Fault Diagnosis Research on Bearingof Motor Based on LMD And Support Vector Machine by YIN Zhao-jie, XU Tong-le, ZHENG Dian-kun

“…Firstly，the local mean decomposition ( LMD) algorithm is used to adaptively decompose the signal to get a series of PF components ，and the correlation analysis is used to eliminate false components. …”
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Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

“… This study addresses the crucial issue of predicting student performance in educational data mining (EDM) by proposing an Adaptive Dimensionality Reduction Algorithm (ADRA). …”
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UAV Real-Time Target Detection and Tracking Algorithm Based on Improved KCF and YOLOv5s_MSES by Shihai Cao, Ting Wang, Tao Li, Shumin Fei

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Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

“… This study addresses the crucial issue of predicting student performance in educational data mining (EDM) by proposing an Adaptive Dimensionality Reduction Algorithm (ADRA). …”
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Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks by Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang

“…Existing research on multilayer IoT attacks exhibits gaps in real-world applicability, due to reliance on outdated datasets with a limited focus on adaptive, dynamic approaches to address multilayer vulnerabilities. …”
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Neuro-fuzzy techniques for modeling process parameters in pulsed electrochemical machining of steel by Irvin Uriel Nopalera Angeles, Everardo Efrén Granda Gutiérrez, Roberto Alejo Eleuterio, René Arnulfo García Hernández, Ángel Hernández Castañeda, María Guadalupe Pineda Arizmendi

“…This algorithm performs inference-based mapping using fuzzy logic while adaptively adjusting parameters through a supervised criterion, as in neural networks. …”
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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…This review synthesizes key advancements in biofuel optimization, highlighting the use of techniques such as Artificial Neural Networks (ANN), Genetic Algorithms (GA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and Response Surface Methodology (RSM). …”
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Available Transfer Capability Calculation Constrained with Small-Signal Stability Based on Adaptive Gradient Sampling by Peijie Li, Ling Zhu, Xiaoqing Bai, Hua Wei

“…The highlighted feature is the sample size of the gradient changes dynamically in every iteration, yielding an adaptive gradient sampling (AGS) process. Thus, the computing efficiency is greatly improved owing to the decrease and the parallelization of gradient evaluation, which dominates the computing time of the whole algorithm. …”
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Cloud computing virtualization technology based on bandwidth resource-aware migration algorithm by Jin Zhiwei

“…The algorithm monitors bandwidth usage in real-time, identifying potential bottlenecks and considering both resource utilization and bandwidth availability when determining whether to migrate virtual machines. …”
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Replica exchange enhanced adaptively weighted stochastic gradient Langevin dynamics for Bayesian sampling and optimization by Zhenqing Wu, Wenwu Gong, Ziying Yu, Liuxin Zhu, Lili Yang

“…Abstract We propose the replica exchange adaptively weighted stochastic gradient Langevin dynamics (REAWSGLD) algorithm, designed explicitly for Bayesian learning with complex energy landscapes encountered in big data problems. …”
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Improving neural network training using dynamic learning rate schedule for PINNs and image classification by Veerababu Dharanalakota, Ashwin Arvind Raikar, Prasanta Kumar Ghosh

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Concrete Crack Skeleton Analysis: A Machine Vision Approach to Feature Extraction by Rui Wang, Xinxin Guo, Jiaxuan Liu, Yu Wan

“…The test data show that the algorithm has good adaptability and the accuracy is higher than 90%. …”
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Resource Adaptive Automated Task Scheduling Using Deep Deterministic Policy Gradient in Fog Computing by Prashanth Choppara, S. Sudheer Mangalampalli

“…This paper presents a novel adaptive scheduling framework based on the DDPG algorithm for task scheduling optimization in fog computing environments. …”
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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

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A Comparison of Approaches for Handling Concept Drifts in Data Processed With Machine Learning by Emanuel Valerio Pereira, Wendley Souza da Silva

“…The study encompasses a comparative exploration of different classification algorithms within the scikit-multiflow framework. These algorithms integrate adaptive strategies to contend with concept drifts. …”
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The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review by Wilhelm Grzesiak, Daniel Zaborski, Marcin Pluciński, Magdalena Jędrzejczak-Silicka, Renata Pilarczyk, Piotr Sablik

“…The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). …”
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Forecasting Delivery Time of Goods in Supply Chains Using Machine Learning Methods by V. K. Rezvanov, O. M. Romakina, E. V. Zaytseva

“…The presented study aims to fill these gaps and demonstrate the efficiency of using open, accessible data and known algorithms. The research objective is to describe a pattern of appropriate selection of the least resource-intensive delivery forecasting model based on the analysis of machine learning algorithms.Materials and Methods. …”
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Comparison of Deep Learning Sentiment Analysis Methods, Including LSTM and Machine Learning by Jean Max T. Habib, A. A. Poguda

“…In general, both deep classification algorithm. A combination of both approaches can also learning and feature-based selection methods can be used to solve be used to further improve the efficiency of the algorithm. some of the most pressing problems. …”
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Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing by Katarzyna Antosz, Lucia Knapčíková, Jozef Husár

“…A variety of classification algorithms, including neural networks (NNs), bagged trees (BT), and support vector machines (SVMs), were employed to efficiently analyse and predict defects. …”
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Machine Learning for Human Activity Recognition: State-of-the-Art Techniques and Emerging Trends by Md Amran Hossen, Pg Emeroylariffion Abas

“…Additionally, addressing ethical considerations, such as privacy and algorithmic fairness, remains a priority as HAR systems become more pervasive. …”
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