Trajectory Compression Algorithm via Geospatial Background Knowledge by Yanqi Fang, Xinxin Sun, Yuanqiang Zhang, Jumei Zhou, Hongxiang Feng

“…At the same compression ratio, the proposed algorithm reduces the average water depth error by approximately 99.1% compared to the Douglas–Peucker (DP) algorithm, while also addressing the common problem of compressed trajectories potentially intersecting with obstacles in traditional trajectory compression methods.…”
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Road damage detection based on improved YOLO algorithm by Luyao Ma, Ming Chen

“…The dual-branch attention mechanisms enhance feature representation in channel and spatial dimensions, while the GIoU loss optimizes bounding box regression—yielding notable improvements, particularly in small object detection and bounding box localization accuracy. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
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An empirical study of the naïve REINFORCE algorithm for predictive maintenance by Rajesh Siraskar, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Ambarish Kulkarni

“…Abstract Reinforcement Learning (RL) is a biologically inspired, autonomous machine learning method. RL algorithms can help generate optimal predictive maintenance (PdM) policies for complex industrial systems. …”
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Using machine learning algorithms to predict colorectal cancer by Xingjian Xiao, Bo Hong, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Shiyou Liu, Xianglong Xu

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AI driven automation for enhancing sustainability efforts in CDP report analysis by Ramya Rangarajan, Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, Venyaa Venkataraman, Krithik Shankar

“…Abstract The need for sustainable practices in supply chains is becoming increasingly critical, as businesses face pressure to reduce their carbon footprint while maintaining operational efficiency. This paper proposes a novel hybrid approach that combines Genetic Algorithms (GA) with Long Short-Term Memory (LSTM) networks to optimize supply chain sustainability. …”
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A GAN-Based Method for Cognitive Covert Communication UAV Jamming-Assistance Under Fully Labeled Sample Conditions by Wenxuan Fu, Bo Li, Haipeng Wang, Haochen Gong, Xiang Lin

“…The numerical results show that, compared with the commonly used multi-objective optimization algorithm or nonlinear programming algorithm at present, this algorithm exhibits faster and more stable convergence, enabling the derivation of optimal mobile interference assistance schemes for cognitive CC systems.…”
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Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques by Poonam Saroha, Gopal Singh, Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Majed Alsafyani, Hamed Alsufyani

“…These dynamics are difficult for traditional systems to handle, but new developments in reinforcement learning and optimization may be able to help. The paper introduces a novel Demand Response (DR) method that integrates a Self-Adaptive Puma Optimizer Algorithm (SAPOA) with a Multi-Objective Deep Q-Network (MO-DQN), improving smart home energy consumption, cost, and user preferences management. …”
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Analysis of optimal configuration of energy storage in wind-solar micro-grid based on improved gray wolf optimization by Huang Qian, Huang Dengke, Cai Li, Xu Qingshan

“…Comparing the difference between energy storage without an installation and energy storage with improved algorithm, it is shown that the energy storage configuration of the improved gray wolf optimization improves the economy, efficient energy use, and revenue of the whole system.…”
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An AI-ISM Methodology for Structural Modeling of Sustainable Supply Chain Management Drivers by Reza Roshanpour, Mohammadreza Parsanejad, Mir Saman Pishvaee

“…To address these challenges, this study proposes a novel Hybrid AI-ISM methodology, integrating Genetic Algorithms (GA) to optimize the reachability matrix by minimizing transitivity violations and reciprocal inconsistencies. …”
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Advanced methodology for maximum torque point tracking of hybrid excitation PMSM for EVs by Mahmoud M. Elymany, Nadia A. Elsonbaty, Aymen FLah, Lukas Prokop, Habib Kraiem, Mohamed A. Enany, Ahmed A. Shaier

“…Additionally, the Multi-Objective Ant Lion Optimizer (MOALO) algorithm is used in two stages: first to optimize the hybridization ratio (HR) and base speed (N b ), and second to analyze the effect of varying the hybridization ratio while maintaining constrained output power. …”
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Design of a Lorentz Force Magnetic Bearing Group Steering Law Based on an Adaptive Weighted Pseudo-Inverse Law by Chenyu Wang, Lei Li, Weijie Wang, Yanbin Zhao, Baiqi Li, Yuan Ren

“…Incorporating spacecraft maneuvering requirements, a genetic optimization algorithm establishes the optimal mounting configuration under task constraints. …”
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Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

“…The experimental results show that the algorithm excels at solving the MOAEOSSP, outperforming competing algorithms across several metrics and demonstrating its effectiveness for complex optimization problems.…”
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Link Prediction in Social Networks Using the HTOA by Foad Asef, Vahid Majidnezhad, Mohammad-Reza Feizi-Derakhshi

“…This study introduces a novel approach to link prediction in social networks by employing the Heat Transfer Optimization Algorithm (HTOA) for topological feature selection. …”
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Advanced Queueing and Location-Allocation Strategies for Sustainable Food Supply Chain by Amirmohammad Paksaz, Hanieh Zareian Beinabadi, Babak Moradi, Mobina Mousapour Mamoudan, Amir Aghsami

“…<i>Methods:</i> The grasshopper optimization algorithm (GOA), a meta-heuristic algorithm inspired by the behavior of grasshopper swarms, is utilized to solve the model on a large scale. …”
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Shared energy storage planning based on the adjustable potential of data center based on visual IOT platform by Lei Su, Wanli Feng, Haoyu Ma, Mingjiang Wei, RuoShi Gu, Ziya Chen, Junda Qin

“…Within this framework, a room-level energy management model is designed, integrating adjustable potential for batch-computing workloads and air conditioning systems to optimize time-of-use power consumption. Based the two-stage stochastic optimization model, a improved L-shaped algorithm is proposed to solve the planning model effectively, reducing computational complexity through problem decomposition. …”
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Structure and dynamics analysis of brain functional hypernetworks based on the null models by Chen Cheng, Yao Li, Chunyan Wang, Yanli Yang, Hao Guo

“…Specifically, first, based on the original brain functional hypernetwork, this article proposed the optimized hyper dK-series algorithm with hyperedges to construct null models that preserved the different node attributes and hyperedge attributes of the original brain functional hypernetwork, respectively. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…This study proposes a multi-objective particle swarm optimization algorithm based on a dual-population coevolution strategy (DPMOPSO) to solve the optimization problem. …”
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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

“…A novel hybrid framework was put forth for consideration, comprising three distinct stages: Clustering, Parallel Filtering, and Hybrid-Parallel Optimization. In each step, a combination of techniques and algorithms is used to improve the results in terms of stability and/or accuracy. …”
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A Novel Traffic Scheduling Algorithm for Multi-CQF Using Mixed Integer Programming and Variable Neighborhood Search Genetic Algorithm in Time-Sensitive Networking by Cheng Wang, Zhiquan Lin, Yuhao Zhao, Fen Hu, Zhan Huan

“…Subsequently, Mixed Integer Programming (MIP) and the Variable Neighborhood Search Genetic Algorithm (VNS-GA) are employed to optimize transmission delay in small- and large-traffic TSN networks, respectively. …”
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