Programming of adaptive machining for end milling by Y. Petrakov, D. Shuplietsov

“…The developed algorithms automatically search for the correction of the CNC-program for implementing the principle of adaptive machining solution of the problem of minimax. …”
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Optimal design of hollow conductor for high‐speed synchronous motor exploiting adaptive‐sampling radial basis function algorithm by Ruiye Li, Peng Cheng, Hai Lan

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Electrical Equivalent Circuit Parameter Estimation of Commercial Induction Machines Using an Enhanced Grey Wolf Optimization Algorithm by Premkumar Manoharan, Sowmya Ravichandran, Jagarapu S. V. Siva Kumar, Mustafa Abdullah, Tan Ching Sin, Tengku Juhana Tengku Hashim

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Optimization Algorithm of Neural Network Structure Based on Adaptive Genetic Algorithm by XILiang, WANGRui dong

“…The structural design of neural network is one of the hot issues in neural network research The number of hidden layers and nodes has a great influence on the convergence speed and generalization ability of neural network Genetic algorithm is an adaptive optimization probability search algorithm formed by simulating biological heredity and evolution Its core idea is derived from the natural law of biological genetics and survival of the fittest, and it is a search algorithm with the iterative process of “survival + detection” However, the selection of genetic algorithm parameters is subjective, slow convergence and easy to fall into premature convergence To solve these problems, an adaptive genetic algorithm is proposed to find the optimal neural network structure The adaptive genetic algorithm selects the first n optimal individuals and adds a certain amount of random individuals in the optimization process of each iteration to update the population, and selfadaptive optimization of the search step size of the population can ensure the diversity of the population and improve the convergence rate at the same time Then we code and the structure of neural network processing, adaptive genetic algorithm, neural network structure optimization, so as to make the neural network as soon as possible to find the optimal network structure and parameters, in order to improve the accuracy of neural network. …”
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Using SABC Algorithm for Scheduling Unrelated Parallel Batch Processing Machines Considering Deterioration Effects and Variable Maintenance by Ziyang Ji, Jabir Mumtaz, Ke Ke

Subjects: “…self-adaptive artificial bee colony algorithm…”
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An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis by Hao Yan, Liangliang Shang, Wan Chen, Mengyao Jiang, Tianqi lu, Fei Li

“…Subsequently, the hierarchical hybrid kernel extreme learning machine (HHKELM) is refined through an enhanced Aquila Optimizer (AO) algorithm, which iteratively optimizes the kernel hyperparameter combination. …”
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Utilizing an Innovative Gaussian Process Regression Machine Learning Algorithm for Estimating Unconfined Compressive Strength Predictions by Hazel Abraham

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A computer vision system and machine learning algorithms for prediction of physicochemical changes and classification of coated sweet cherry by Yashar Shahedi, Mohsen Zandi, Mandana Bimakr

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Real-Time Head Orientation and Eye-Tracking Algorithm Using Adaptive Feature Extraction and Refinement Mechanisms by Ming-Chang Ye, Jian-Jiun Ding

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Assessment of future urban flood risk of Thailand's bangkok metropolis using geoprocessing and machine learning algorithm by Duangporn Garshasbi, Jarunya Kitiphaisannon, Tanaphoom Wongbumru, Nawhath Thanwiset Thanvisitthpon

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High frequency resonance mitigation of microgrid-connected PV units using novel adaptive control based on virtual impedance and machine learning algorithm by Mohammad Hossein Nemati, Mohammad Hossein Shaabani, Navid Dehghan, Gevork B. Gharehpetian

“…This study proposes a novel adaptive control framework that combines virtual impedance (VI) methods with a machine learning-based tuning strategy using K-Nearest Neighbors (KNN) algorithm. …”
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Recent Progress in Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes by Sheng Du, Zixin Huang, Li Jin, Xiongbo Wan

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Adaptive predator prey algorithm for many objective optimization by Nikunj Mashru, Kanak Kalita, Lenka Čepová, Pinank Patel, Arpita, Pradeep Jangir

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Enhancing Cloud Security: A Multi-Factor Authentication and Adaptive Cryptography Approach Using Machine Learning Techniques by K. Sasikumar, Sivakumar Nagarajan

“…This article introduces a novel multi-factor authentication system integrated with a hybrid cryptographic framework that dynamically changes encryption algorithms using machine learning techniques based on an intrusion-detection system. …”
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A Model for Detecting <i>Xanthomonas campestris</i> Using Machine Learning Techniques Enhanced by Optimization Algorithms by Daniel-David Leal-Lara, Julio Barón-Velandia, Lina-María Molina-Parra, Ana-Carolina Cabrera-Blandón

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A simulation-driven computational framework for adaptive energy-efficient optimization in machine learning-based intrusion detection systems by Ripal Ranpara, Osamah Alsalman, Om Prakash Kumar, Shobhit K. Patel

“…In the proposed research paper study, by integrating advanced machine learning techniques such as random forest classifier and support vector machines classifier with knowledge distillation and adaptive energy-aware optimization, GreenMU achieves a balanced trade-off between computational efficiency and cybersecurity accuracy. …”
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Using machine learning algorithms to predict colorectal polyps by Xingjian Xiao, Shiyou Liu, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Xianglong Xu

“…In our study, the AUC of Random Forest and eXtreme Gradient Boosting reached 0.71, Adaptive Boosting Machine, Gradient Boosting Machine and Light Gradient Boosting Machine reached 0.7 in predicting the occurrence of colorectal cancer. …”
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Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses by Esra Imamoglu

“…Commonly employed ML algorithms, including the support vector machine (SVM), genetic algorithm (GA), decision tree (DT), random forest (RF), artificial neural network (ANN), and deep learning (DL), each have unique strengths but also present challenges, such as computational demands, overfitting, and transparency. …”
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Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

“…Machine learning (ML) is used in developing adaptive intelligent systems that can perform complex tasks beyond human abilities. …”
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Using machine learning algorithms to predict colorectal cancer by Xingjian Xiao, Bo Hong, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Shiyou Liu, Xianglong Xu

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