A Lightweight Detection Method for Meretrix Based on an Improved YOLOv8 Algorithm by Zhongxu Tian, Sifan Hou, Xiaoxue Yue, Xuewen Hu

“…To address this issue, this paper proposes a lightweight detection method, YOLOv8-RFD, based on an improved YOLOv8 algorithm, tailored for clam sorting applications. …”
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Application of improved and efficient image repair algorithm in rock damage experimental research by Mingzhe Xu, Xianyin Qi, Diandong Geng

“…Additionally, we adopt deep separable convolutional networks to optimize the algorithm’s operational efficiency. Based on this, the analysis of rock damage is conducted using the repaired strain nephograms, achieving a closer correlation with the actual physical processes of rock damage compared to conventional digital image technology and acoustic emission techniques. …”
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RTL-Net: real-time lightweight Urban traffic object detection algorithm by Zhiqing Cui, Jiahao Yuan, Haibin Xu, Yamei Wei, Zhenglong Ding

“…Abstract Object detection algorithm in urban traffic using remote sensing images often suffers from high complexity, low real-time performance, and low accuracy. …”
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Research on a traffic flow statistical algorithm based on YBOVDT and SAM2 by Yuanyuan Wang, Zheng Ding, Jiange Liu, Kexiao Wu, Md Sharid Kayes Dipu, Tingmei Ma, Yonghao Ma, Haiyan Zhang

“…A comparative analysis with YOLO-v3,YOLO-v5, YOLO-v6,and YOLO-v8 algorithms indicated that, while balancing spatial and temporal resource consumption and accuracy, the proposed algorithm offers higher recognition accuracy and environmental adaptability. …”
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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
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CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…A hybrid machine learning algorithm was applied to predict the timing of Continuous Kidney Replacement Therapy initiation for patients with acute kidney injury. …”
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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…With the continuous research by domestic scholars, YOLO algorithm is also continuously iteratively optimized, and its ability to detect the objects of different sizes and shapes is significantly improved, which can adapt to the maturity degree, size and occlusion of fruits, and improve the detection performance in complex environments.…”
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Energy scheduling algorithm for urban rail active traction power supply system by ZHANG Chao, LI Hongbo, ZHAO Liying, HUANG Zihao, LUO Wenguang, WANG Xiong

“…The full power and constant voltage models were used to simulate the two different working conditions of the bidirectional converter, and the internal and external double-layer iterative algorithm was used to calculate the power flow. When all the bidirectional converters were in constant voltage mode, the minimum energy consumption of the whole network was taken to solve the output voltage equation of the traction substation and optimization model of inequation constraints. …”
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A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling by Ruochen Liu, Chenlin Ma, Wenping Ma, Yangyang Li

“…The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. …”
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Synthesis of Thinned Concentric Circular Antenna Arrays Using Modified TLBO Algorithm by Zailei Luo, Xueming He, Xuedong Chen, Xin Luo, Xiaoqing Li

“…Teaching-learning-based optimization (TLBO) algorithm is a new kind of stochastic metaheuristic algorithm which has been proven effective and powerful in many engineering optimization problems. …”
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A multi-objective optimized OLSR routing protocol. by Wenhong Wei, Huijia Wu, Ying He, Qingxia Li

“…Simulation results show that the proposed algorithm can effectively reduce packet loss and end-to-end delay while obtaining better results in HV and Spacing, two multi-objective optimization result evaluation metrics.…”
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Optimization of Vehicle Routing with Pickup Based on Multibatch Production by Hongtao Hu, Jiao Mo, Chengle Ma

“…In the second stage, the Particle Swarm Optimization (PSO) algorithm was used to allocate vehicles to each production batch. …”
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Artificial intelligence-driven modeling of biodiesel production from fats, oils, and grease (FOG) with process optimization via particle swarm optimization by Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau

“…The findings demonstrate the effectiveness of combining ML and optimization techniques to enhance biodiesel production efficiency while reducing costs and energy consumption.…”
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Universality in game-driven random walks with strategies generated by a genetic algorithm by Kouki Tsuji, Kenta Takashima, Yuzuru Sato, Takuma Akimoto

“…Each player follows a strategy categorized as either a mixed strategy or an adaptive strategy optimized via a genetic algorithm (GA) that analyzes the opponent’s past hands. …”
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A Multiobjective Cooperative Driving Framework Based on Evolutionary Algorithm and Multitask Learning by Xia Jiang, Jian Zhang, Qing-yang Li, Tian-yi Chen

“…Based on a multi-objective evolutionary algorithm, CAVs are denoted as a sequence to be searched in solution space, while a multitask learning neural network with adaptive loss function is implemented for optimization target feedback to surrogate the simulation test procedure. …”
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A Detailed Comparison of Two New Heuristic Algorithms Based on Gazelles Behavior by Emine Baş

“…In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. …”
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RESEARCH ON DYNAMIC PERFORMANCE OF GEAR SYSTEM BASED ON ORTHOGONAL DESIGN AND GENETIC ALGORITHM by WU ZhengWei, WU XunCheng, ZHANG JueCheng

“…Dynamic performance of gear system especially vibration was a typical nonlinear problem,while the vibration was closely related to the gear profile modification,the solving gear profile modification parameters was a nonlinear optimization problem. …”
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Minimum number oriented relay node deployment algorithm in two-tiered WSN by Chun-yu MIAO, Li-na CHEN, Guo-yong DAI, Fan YANG, Qing-zhang CHEN

“…Aiming at minimizing the number of relay nodes distributed in the sensing area while keeping the feasible communication with at least one relay node for every sensor node, two algorithms (i.e. the integral linear programming optimal algorithm and the heuristic algorithm) were proposed. …”
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Service chain deployment algorithms for deterministic end-to-end delay upper bound by Ze’nan WANG, Jiao ZHANG, Shuo WANG, Tao HUANG, F.Richard Yu

“…To solve the problem that the current service chain deployment algorithms cannot guarantee the delay of each packet passing through the service chain (SC), a SC deployment algorithm for deterministic end-to-end delay upper bound was proposed.First, the end-to-end delay bound of the SC was derived based on network calculus.Then, the deterministic end-to-end delay bound of the SC was achieved by collaboratively optimizing the routing of SC and the resource allocation of the virtual network function nodes in the SC.The experimental results show that the proposed algorithm can effectively improve the volume of accepted SC while guaranteeing that the end-to-end delay of each packet satisfies the delay requirements.…”
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Use of Diagnostic Algorithms for *NTRK* Fusion-Positive Tumors in Pathology Institutes in Switzerland by Holger Moch, Gieri Cathomas, Milo Frattini, Wolfram Jochum, Erik Vassella, Laurence de Leval, Joachim Diebold, Christian Britschgi, Thomas McKee, Lukas Bubendorf

“…As the detection of *NTRK* gene fusion opens up new treatment options for patients, it is vital to ensure that the detection methods and diagnostic algorithms in pathology institutes are optimized and of high quality. …”
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