Abnormal Electricity Consumption Behaviors Detection Based on Improved Deep Auto-Encoder by Nvgui LIN, Lanxiu HONG, Daoshan HUANG, Yang YI, Zhixuan LIU, Qifeng XU

“…Because the effective data characteristics are destroyed by the abnormal behaviors, the abnormal behaviors can be detected through comparing the difference between the reconstruction error and the detection threshold. To improve the feature extraction ability and the robustness of AE network, the sparse restrictions and the noise coding are introduced into the auto-encoder, and the hyper-parameters of AE network are optimized through the particle swarm optimization algorithm to improve the learning efficiency and generalization ability. …”
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High-efficiency MPPT Using ZVS quasi-resonant converter and PSO algorithm: Simulation and PIL validation by Souhail Barakat, Abdelouahed Mesbahi, Badr N’hili, Ayoub Nouaiti, Mohcine Abouyaakoub

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Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials by Murat İnce, Hatice Varol Özkavak

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Analytical and Geometric Foundations and Modern Applications of Kinetic Equations and Optimal Transport by Cécile Barbachoux, Joseph Kouneiher

“…By bridging entropy dissipation, optimal transport, and geometric analysis, our work offers a new perspective on stability, convergence, and structure in high-dimensional kinetic models and applications.…”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. The core of the research lies in enhancing the feature extraction capability of the model, optimizing the feature expression of the model by introducing the CBAM attention mechanism, and improving the original structure of the neck component. …”
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An Efficient Path Planning Algorithm Based on Delaunay Triangular NavMesh for Off-Road Vehicle Navigation by Ting Tian, Huijing Wu, Haitao Wei, Fang Wu, Jiandong Shang

“…This paper proposed an improved A* path planning algorithm based on a Delaunay triangular NavMesh model with off-road environment representation. …”
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Integrative machine learning approach for forecasting lung cancer chemosensitivity: From algorithm to cell line validation by Jinghong Chen, Yonglin Yi, Chunqian Yang, Haoxuan Ying, Jian Zhang, Anqi Lin, Ting Wei, Peng Luo

“…Therefore, predicting individual responses is critical for optimizing treatment outcomes and improving patient prognosis. …”
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YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…Replacing YOLOv8’s C2f module with C2f-DCNv3 increases the network’s ability to focus on the target region while lowering the amount of model parameters. The MSCA mechanism is added after the backbone’s SPPF module to improve the model’s detection performance by directing the network’s detection resources to the major road target detection zone. …”
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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…The algorithm is improved in three aspects: firstly, replacing part of the traditional convolutional layers by linear deformable convolution, and designing a new C2L module by optimizing the C2F module, so as to reduce the number of model parameters and maintain the detection accuracy at the same time. …”
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A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention by Yizong Wang, Zhengrong Xiao, Hong Wang, Fei Li, Jiya Tian

“…Discussion The algorithm provides an efficient tool for early and accurate identification of citrus Huanglong disease, which is of great practical significance for reducing pesticide misuse and improving the efficiency of orchard management, and also provides new ideas for the design of lightweight target detection models in agricultural scenarios.…”
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An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…Finally, it saves the loss and accuracy data during the training process and evaluates the accuracy of the model. In order to improve the training learning rate, Adam optimizer combining momentum algorithm and RMSprop algorithm is used to dynamically adjust the learning rate; the combination of the two algorithms makes the loss function converge to the lowest point faster. …”
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A device free high-precision indoor positioning and tracking method based on GMM-WKNN algorithm by Mumen Jiang, Jiangnan Yuan

“…Abstract To address the high deployment complexity and algorithmic intricacies associated with current indoor target localization and tracking methods, this paper presents a Wi-Fi CSI indoor localization and tracking algorithm that integrates a Gaussian Mixture Model (GMM) with Weighted K-Nearest Neighbors (WKNN) and Kalman filtering. …”
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Enhanced Hybrid Artificial Fish Swarm Algorithm for Three-Dimensional Path Planning Applied to Robotic Systems by Ilias Chouridis, Gabriel Mansour, Vasileios Papageorgiou, Michel Theodor Mansour, Apostolos Tsagaris

“…The improved AFSA incorporates a 3D model of 24 possible movement points to more realistically simulate real-world robot movement capabilities. …”
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Tuning of Kalman Filter Parameters via Genetic Algorithm for State-of-Charge Estimation in Battery Management System by T. O. Ting, Ka Lok Man, Eng Gee Lim, Mark Leach

“…This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. …”
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A Joint Optimization Method for Cooperative Detection Resources Based on Channel Capacity by Wenda Yang, Minggong Wu, Xiangxi Wen, Kexin Bi

“…Aiming at the shortcomings of ABC algorithm, its search strategy and parameter optimization method are improved. …”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…Experimental results show that the optimized model significantly improves the detection effect on small targets compared with the original YOLOv5 model. …”
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Emergency Scheduling Optimization Simulation of Cloud Computing Platform Network Public Resources by Dingrong Liu, Zhigang Yao, Liukui Chen

“…An emergency scheduling method of cloud computing platform network public resources based on genetic algorithm is proposed. With emergency public resource scheduling time cost and transportation cost minimizing target, initial population by Hamming distance constraints, emergency scheduling model, and the corresponding objective function improvement as the fitness function, the genetic algorithm to individual selection and crossover and mutation probability were optimized and complete the public emergency resources scheduling. …”
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Chinese Clinical Named Entity Recognition With Segmentation Synonym Sentence Synthesis Mechanism: Algorithm Development and Validation by Jian Tang, Zikun Huang, Hongzhen Xu, Hao Zhang, Hailing Huang, Minqiong Tang, Pengsheng Luo, Dong Qin

“…We applied the SSSS algorithm to the Robustly Optimized Bidirectional Encoder Representations from Transformers Pretraining Approach (RoBERTa) + conditional random field (CRF) and RoBERTa + Bidirectional Long Short-Term Memory (BiLSTM) + CRF models and evaluated our models (SSSS + RoBERTa + CRF; SSSS + RoBERTa + BiLSTM + CRF) on the China Conference on Knowledge Graph and Semantic Computing (CCKS) 2017 and 2019 datasets. …”
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Microgrid Load Forecasting Based on Improved Long Short-Term Memory Network by Qiyue Huang, Yuqing Zheng, Yuxuan Xu

“…In this paper, a load-forecasting algorithm for microgrid based on improved long short-term memory neural network (LSTM) is proposed. …”
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An Accurate Book Spine Detection Network Based on Improved Oriented R-CNN by Haibo Ma, Chaobo Wang, Ang Li, Aide Xu, Dong Han

“…This allows for a more accurate computation of anchor box aspect ratios that are better aligned with the book spine dataset, enhancing the model’s training performance. We conducted comparison experiments between the proposed model and other state-of-the-art models on the book spine dataset, and the results demonstrate that the proposed approach reaches an mAP of 90.22%, which outperforms the baseline algorithm by 4.47 percentage points. …”
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