Closed-Loop Clustering-Based Global Bandwidth Prediction in Real-Time Video Streaming by Sepideh Afshar, Reza Razavi, Mohammad Moshirpour

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NeIL: Intelligent Replica Selection for Distributed Applications by Faraz Ahmed, Lianjie Cao, Ayush Goel, Puneet Sharma

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High‐Precision Prediction of Ionospheric TEC in the China Region Based on CMONOC High‐Resolution Data and an Auxiliary Attention Temporal Convolutional Network by Jianghe Chen, Pan Xiong, Haochen Wu, Xiaoran Zhang, Xuemin Zhang, Rongzi Chai, Ting Zhang, Kaixin Wang, Chaoyu Wang

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Phase-Controlled Closing Strategy for UHV Circuit Breakers with Arc-Chamber Insulation Deterioration Consideration by Hao Li, Qi Long, Xu Yang, Xiang Ju, Haitao Li, Zhongming Liu, Dehua Xiong, Xiongying Duan, Minfu Liao

“…The test data are processed by the least squares method, adaptive switching algorithm, and machine learning method. …”
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Tool wear monitoring method based on AMIDBOAB and imbalanced data optimization by Guan-Hua Xu, Hong-Yu Wu, Bo Tang, Jun-Long Xu

“…Introducing circle chaotic mapping, Levy flight strategy, and adaptive variable inertia weight, a multiple improvement dung beetle optimizer algorithm is proposed to optimize the parameters of the base classifier in the adaptive boosting model. …”
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Diagnosis of citrus leaf canker disease based on naive Bayesian classification by SHU Meiyan, WEI Jiaxi, ZHOU Yeying, DONG Qizhou, CHEN Haochong, HUANG Zhigang, MA Yuntao

“…The results showed that the method based on naive Bayesian classification was effective in the segmentation of citrus leaf canker disease, and the incorrect segmentation rate was only 3.58%, which was far better than the threshold methods and support vector machine. In terms of performance efficiency, the time order of the four algorithms was fixed threshold method＜adaptive threshold＜naive Bayesian＜support vector machine, all of which were within a reasonable range. …”
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Efficient cutting stock optimization strategies for the steel industry. by Chattriya Jariyavajee, Suthida Fairee, Charoenchai Khompatraporn, Jumpol Polvichai, Booncharoen Sirinaovakul

“…The solution process involves three key steps: (i) Problem representation, where feasible cutting solutions are modeled based on pre-cut steel bars and customer orders, (ii) Problem space reduction, which reduces the problem space by eliminating suboptimal solutions and following manufacturer loss limits, and (iii) Optimal solution search, whereas the optimal solution is identified using a new Adaptive Pathfinding Optimization Algorithm. This algorithm combines a newly proposed Wandering Ant Colony Optimization with a brute force method, and uses specific conditions to determine which of these two approaches to be used to obtain the solution. …”
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Modeling and Implementing Two-Stage AdaBoost for Real-Time Vehicle License Plate Detection by Moon Kyou Song, Md. Mostafa Kamal Sarker

“…This paper proposes to automatical detection of car LPs via image processing techniques based on classifier or machine learning algorithms. In this paper, we propose a real-time and robust method for LPD systems using the two-stage adaptive boosting (AdaBoost) algorithm combined with different image preprocessing techniques. …”
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An Effective Method for Detecting Cyber Attacks on Computer Networks from the NSL-KDD Data Set by Shaik Aseena Babu, Reddy Rajeswara, Vullam Nagagopi Raju, Reddy Gondi Konda, Shaik Subhani

“…Adaptive methods such as machine learning can improve detection rates. …”
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Research on Fault Diagnosis Method of High-Speed EMU Air Compressor Based on ICEEMDAN and Wavelet Threshold Combined Noise Reduction by Liqiang Peng, Akang Guo, Shuzhao Zhang

“…The t-SNE manifold learning algorithm is applied for secondary feature extraction, creating an MPGA-SVM (Multi-Objective Genetic Algorithm-Support Vector Machine) fault diagnosis model. …”
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A Heavy-Haul Railway Corrugation Diagnosis Method Based on WPD-ASTFT and SVM by Binghuan Xiao, Jinzhao Liu, Ziyuan Zhang

