Objective during System Prototyping on Multi-FPGA Platform by Mariem Turki, Zied Marrakchi, Habib Mehrez, Mohamed Abid

“…Many scenarios are proposed to obtain the most optimized results in terms of prototyping system frequency. …”
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Water Supply Scheduling for Cross-basin Reservoir Groups Based on Improved Scheduling Diagram by ZHAO Siqi, XU Wei, CHEN Si, WANG Sufan, YANG Yi

“…To exploit the scheduling potential of cross-basin reservoir groups by employing runoff information,this paper proposes an improved reservoir scheduling diagram to retain simplicity and intuitiveness.Taking the Xiajiankou,Fengyan,and Nanpeng reservoirs in Banan District of Chongqing as an example,it adopts the POA algorithm to build a joint scheduling model of water diversion and water supply for the cross-basin reservoir groups by a simulation-optimization approach.Meanwhile,three scenarios of the current situation scheduling,optimized scheduling with conventional scheduling diagrams,and optimized scheduling with improved scheduling diagrams are set up to evaluate the water diversion and supply performance of reservoirs and analyze the influence of uncertainty runoff information on the scheduling performance.The results are as follows:① The improved scheduling diagram performs best in the long series scheduling,and it can increase the annual average water supply of the reservoir group by 6.87% and reduce the abandoned water by 87.58% compared with the current situation scheduling;② In a dry year,the method can reduce 486.3×10⁴ m³ of water shortage and increase 477.6×10⁴ m³ of water for power generation based on the current situation scheduling;③ When considering the runoff information uncertainty,the water supply of the improved scheduling diagram is 3.37% lower than the ideal case but is still 5.96% more than the conventional optimization.The results are conducive to making scientific decisions and improving the water supply effect.…”
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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…Finally, the actual blasting effect of tunnel construction is tested and the optimization algorithm model of tunnel fault drilling and blasting parameters is established. …”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
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Optimal control strategy for trains in emergency self-propelled running conditions by ZHU Yutong

“…In conclusion, the designed coasting algorithm based on the optimal constant speed can effectively reduce the total energy consumption of emergency self-propelled train operation, thereby improving the self-rescue success rate of high-speed trains.…”
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Optimization of Intelligent English Pronunciation Training System Based on Android Platform by Qianyu Cao, Hanmei Hao

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Solution Approach to the Minimum Spanning Tree Problem in Tsukamoto Fuzzy and Fermantean Fuzzy Environments by Desli de Haas, Citra Palembang, Aziz Rumakefing

“…With the help of Numerical examples, the solution technique for the proposed FFMST model is explained. It aims to modify the Prims algorithm for oriktade graphing and the optimal result processing algorithm for re-graphing in Fuzzy Fermatean ( FFN )-miljö. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

“…We generated a stratified 60‐20‐20 train‐validate‐test split to assess model generalizability. We trained four machine learning algorithms including logistic regression, Random Forest, AdaBoost and XGBoost. …”
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Collaborative Optimization Strategy for Dependent Task Offloading in Vehicular Edge Computing by Xiting Peng, Yandi Zhang, Xiaoyu Zhang, Chaofeng Zhang, Wei Yang

“…The task-offloading problem is modeled as a Markov Decision Process, and an improved twin-delayed deep deterministic policy gradient algorithm, LT-TD3, is introduced to enhance the decision-making process. …”
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Tool wear monitoring method based on AMIDBOAB and imbalanced data optimization by Guan-Hua Xu, Hong-Yu Wu, Bo Tang, Jun-Long Xu

“…Introducing circle chaotic mapping, Levy flight strategy, and adaptive variable inertia weight, a multiple improvement dung beetle optimizer algorithm is proposed to optimize the parameters of the base classifier in the adaptive boosting model. …”
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