Information entropy based match field cutting algorithm by Peng-hao SUN, Ju-long LAN, Shao-jun ZHANG, Jun-fei LI

“…With the increasing diversity of network functions,packet classification had a higher demand on the number of match fields and depth of match table,which placed a severe burden on the storage capacity of hardware.To ensure the efficiency of matching process while at the same time improve the usage of storage devices,an information entropy based cutting algorithm on match fields was proposed.By the analysis on the redundancy of match fields and distribution pattern in a rule set,a match field cutting model was proposed.With the mapping of matching process to the process of entropy reduction,the complexity of optimal match field cutting was reduced from NP-hard to linear complexity.Experiment results show that compared to existing schemes,this scheme can need 40% less TCAM storage space,and on the other side,with the growing of table size,the time complexity of this algorithm is also far less than other algorithms.…”
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A practical guide to optimizing industrial thermal spraying through comparative multi-objective optimization by Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau

“…This paper applies three multi-objective optimization algorithms to determine optimal process parameters for high-velocity oxygen fuel (HVOF) thermal spraying. …”
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Algorithms for Railway Embedded Control Devices for Safety Manoeuvres by Beinaroviča Anna, Gorobetz Mikhail, Alps Ivars

“…This study is dedicated to solve manoeuvres making task while working on the station with no marshalling hump. …”
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Improved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems by Martins Akugbe Arasomwan, Aderemi Oluyinka Adewumi

“…A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. …”
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EULER AND EXPONENTIAL ALGORITHM IN VISCOELASTIC ANALYSES OF LAMINATED GLASS by Jaroslav Schmidt, Alena Zemanová

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A Vehicle Path Planning Algorithm: QDDG-RRT by Ruixin Zhang, Qing Xu, Kai Sun, Yi Liu, Ximming Zhu, Guo Zhang, Xiang Cheng

“…The Rapidly-exploring Random Tree (RRT) algorithm, while widely used, suffers from slow search speeds, numerous inflection points, and redundant operations. …”
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Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms by Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang, Yaolong Duan

“…In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize flow aggregation. …”
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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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Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…Based on the multi-scale mean-shift clustering algorithm, Adaptive Kernel Density Estimation (AKDE) is introduced to map density to bandwidth, achieving adaptive adjustment of clustering bandwidth while reducing computational resources and improving cloud hierarchy. …”
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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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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…This study highlights the utility of evolutionary algorithms to generate feature sets that enhance the performance of interpretable machine learning models.…”
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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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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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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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Nonlinear Narrowband Active Noise Control for Tractors Based on a Momentum-Enhanced Volterra Filter by Tao Zhang, Zhixuan Guan, Shuai Zhang, Kai Song, Boyan Huang

“…The proposed approach integrates the nonlinear representation power of the Volterra filter with a momentum optimization mechanism to enhance convergence speed while maintaining robust steady-state accuracy. …”
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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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Study on Trajectory Planning for Polishing Free-Form Surfaces of XY-3-RPS Hybrid Robot by Xiaozong Song, Junfeng An, Xingwu Ma

“…Additionally, a hybrid optimization framework combining a genetic algorithm (GA) and local search (LS) is proposed to address the challenges of balancing global optimization with local fine-tuning in traditional trajectory planning methods. …”
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Two-Stage Uncertain UAV Combat Mission Assignment Problem Based on Uncertainty Theory by Haitao Zhong, Rennong Yang, Aoyu Zheng, Mingfa Zheng, Yu Mei

“…The proposed modified PSO exhibits superior performance compared with the ant colony optimization algorithm, enabling the acquisition of an optimal allocation scheme with greater benefits. …”
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Minimization of total costs for distribution systems with battery energy storage systems and renewable energy sources by Thai Dinh Pham, Thang Trung Nguyen, Le Chi Kien

“…Besides, this work also suggests an open-source simulator (OpenDSS) for addressing the power flow problem and develops a co-simulation between two active software (OpenDSS and MATLAB) through the component object model (COM) interface for addressing the continuous optimization problems. The proposed solution by MCOA has demonstrated superiority over other methods through total cost savings of up to 24.13% and 27.46% in IEEE 123-bus UDS and 55-bus BDS, while the values are only 23.11% and 26.50% for salp swarm algorithm (SSA) and 23.76% and 26.78% for coyote optimization algorithm (COA), respectively, as compared to the original cases. …”
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