Intelligent Flight Procedure Design: A Reinforcement Learning Approach with Pareto-Based Multi-Objective Optimization by Yunyang Huang, Yanxin Zhang, Yandong Zhu, Zhuo Zhang, Longtao Zhu, Hongyu Yang, Yulong Ji

“…To further enhance performance by tackling the low sampling efficiency in the replay buffer, we introduce a multi-objective sampling strategy based on the Pareto frontier, integrated with the soft actor–critic (SAC) algorithm. Experimental results demonstrate that the proposed method generates executable flight procedures in the BlueSky open-source flight simulator, successfully balancing these three conflicting objectives, while achieving a 28.6% increase in convergence speed and a 4% improvement in comprehensive performance across safety, route simplification, and environmental impact compared to the baseline algorithm. …”
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Motion Adaptive Vertical Handoff in Cellular/WLAN Heterogeneous Wireless Network by Limin Li, Lin Ma, Yubin Xu, Yunhai Fu

“…Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms.…”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…Traditional path planning methods such as genetic algorithms, Dijkstra's algorithm, and Floyd's algorithm typically rely on deterministic search strategies, which can lead to local optima and lack global search capabilities in dynamic settings. …”
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Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…CIoU Loss function was replaced by SIoU Loss function as the boundary box regression algorithm to improve the accuracy and rate of convergence of the boundary box regression. …”
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A Novel Method to Compute the Contact Surface Area Between an Organ and Cancer Tissue by Alessandra Bulanti, Alessandro Carfì, Paolo Traverso, Carlo Terrone, Fulvio Mastrogiovanni

“…Tested on synthetic data, the algorithm showed minimal error and was evaluated on data from 82 patients. …”
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Cardiac disease diagnosis based on GAN in case of missing data. by Xing Chen, Na Zhang, Xiaohui Yang, Chunyan Wang, Qi Na, Tianyun Luan, Wendi Zhu, Chenjie Zhang, Chao Yang

“…This approach establishes the missing data filling mechanism based on the generative adversarial networks, which ensures the rationality of the data distribution while filling the missing data samples. The experimental results demonstrate that compared to other filling algorithms, the data matrix filled by the proposed algorithm in this paper has more evident practical significance, fewer errors, and higher accuracy in downstream classification prediction.…”
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Nanodesigner: resolving the complex-CDR interdependency with iterative refinement by Melissa Maria Rios Zertuche, Şenay Kafkas, Dominik Renn, Magnus Rueping, Robert Hoehndorf

“…NanoDesigner integrates key stages—structure prediction, docking, CDR generation, and side-chain packing—into an iterative framework based on an expectation maximization (EM) algorithm. The algorithm effectively tackles an interdependency challenge where accurate docking presupposes a priori knowledge of the CDR conformation, while effective CDR generation relies on accurate docking outputs to guide its design. …”
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Analysis and mitigation of greenhouse gases by replacing traditional energy with a hybrid energy system using battery optimization by Madhusudhanan Sampath, Amalorpava Mary Rajee Samuel, Yamuna Devi M.M, Senthil Murugan

“…The paper presents an improved Lyapunov optimisation (LO) algorithm to optimally estimate the number of photovoltaic panels and battery banks for enhanced energy management. …”
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Complexity analysis and practical resolution of the data classification problem with private characteristics by David Pantoja, Ismael Rodríguez, Fernando Rubio, Clara Segura

“…In particular, a greedy algorithm and two genetic algorithms are presented. …”
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Sentiment Analysis using Support Vector Machine and Random Forest by Talha Ahmed Khan, Rehan Sadiq, Zeeshan Shahid, Muhammad Mansoor Alam, Mazliham Bin Mohd Su'ud

“…The Random Forest algorithm achieved an accuracy of 0.78564, while SVM outperformed it slightly with an accuracy of 0.80394. …”
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Detection and diagnosis of air compressor faults using weightless neural networks by Anubhab Bhattacharyya, Naveen Venkatesh Sridharan, Aravinth Sivakumar, Sugumaran Vaithiyanathan

“…The training process employs a versatile and effective algorithm aimed at generating reliable and accurate results. …”
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A High-Resolution Gridded Dataset for China’s Monthly Sectoral Water Use by Yuqian Zhang, Yunhe Yin, Mijia Yin, Xufang Zhang

“…HSWUD shows a strong correlation with prefecture-level statistical data (R2 = 0.88), while the captured spatiotemporal patterns are broadly consistent with existing datasets.…”
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LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…To address the challenges of detecting cotton pests and diseases in natural environments, as well as the similarities in the features exhibited by cotton pests and diseases, a Lightweight Cotton Disease Detection in Natural Environment (LCDDN-YOLO) algorithm is proposed. The LCDDN-YOLO algorithm is based on YOLOv8n, and replaces part of the convolutional layers in the backbone network with Distributed Shift Convolution (DSConv). …”
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A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response by Wenzhi Chen, Hongjian Sun, Minglei You, Jing Jiang, Marco Rivera

“…Firstly, a household device action recommendation algorithm is proposed that improves the knowledge graph attention algorithm to make accurate household appliance recommendations. …”
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Joint Allocation of Shared Yard Space and Internal Trucks in Sea–Rail Intermodal Container Terminals by Xiaohan Wang, Zhihong Jin, Jia Luo

“…Numerical experiments verify the model and algorithm performance, revealing that the proposed method achieves an optimality gap of only 1.82% compared to CPLEX in small-scale instances while outperforming benchmark algorithms in solution quality. …”
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STAR-RIS enabled covert integration of sensing communication and over-the-air computing with analysis and optimization by Miao Zhang, Chao Wang, Tianyu Ren, Jing Li

“…Simulations demonstrate that our algorithm surpasses benchmark schemes in convergence and robustness.…”
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Simulation Study: Trajectory Tracking Control of Parafoil System Based on Deep Reinforcement Learning by Xuepu Zhang

“…Secondly, the network structure of the MC-DSAC-T algorithm and the process of updating the network using sampling data were introduced. …”
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Hybrid PI and Fuzzy Logic Control for Energy Optimization in Train Operations by Hwan-Hee Cho, Jae-Won Kim, Min-Sup Song, Chi-Myeong Yun, Gyu-Jung Cho, Zhongbei Tian

“…This paper presents a Fuzzy logic-based train control algorithm designed to enhance energy efficiency across a complete railway route. …”
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Deep Learning Method with Domain-Task Adaptation and Client-Specific Fine-Tuning YOLO11 Model for Counting Greenhouse Tomatoes by Igor Glukhikh, Dmitry Glukhikh, Anna Gubina, Tatiana Chernysheva

“…This algorithm can be utilized in mobile video surveillance systems, enhancing monitoring efficiency in greenhouses.…”
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Substation Equipment Defect Detection Based on Improved YOLOv8 by Yiwei Sun, Xiangran Sun, Ying Lin, Yi Yang, Zhuangzhuang Li, Lun Du, Chaojun Shi

“…Finally, the Bottleneck component within YOLOv8’s C2f module is substituted with FasterBlock, which significantly accelerates inference speed while maintaining model accuracy. Experimental results on the substation equipment defect dataset demonstrate that the improved algorithm achieves a mean average precision (mAP) of 92.8%, representing a 1.8% enhancement over the baseline model. …”
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