The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

“…In the process of model training, cross-validation and grid search optimization methods are adopted to ensure the reasonable selection of super parameters. …”
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Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

“…The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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Machine learning based on patch antenna design and optimization for 5 G applications at 28GHz by Md․Sohel Rana, Sheikh Md․ Rabiul Islam, Sanjukta Sarker

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An integrated machine learning and hyperparameter optimization framework for noninvasive creatinine estimation using photoplethysmography signals by Parama Sridevi, Zawad Arefin, Sheikh Iqbal Ahamed

“…We integrated Optuna, a hyperparameter optimization framework, with every ML model to get the optimal hyperparameters. …”
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Machine learning with knowledge constraints for design optimization of microring resonators as a quantum light source by Parisa Sadeghli Dizaji, Hamidreza Habibiyan

“…This optimization model is developed specifically for single resonators made of silicon nitride. …”
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HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction by Madhusmita Das, Biju R. Mohan, Ram Mohana Reddy Guddeti

“…We strive to do this by designing a swarm-optimized machine learning defect prediction (SoMLDP) model within the HSoMLSDP framework. …”
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Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization by Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen

“…On this basis, a multi-objective intelligent optimization model is established to solve the optimized operating parameters of shield machine by non-dominated sorting genetic algorithm II and technique for order preference by similarity to ideal solution to reduce GS and improve drilling efficiency. …”
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Adaptive optimization of natural coagulants using hybrid machine learning approach for sustainable water treatment by Pallavi Randive, Madhuri S. Bhagat, Mangesh P. Bhorkar, Rajesh M. Bhagat, Shilpa M. Vinchurkar, Sagar Shelare, Shubham Sharma, N. Beemkumar, S. Hemalatha, Parveen Kumar, Ankit Kedia, Ehab El Sayed Massoud, Deepak Gupta, Jasmina Lozanovic

“…To overcome these obstacles, this research paper proposes advanced hybrid models in machine learning to enhance flocculation efficiency. …”
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Machine learning and population pharmacokinetics: a hybrid approach for optimizing vancomycin therapy in sepsis patients by Keyu Chen, Chuhui Wang, Yu Wei, Sinan Ma, Weijia Huang, Yalin Dong, Yan Wang

“…ABSTRACT Predicting vancomycin exposure is essential for optimizing dosing regimens in sepsis patients. While population pharmacokinetic (PPK) models are commonly used, their performance is limited. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…Findings: The optimized LightGBM model showed significant improvement in early CHD detection. …”
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Resource Optimization for Grid-Connected Smart Green Townhouses Using Deep Hybrid Machine Learning by Seyed Morteza Moghimi, Thomas Aaron Gulliver, Ilamparithi Thirumarai Chelvan, Hossen Teimoorinia

“…CSGTs with one to four bedrooms are investigated considering water systems and party walls. A deep Machine Learning (ML) model combining Long Short-Term Memory (LSTM) and a Convolutional Neural Network (CNN) is proposed to improve the performance. …”
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A Hybrid Approach to Traffic Incident Management: Machine Learning-Based Prediction and Patrol Optimization by Yusuf Sait Turkan, Mesut Ulu

“…This study presents a novel five-stage hybrid approach to the patrol assignment problem, which estimates the traffic accident-incident location, event time, and traffic incident duration based on machine learning algorithms. The successful prediction results are then used as inputs in the patrol assignment optimization model. …”
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Load Optimization for Connected Modern Buildings Using Deep Hybrid Machine Learning in Island Mode by Seyed Morteza Moghimi, Thomas Aaron Gulliver, Ilamparithi Thirumarai Chelvan, Hossen Teimoorinia

“…These results indicate that the proposed model provides robust load optimization, particularly in island mode, and highlight the potential of CSGBs for sustainable urban living.…”
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Machine learning for optimal parameter prediction in free space continuous-variable quantum key distribution by Dong Chen, Cheng Jin, Liu Ao, Chen Lanjian, Chen YuJie, Yin Peng, Wu TianYi

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Machine learning-based voice assistant: optimizing the efficiency of speech conversion for people with speech disorders by M.H. Antor, N.V. Chudinovskikh, M.V. Bachurin, A.A. Shurpikov, N.A. Khlebnikov, B.A. Bredikhin

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A Multi-Objective Approach for Optimizing Virtual Machine Placement Using ILP and Tabu Search by Mohamed Koubàa, Rym Regaieg, Abdullah S. Karar, Muhammad Nadeem, Faouzi Bahloul

“…Efficient Virtual Machine (VM) placement is a critical challenge in optimizing resource utilization in cloud data centers. …”
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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…We compared models trained on weekly log data against a single model trained on all weeks’ data. …”
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Multi-objective optimization of cushion gas design in underground gas storage using machine learning by Mohaddeseh Ahmadi Aghdam, Maryam Fazaeli, Mahdi Kanaani, Behnam Sedaee

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Machine learning optimization of environmental factors influencing biomass and nutritional composition in local algal species by Aisha Khan, Saleem Ullah, Rifat Ali, Mahwish Rehman, Said Moshawih, Khang Wen Goh, Long Chiau Ming, Lai Ti Gew

“…Machine learning was applied to optimize environmental conditions, with random forest (RF) identified as the most effective model. …”
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Optimization method of obstacle avoidance path for dual-arm cooperative robot based on machine vision by Jing Li

“…Abstract This study focuses on optimizing the obstacle avoidance path for a dual-arm cooperative robot using machine vision techniques, aiming to ensure that the robot can navigate around obstacles smoothly and swiftly. …”
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