Set-Based Differential Evolution Algorithm Based on Guided Local Exploration for Automated Process Discovery by Si-Yuan Jing

“…Thirdly, a fine-grained evaluation technique is designed to assign score to each node in a process model, which is employed to guide the local exploration and improve the efficiency of the algorithm. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…Our approach uses large language models (LLMs) to improve the accuracy of classifying different pavement types. …”
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Optimization of external container delivery and pickup scheduling based on appointment mechanism. by Pengfei Huang, Hao Wang, Fangjiao Tan, Yuyue Jiang, Jinfen Cai

“…The improved Ant Colony Optimization algorithm (IACO) incorporates a time window width impact factor and a time deviation consideration into its state transition rules, enhancing its adaptability. …”
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MSFA-YOLO: A Multi-Scale SAR Ship Detection Algorithm Based on Fused Attention by Zhao Liangjun, Ning Feng, Xi Yubin, Liang Gang, He Zhongliang, Zhang Yuanyang

“…In addition, the DenseASPP module is incorporated to enhance the model’s adaptability to ships of varying scales, improving its ca-pability to accommodate larger ships within lower model scales. …”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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Performance enhancement of drone LiB state of charge using extended Kalman filter algorithm by Kamal Anoune, Ismail El Kafazi, Anas El Maliki, Badre Bossoufi, Badr NASIRI, Hana Zekraoui, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

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Flex-route demand response transit scheduling based on station optimization by HU Di, JIN Wenzhou

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Robotic Tack Welding Path and Trajectory Optimization Using an LF-IWOA by Bingqi Jia, Haihong Pan, Lei Zhang, Yifan Yang, Huaxin Chen, Lin Chen

“…To overcome these challenges, a Lévy flight-enhanced improved whale optimization algorithm (LF-IWOA) was developed. …”
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Method for Increasing the Energy Efficiency of the Gear Teeth Cutting Process by Smoothing the Cutting Force Variation by Gabriel Radu Frumusanu, Mihail Bordeanu, Florin Susac

“…The available solutions for energy optimization in cutting processes mentioned are the improvement of manufacturing equipment, the optimization of processes, and appropriate production scheduling. …”
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A self-learning method with domain knowledge integration for intelligent welding sequence planning by Weidong Shen, Xuewen Wang, Juanli Li, Yong Wang, Xiaojun Qiao

“…To improve the interpretability of the results, domain knowledge was integrated into the construction and training processes of a self-learning model. …”
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Discrete Robustness Optimization on Emergency Transportation Network Based on Prospect Theory by Zheng-kun Zhang, Chang-feng Zhu, Qing-rong Wang, Jia-shan Yuan

“…Finally, a case study is exhibited to demonstrate the reasonability of the model, theory, and algorithm. The result shows that the path cluster with the better timeliness and robustness can be well obtained by using the prospect theory and improved genetic algorithm. …”
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Sentiment Analysis of Consumer Acceptance of Honda’s Digital Marketing Strategy Using Lexicon-Based Algorithm by Bartolomius Dias, Asma’ Khoirunnisa’, Yosef Budiman, Setiyawami Setiyawami

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Non-Vertical Well Trajectory Design Based on Multi-Objective Optimization by Xiaowei Li, Yu Li, Yang Wu, Zhaokai Hou, Haipeng Gu

“…By introducing multi-granularity reference vector generation and an information entropy-guided search direction adaptation mechanism, the performance of the algorithm in the complex target space is improved, and the three-stage wellbore trajectory is optimized. …”
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Advanced Cooperative Formation Control in Variable-Sweep Wing UAVs via the MADDPG–VSC Algorithm by Zhengyang Cao, Gang Chen

“…The algorithm not only optimizes multi-UAV formation control efficiency but also improves obstacle avoidance, attitude stability, and decision-making speed. …”
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High-Performance Mobility Simulation: Implementation of a Parallel Distributed Message-Passing Algorithm for MATSim by Janek Laudan, Paul Heinrich, Kai Nagel

“…This paper presents an architectural update to the MATSim traffic simulation framework, introducing a prototype that adapts the existing traffic flow model to a distributed parallel algorithm. The prototype is capable of scaling across multiple compute nodes, utilizing the parallel computing power of modern hardware. …”
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Synthetic Data-Based Algorithm Selection for Medical Image Classification Under Limited Data Availability by Maxim Zhabinets, Benjamin Tyler, Martin Lukac, Shinobu Nagayama, Ferdinand Molnár, Michitaka Kameyama

“…The Algorithm selection approach improves performance by dynamically choosing the optimal Algorithm for each input instance. …”
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Research on Adaptive Education Path Dynamic Programming Algorithm Based on Reinforcement Learning and Cognitive Graphs by Hongli Lou, Pin Yue, Jianwen Chen

“…By employing reinforcement learning algorithms, the system continuously refines its model based on learner feedback and past interactions. …”
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Crime Type Identification Using High-Order Deep Residual Network with Multiple Attention Algorithm by Dawei Qiu, Chang Liu, Yuangfeng Shang, Zixu Zhao, Jinlin Shi

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A algorithm for low light image enhancement in coal mine underground based on illumination constraints by Yuchen BAI, Zuohua MIAO, Houyou XU, Mengting WANG

“…Compared to the original model, it showed improvements of approximately 23.40%, 16.07%, and 20.45% in these metrics, demonstrating optimal image enhancement effectiveness.…”
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Improving SLICES crystal representation through CHGNet integration and parameter tuning by Bizhu Zhang, Kedeng Wu, Chang Zhang, Hang Xiao, Liangliang Zhu

“…To bridge this gap, we present an enhanced approach to the simplified line-input crystal-encoding system (SLICES) representation by incorporating the Crystal Hamiltonian Graph Neural Network (CHGNet) machine learning force field model. Comprehensive evaluations across multiple datasets (MP-20, MP21-40, and MOF) using different neighbor recognition algorithms (EconNN and CrystalNN) show that our approach outperforms the original in reconstructing structures with fewer than 20 atoms per unit cell, achieving up to a 1.34% improvement in reconstruction rate (from 92.55% to 93.89%). …”
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