Optimizing Intrusion Detection in IoMT Networks Through Interpretable and Cost-Aware Machine Learning by Abdelatif Hafid, Mohamed Rahouti, Mohammed Aledhari

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Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

“…This research attempts to take a machine learning approach to find the right model for process optimization. …”
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Enhancing Multi-Disease Prediction with Machine Learning: A Comparative Analysis and Hyperparameter Optimization Approach by Mariam Kili Bechir, Ferhat Atasoy

“…In conclusion, this study highlights the potential of machine learning and hyperparameter optimization for multi-disease prediction and underlines the importance of model selection.…”
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Optimizing energy forecasts at Boma for 2023 to 2053 Using machine learning techniques of the PSO algorithm by André Mampuya Nzita, Bernard Ndaye Nkanka, Guyh Dituba Ngoma, Clément N’zau Umba-di-Mbudi

“…Keywords: Optimization, energy forecasting, PSO algorithm, machine learning techniques, energy management…”
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MSPO: A machine learning hyperparameter optimization method for enhanced breast cancer image classification by Haonan Li, Vijay Govindarajan, Tan Fong Ang, Zaffar Ahmed Shaikh, Amel Ksibi, Yen-Lin Chen, Chin Soon Ku, Ming Chern Leong, Fatiha Hana Shabaruddin, Wan Zamaniah Wan Ishak, Lip Yee Por

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Structural Parameter Analysis and Optimization of Six-link Double-crank Slider Mechanism of Stamping Machine by Liu Shanmin, Wu Ziyue, Liu Shanzeng

“…Secondly,based on the proposed optimization design mathematical model and MATLAB software,the optimization design,kinematics simulation analysis and kinematic characteristics of the six-link double crank slider mechanism are carried out. …”
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Global atomic structure optimization through machine-learning-enabled barrier circumvention in extra dimensions by Casper Larsen, Sami Kaappa, Andreas Lynge Vishart, Thomas Bligaard, Karsten Wedel Jacobsen

“…The new degrees of freedom are incorporated in a machine-learning model through a vectorial fingerprint trained using density functional theory energies and forces. …”
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A Discrete-time Neural Network for Solving Convex Optimization Problem in Support Vector Machine by LIU Feng-qiu, ZHANG Hong-xu

“…This paper proposes a discrete-time neural network model to solve the convex optimization problem deduced by a positive-kernel-based support vector machine ( SVM) . …”
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Intelligent Fault Severity Detection of Rotating Machines Based on VMD-WVD and Parameter-Optimized DBN by Ning Jia, Yao Cheng, Youyuan Tian, Feiyu Yang

“…Experiments show that, based on VMD-WVD and SSA-DBN, accuracy of the fault severity detection model for rotating machines, which has good generalization ability and robustness, can reach 98%. …”
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Experimental Study of an Approximate Method for Calculating Entropy-Optimal Distributions in Randomized Machine Learning Problems by Alexey Yu. Popkov, Yuri A. Dubnov, Ilya V. Sochenkov, Yuri S. Popkov

“…This paper is devoted to the experimental study of the integral approximation method in entropy optimization problems arising from the application of the Randomized Machine Learning method. …”
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Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach by Mohamed Koubàa, Abdullah S. Karar, Faouzi Bahloul

“…This paper introduces a novel model for virtual machine (VM) requests with predefined start and end times, referred to as scheduled virtual machine demands (SVMs). …”
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Static Topology Optimization and Dynamic Characteristics Analysis of 6000T Compression-Shear Test Machine Frame by Genshang Wu, Beibei Cui, Yanmin Li, Jinggan Shao, Zhanshu He, Shusen Zhao, Chao Li, Jinlong Yu

“…Then, taking the volume of the frame of the compression-shear testing machine as the constraint condition, the topology optimization of the compression-shear testing machine frame is performed using the variable density method of topology optimization, and the model is reconstructed accordingly. …”
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Optimization of machining process route for internal joint parts using artificial fish swarm algorithm by Jun HAN, Junwei ZHU, Yang ZHANG, Zhenyao ZHAO, Zexi AN

“…A reasonable constraint matrix model is constructed. The objective function is to determine the minimum number of machine tool, cutting tool, and clamping type changes. …”
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Machining characteristics and process parameter optimization of Near-dry electrical discharge milling of titanium alloy by Shaopeng Kang, Xianghua Zhuo, Linglei Kong, Yanxin Li, Yafeng He

“…The near-dry electrical discharge milling (N-EDM) method, which removes excess material via electroerosion, mitigates the impact of titanium alloy’s hardness and strength, enabling effective material cutting. To enhance machining efficiency and surface quality, this study employs a simulation model of the inter-electrode flow field, combined with experimental data, to investigate the effect of milling thickness on key machining parameters and determine the optimal thickness. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…Our approach employs advanced machine learning techniques, including multi-output regression models (Ridge, Lasso, Random Forest, Gradient Boosting, and XGBoost) to predict optimal docking configurations for novel ligands. …”
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Voltage Optimal Control Strategy for Distribution Networks with Multiple Integrated Photovoltaic and Energy Storage Machines by Jinglin HAN, Ping HU, Ruosong HOU, Zhiyong CHEN, Hongtao LI, Yuanyuan CHAI

“…Firstly, a centralized rolling optimization model is established to formulate the voltage and power references of PV-ES machine in the next period. …”
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Optimized machine learning mechanism for big data healthcare system to predict disease risk factor by Venkata Nagaraju Thatha, Silpa Chalichalamala, Udayaraju Pamula, D. Pramodh Krishna, Manjunath Chinthakunta, Srihari Varma Mantena, Shariff Vahiduddin, Ramesh Vatambeti

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Quantum algorithms and complexity in healthcare applications: a systematic review with machine learning-optimized analysis by Agostino Marengo, Vito Santamato

“…This paper presents a systematic review of quantum computing approaches to healthcare-related computational problems, with an emphasis on quantum-theoretical foundations and algorithmic complexity. We adopt an optimized machine learning methodology—combining Particle Swarm Optimization (PSO) with Latent Dirichlet Allocation (LDA)—to analyze the literature and identify key research themes at the intersection of quantum computing and healthcare. …”
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Optimization of drilling parameters to minimize delamination in CNT-filled GFRP composites using machine learning by Aveen K P, Ullal Vignesh Nayak, K M Pranesh Rao, Shivaramu H T, V Londhe Neelakantha, Shashikumar C M

“…Torque (T) and thrust force (F) were measured using a digital drilling machine with a dynamometer. A machine learning based multi-output random forest regression model with hyper parameter tuning was used to predict the T, F, and delamination factor (Fd). …”
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Optimizing space heating efficiency in sustainable building design a multi criteria decision making approach with model predictive control by Zheng Qi, Nan Zhou, Xianwei Feng, Sama Abdolhosseinzadeh

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