Convex Optimization of Markov Decision Processes Based on Z Transform: A Theoretical Framework for Two-Space Decomposition and Linear Programming Reconstruction by Shiqing Qiu, Haoyu Wang, Yuxin Zhang, Zong Ke, Zichao Li

“…The proposed approach introduces three mathematical innovations: (i) a spectral clustering mechanism that reduces state-space dimensionality while preserving Markovian properties, (ii) a Lagrangian dual formulation with adaptive penalty functions to handle operational constraints, and (iii) a warm start algorithm accelerating convergence in high-dimensional convex optimization. …”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…On the contrary, the algorithms applying YOLOv5, YOLOX, YOLOv7 and the paper's improved YOLOv5 achieved the recall rates from 95.26% to 96.28%, while algorithms applying DeepSORT, StrongSORT, Bot-SORT and CombineSORT achieved the MOTA values from 0.887 to 0.901. …”
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Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications by Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong

“…To address these challenges, this study proposes an improved individual tree trunk detection algorithm, Random Sample Consensus Cylinder Fitting (RANSAC-CyF), specifically optimized for detecting cylindrical tree trunks. …”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…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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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…This study proposes a systematic framework, termed VMD-RUN-Seq2Seq-Attention, for noise reduction, outlier detection, and wind speed prediction by integrating Variational Mode Decomposition (VMD), the Runge–Kutta optimization algorithm (RUN), and a Sequence-to-Sequence model with an Attention mechanism (Seq2Seq-Attention). …”
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Dual Strategy of Reconfiguration with Capacitor Placement for Improvement Reliability and Power Quality in Distribution System by Ali Nasser Hussain, Wathiq Rafa Abed, Mohanad Muneer Yaqoob

“…While the constraints include limits of system reliability indices to provide optimal constraints on negative interactions of power quality. …”
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Research on Stability Optimization for Automatic Train Operation of Heavy-haul Trains of Baoshen Railway by FU Shangyuan

“…During the departing stage, the optimization algorithm effectively improved operational stability on steep grades, and increased the departing speed by about 11.1%. …”
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Nonlinear Stability Analysis of Shallow-Buried Bias Tunnel Based on Failure Mode Improvement by Wei Luo, Gequan Xiao, Zhi Tao, Jingyu Chen, Xi Lu, Haifeng Wang

“…The SQP algorithm in MATLAB (R2022a) software was used to optimize the solution, and the influence of slope top load, buried depth ratio, cohesion, and axial tensile stress on the surrounding rock pressure and the failure mode of shallow-buried tunnel was analyzed through examples. …”
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Optimizing Strategies in Patients Affected by Tumors Infiltrating the Skull: A Single Center Experience by Giuseppe Emmanuele Umana, Sruthi Ranganathan, Salvatore Marrone, Jessica Naimo, Matteo Giunta, Angelo Spitaleri, Marco Fricia, Gianluca Ferini, Gianluca Scalia

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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…A low-carbon, economic dispatch method for IES using an enhanced wind power scenario reduction algorithm is introduced in this paper. It employs an improved iterative self-organizing data analysis technique algorithm (ISODATA) for clustering historical wind power scenarios, addressing the limitations of traditional clustering algorithms in determining cluster centers and analyzing inherent data features. …”
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МЕСHANICAL BEHA VIOR OF GRADED HONEYCOMB AND ITS MULTI-OBJECTIVE OPTIMAL DESIGN by CHEN BiMin, HUANG XiaoDi

“…Taking the crashworthiness index of the honeycomb as the optimization goal, in the design space of the gradient honeycomb, the multi-objective optimization algorithm is directly used to determine the specific parameters of each layer of the gradient honeyeomb. …”
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LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…Additionally, the CBAM attention mechanism is incorporated into the neck network to improve model performance. A Focal-EIoU loss function is also integrated to optimize the model’s training process. …”
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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

“…By incorporating the model bias, the combined metamodel can better approximate the original optimal solution. Moreover, incorporating the gradient information of the traffic flow in the optimization search algorithm can further improve the solution performance. …”
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Advanced Control Technique for Optimal Power Management of a Prosumer-Centric Residential Microgrid by Peter Anuoluwapo Gbadega, Yanxia Sun, Olufunke Abolaji Balogun

“…To solve the multi-objective power management optimization problem, the Teaching-Learning-Based Optimization (TLBO) algorithm was implemented. …”
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A Bi-Level Optimization Model for Flexible Capacity Allocation with Coordinated Planning and Operation by Xinyu Yin, Xiaoyan Bian, Qinran Zhu, Jinbin Zhao, Shunfu Lin, Kwok L. Lo

“…Using collaborative optimization during the flexibility resource planning stage can significantly improve the overall economics and flexibility. …”
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A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…Therefore, feature factors selection using the MDA method was considered the optimal feature subset. Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”
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Throughput-Delay Trade-Off for Cognitive Radio Networks: A Convex Optimization Perspective by Hang Hu, Hang Zhang, Hong Yu

“…It is proved that the maximum achievable throughput and the minimum transmission delay cannot be obtained simultaneously. An efficient algorithm is proposed to optimize the sensing bandwidth and the final decision threshold jointly such that the throughput is maximized while the delay is constrained. …”
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Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

“…The method integrates a conventional proportional derivative control algorithm with Bayesian optimization to rapidly determine optimal control parameters without a precise system model and adaptively re-tune these parameters in response to fluctuations in patient respiratory conditions. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…In addition, a multi-hop relational path inference mechanism is introduced to capture long-distance dependencies to improve the depth of user interest modeling. Experiments on the Amazon-Book and Last-FM datasets show that SKGRec significantly outperforms several state-of-the-art recommendation algorithms on the Recall@20 and NDCG@20 metrics. …”
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Energy Simulation and Optimal Scheduling of Integrated Energy System Considering Hybrid Energy Storage by Yongwei LUO, Chengren LI, Ling ZHANG, Jianmin ZHANG, Xinhong WU, Jinbu LIAN, Jin FAN

“…The complementary multi-energy based integrated energy system (IES) is an important way to improve regional energy efficiency and optimize energy resources allocation. …”
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