“…The training and testing samples are classified using Support Vector Machine (SVM). The adaptive short-time Fourier transform (ASTFT) is incorporated with the Renyi entropy and the particle swarm optimization algorithm, which achieves a better aggregation of the time-frequency distribution and reduces the computation cost. …”
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Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit by Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

“…Firstly, Spatial Pyramid Matching (SPM) chaotic mapping, variable spiral strategy, Levy flight mechanism, and adaptive T-distribution variation perturbation strategy were utilized to enhance the DBO algorithm. …”
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基于Shannon熵的LCD-SVM方法在齿轮故障分类中的研究 by 李鹏宇, 邵忍平, 汪亚运

“…Local feature scale decomposition（Local characteristic scale decomposition,LCD）is a new adaptive time-frequency analysis method,which can adaptively decompose a complex signal into a number of ISC（Intrinsic scale component,ISC）components.SVM（support vector machine,SVM）is a kind of intelligent classification methods of machine learning,Shannon entropy is a nonlinear statistical learning methods.The LCD and SVM are introduced to the fault classification of mechanical transmission system.The Hilbert demodulation algorithm is used to strike the envelope signal of ISC components,through which the Shannon entropy is structured.After an in-depth analysis on the basis,it is combined with SVM in good relationship.The result is input vectors of SVM classifier,the trained SVM is used to determine the fault location,the type or degree of the test sample.Through the experimental analysis and verification,using this combining method,the recognition rate of four operating states which contains the normal state,the root crack of tooth,the wear of tooth surface,the composite fault is up to 97.5%.…”
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Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Second, a two-stage hybrid algorithm is proposed for the problem model. In the first stage, the deep neural network and the grid search improved support vector machine algorithm (DNN-GSM-SVM) are used to screen and classify customer priority features, and in the second stage, adaptive large-scale neighborhood search improved genetic algorithms (ALNS-GA) are used to solve the problem of vehicle-drone joint distribution path planning problem. …”
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Topology optimization of the plate using neural networks by Yu. S. Selivanov, K. A. Matveev

“…The method of adaptive moment estimation is used as an optimization algorithm directly by the parameter of the neural network. …”
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Research on navigation method in closed-canopy orchard based on 3D LiDAR by Zhigang ZHANG, Kaiyuan BAO, Wenyu ZHANG, Fan DING, Zongyi TONG, Fukang ZHOU

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Speculation resource provisioning in high-performance computing by Leena Sri, Balaji Narayanan

“…We have conveyed our proposed work in an open source cloud structure and contrasted our outcomes and other machine learning approaches. Our Experimental results demonstrate adaptive resource allocation over customer-driven service management under the rapidly changing requirements of cloud computing. …”
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A hybrid ensemble framework with particle swarm optimization for network anomaly detection by Narinder Verma, Neerendra Kumar, Gourav Kumar, Kuljeet Singh

“…By incorporating adaptive mechanisms within the PSO algorithm, our framework dynamically adjusts hyperparameters during optimization, enhancing model robustness and convergence speed. …”
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Dual Strategy Based Improved Swarm Intelligence and Stacked LSTM With Residual Connection for Land Use Land Cover Classification by Vinaykumar Vajjanakurike Nagaraju, Ananda Babu Jayachandra, Andrzej Stateczny, Swathi Holalu Yogesh, Raviprakash Madenur Lingaraju, Balaji Prabhu Baluvaneralu Veeranna

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Reversible Spectral Speech Watermarking with Variable Embedding Locations Against Spectrum-Based Attacks by Xuping Huang, Akinori Ito

“…Our experimental results demonstrate the efficacy of our proposed method in both sound quality preservation and log-likelihood value, indicating the absolute discontinuity of the spectrogram after embedding is proposed to evaluate the effectiveness of the proposed reversible spectral expansion watermarking algorithm. The result of EER indicated that the adaptive hiding performed best against attacks by spectral analysis.…”
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