A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity by Xue-Yang Pei, Yuan Hou, Hai-Bin Huang, Jun-Xing Zheng

“…To address this challenge, this study proposes a multi-objective sensor placement optimization method based on the Non-Dominated Sorting Genetic Algorithm. …”
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A Judging Scheme for Large-Scale Innovative Class Competitions Based on Z-Score Pro Computational Model and BP Neural Network Model by Zhuoting Yu, Hongzhong Deng, Shuaiwen Tang

“…The model employs a genetic algorithm to maximize the overlap between experts while ensuring a balanced distribution of evaluation tasks, thus reducing the entropy generated by imbalances in the process. …”
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Real-Time Estimation of the State of Charge of Lithium Batteries Under a Wide Temperature Range by Da Li, Lu Liu, Chuanxu Yue, Xiaojin Gao, Yunhai Zhu

“…The results indicate that creating a database that accommodates temperature variations and optimizing dual Kalman filtering through the cat swarm optimization algorithm significantly improves <i>SOC</i> estimation accuracy.…”
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Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…Preprocessing techniques are first applied to eliminate noise and enhance image quality. The OWSO algorithm is then integrated to optimize the classification performance of MEfficientNetV2, while PCA accelerates the learning process by retaining critical features in the thresholds of the varying components. …”
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Application of Improved BQGA in Robot Kinematics Inverse Solution by Xiaoqing Lv, Ming Zhao

“…In addition, the improved algorithm further completes the anti-degradation mechanism, which maintains the diversity of the population while preserving the dominant gene to the maximum extent, so that the algorithm is not easy to fall into the local extremum and finally approaches the global optimal solution. …”
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Precise wind allocation scheme decision based on attraction-repulsion algorithm by NI Jingfeng, CHEN Dunwei, LIU Yujiao

“…Performance test results showed that AROA had a significant advantage in comprehensive optimization performance compared to Genetic Algorithm (GA), Simulated Annealing-Improved Particle Swarm Optimization (SA-IPSO), and Monotonic Basin Hopping (MBH). …”
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Credit Rating Model Based on Improved TabNet by Shijie Wang, Xueyong Zhang

“…To further enhance classification and predictive performance, a stacked ensemble learning approach is implemented: the improved TabNet serves as the feature extractor, while XGBoost (Extreme Gradient Boosting), LightGBM (Light Gradient Boosting Machine), CatBoost (Categorical Boosting), KNN (K-Nearest Neighbors), and SVM (Support Vector Machine) are selected as base learners in the first layer, with XGBoost acting as the meta-learner in the second layer. …”
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Improved Block Element Method for Simulating Rock Failure by Yan Han, Qingwen Ren, Lei Shen, Yajuan Yin

“…The iterative control index can effectively improve the geometric characteristics of the grid while maintaining the necessary randomness. …”
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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…The image was divided into superpixel regions using SLIC (Simple Linear Iterative Clustering) algorithm, and local features such as texture, contrast, and edge intensity were extracted; in the SRGAN model, the generator improved image resolution through deep residual blocks and Convolutional Neural Network (CNN), while the discriminator optimized the generated image quality through adversarial training; at the same time, a Fuzzy Logic System (FLS) was constructed to dynamically adjust the image fuzzy degree; channel and spatial attention modules in the generator were integrated to enhance key area details. …”
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Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons by Coulon Romain

“…The Genetic Algorithm (GA), a novel optimization-based approach, demonstrates exceptional resilience to outliers. …”
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IMPROVING EFFICIENCY OF RADIO MAINTENANCE TO ENSURE SAFETY by V. E. Emelyanov, I. A. Polotnyanschicov

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EGNAS: Efficient Graph Neural Architecture Search Through Evolutionary Algorithm by Younkyung Jwa, Chang Wook Ahn, Man-Je Kim

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Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

“…Building upon the RT-DETR framework, this study proposes a Multiscale Separable Deformable (MSD) module that integrates depthwise convolution with deformable convolution to enhance feature extraction capabilities while reducing computational load. Additionally, a Deformable Agent Attention (DAA) mechanism is designed to optimize attention weights through sparse queries, effectively improving detection accuracy for small targets and enhancing inference speed in complex scenarios. …”
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Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…The neck structure is enhanced with a collaborative attention mechanism and multi-scale fusion, improving feature representation. An optimized loss function refines bounding box matching for small targets, while a pruning strategy removes redundant filters, boosting computational efficiency. …”
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Topology optimization of a cargo gripper design using the minimum effort principle by Gnezdilov S.G.

“…The primary goal of the research is to enhance the stiffness and reliability of the structure while reducing its mass. The left gripper arm, subjected to complex loading conditions, is selected as the optimization object. …”
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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

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Evolutionary search algorithm for learning activation function of an artificial neural network by Yurshin Viacheslav

“…The proposed method aims to enhance the efficiency of the search process for optimal activation functions. Our algorithm employs genetic programming to evolve the general form of activation functions, while gradient descent optimizes their parameters during network training. …”
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Observation optimization for marine target tracking by airborne and maritime unmanned platforms cooperation using adaptive enhanced dung beetle optimization by Qiuyang Dai, Faxing Lu, Haoran Shi, Junfei Xu, Jianjing Qu

“…Abstract Cooperative observation optimization for maritime targets is crucial for improving marine monitoring precision. …”
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FDR coding and decoding algorithm for reliable transmission in underwater acoustic network by Lijuan WANG, Xiujuan DU, Chong LI

“…By analyzing the shortcomings of RLT coding and decoding algorithm,a filtering dimension reduction (FDR) algorithm was proposed,which eliminated the waiting time of the traditional decoding algorithm and achieves fast decoding.In addition,XOR operation between encoded packages effectively increased the number of one-degree encoded packages,and improved decoding probability while reducing transmission delay.An optimized degree distribution function for FDR decoding algorithm was proposed,which increased the proportion of two-degree,three-degree and four-degree encoded packages,further increased the probability of one-degree packet,so that speeded up the decoding progress.Simulation results with NS3 show that the decoding success probability of FDR algorithms higher than RLT algorithm.…”
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SynthSecureNet: An Improved Deep Learning Architecture with Application to Intelligent Violence Detection by Ntandoyenkosi Zungu, Peter Olukanmi, Pitshou Bokoro

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