RIS-assisted terahertz frequency band vehicle network capacity optimization by Fatang CHEN, Xiaoling LIU, Dan WANG, Ruofan ZHANG

“…In order to alleviate the spectrum scarcity and capacity limitation of the current wireless system, the terahertz frequency band was introduced and the reconfigurable intelligent surface (RIS) was used for auxiliary communication to construct a downlink vehicle network.Considering the constraints of limited total system power, QoS constraints of cellular mobile users, and randomness constraints of vehicle and user locations, a hybrid optimization model was established for optimal power allocation and optimal deployment of RIS with the aim of maximizing the total rate of vehicle users.Based on the balance method, linear transformation method, and element elimination method, the original NP-hard problem was transformed into a convex optimization problem with complex correlation constraints and multivariate coupling.The inner layer iteration was based on the Lagrange multiplier method to solve the optimal power allocation, and the outer layer iteratively solved the optimal deployment of RIS based on a improved genetic algorithm.The simulation results show that rationally deploying the number and distribution density of RIS nodes based on optimal power allocation can save costs while achieving a higher target total capacity.…”
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Optimization Design and Simulation of Single Degree of Freedom Legs of Quadruped Robots by Shi Huiwen, He Jing, Wang Zhijun

“…The optimal motion size and initial position of each component of the mechanism are optimized by using the genetic algorithm and the general nonlinear optimization method with the approximation degree of non-impact foot trajectory as the objective. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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SVR Data-Driven Optimization of Generator Leading Phase Operation Limit by Dengfeng LI, Mincai YANG, Yuming LIU, Ruilin XU, Xia YU, Zhaojiong LI

“…The improved second-order oscillation particle swarm optimization algorithm is then applied to solve the optimization model. …”
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Research on Multi-Objective Reactive Power Optimization of Distribution Grid with Photovoltaics by Lie Xia, Xiaojin Lin, Rongrong Zhou, Kanjian Zhang

“…Aiming at the two objectives of the network loss and voltage fluctuation rate, the improved multi-objective particle swarm optimization algorithm is used to solve the model under the condition that the output of each device does not exceed the constraint and the optimal solution that can reduce the distribution grid loss and improve the voltage stability of the distribution grid is obtained. …”
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Thermal boundary condition optimization of feed system based on RSM-IRIME by Haiyang Liu, Xianying Feng, Ming Yao, Anning Wang, Yandong Liu

“…Inspired by the accumulation of soft and hard-rime, the Tent chaotic map and Lévy flight strategy are introduced, and an improved rime algorithm (IRIME) is proposed to optimize the thermal boundary parameters. …”
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A novel framework for identifying fishing grounds from AIS data containing vessels of unknown types by Changhai Huang, Jialong Kong, Jian Zheng, Yuli Chen, Jingen Zhou

“…Subsequently, an algorithm that integrates the Data Field and OPTICS (DF-OPTICS) algorithm is proposed, and a model for identifying fishing grounds is constructed based on the DF-OPTICS algorithm. …”
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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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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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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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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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Explorative Binary Gray Wolf Optimizer with Quadratic Interpolation for Feature Selection by Yijie Zhang, Yuhang Cai

“…This paper proposes a novel binary Gray Wolf Optimization algorithm to address the feature selection problem in classification tasks. …”
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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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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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