Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

Subjects: “…Supervised machine learning…”
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Justification of the Gravitational Seed Cleaning System Parameters by V. G. Khamuev

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Investigating reduced-dimensional variability in aircraft-observed aerosol–cloud parameters by Kayley M. Butler, Sam J. Silva, Armin Sorooshian, Richard H. Moore, Glenn S. Diskin, John B. Nowak, Luke Ziemba, Ewan Crosbie, Michael A. Shook, Joshua DiGangi, Edward Winstead, Claire Robinson, Yonghoon Choi

“…Analysis of complex observed aerosol-cloud parameter relationships is a crucial piece of reducing this uncertainty. …”
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Digital Twin Framework for 5-axis Milling Machining by WANG Sibao, TANG Zhiyong, HU Yongda, WU Haoyu

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Intelligent Machine Learning Based Internet of Things (IoT) Resource Allocation by Koushik Chakraborty, Dhiraj Kapila, Sumit Kumar, Bhupati, Nazeer Shaik, Akanksha Singh

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Predicting intra-abdominal hypertension using anthropometric measurements and machine learning by Salar Tayebi, Rob Wise, Niels Van Regenmortel, Hilde Dits, Karen Schoonheydt, Inneke De laet, Luca Malbrain, Johan Stiens, Wojciech Dabrowski, Manu L. N. G. Malbrain

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Using Machine Learning for Recognition of Alzheimer’s Disease Based on Transcription Information by U. A. Vishniakou, Chu Yue Yu

Subjects: “…machine learning…”
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Study on the Impact of Input Parameters on Seawater Dissolved Oxygen Prediction Models by Wenqing Li, Jing Lv, Yuhang Wang, Xiangfeng Kong

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A Deep‐Learning Based Parameter Inversion Framework for Large‐Scale Groundwater Models by Amanda Triplett, Andrew Bennett, Laura E. Condon, Peter Melchior, Reed M. Maxwell

“…While there are still limitations for out of sample parameters, the general framework presented here provides a promising approach for parametrizing expensive models.…”
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Machine learning analysis of CO2 and methane adsorption in tight reservoir rocks by Mehdi Maleki, Mohammad Rasool Dehghani, Moein Kafi, Ali Akbari, Yousef Kazemzadeh, Ali Ranjbar

“…This research provides valuable insights for optimizing gas composition and operational parameters in storage applications, serving as a foundation for future studies in gas sequestration and reservoir engineering.…”
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Inversion Methods of Soil Hydraulic Parameters Based on Hyperspectral Characteristics by WU Yanmei, ZHU Han, LI Ji, LI Zixin, HE Jianliang, LIN Kairong, ZHUANG Luwen, DONG Chunyu

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Quantitative analysis of gait parameters in Parkinson’s disease and the clinical significance by Wenchao Yin, Hong Gao, Beichen Liang, Ruichen Liu, Yue Liu, Chenxin Shen, Xiaohui Niu, Cui Wang

“…We also used gait parameters as input features and MDS-UPDRS III score (which was further subdivided into tremor and non-tremor part score) as output labels to train machine learning regression models.ResultsWe found that except for cadence and stride time, most gait parameters of PD patients, including plantar dorsiflexion angle, plantar flexion angle, stride length, velocity were all smaller than those of the healthy controls. …”
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Design and Development of a Vertical Paddle Semi Automated Garri Frying Machine by C.P. Nwadinobi, J.C. Edeh, K.I. Mejeh

“…This work presents the development of a garri fryer and the performance evaluation of the machine at various operational parameters. The fryer throughput capacity, (TP)c and functional/drying efficiency, were used to evaluate the performance of the fryer. …”
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A Process Decision-Making Method for Planar Machining of Box-Type Components by Zhongkun Shi, Meifa Huang, Zhemin Tang, Zecheng Hu, Weihao Hu

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Design and Development of a Vertical Paddle Semi Automated Garri Frying Machine by C.P. Nwadinobi, J.C. Edeh, K.I. Mejeh

“…This work presents the development of a garri fryer and the performance evaluation of the machine at various operational parameters. The fryer throughput capacity, (TP)c and functional/drying efficiency, were used to evaluate the performance of the fryer. …”
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HEALTH CLAIM INSURANCE PREDICTION USING SUPPORT VECTOR MACHINE WITH PARTICLE SWARM OPTIMIZATION by Syaiful Anam, M. Rafael Andika Putra, Zuraidah Fitriah, Indah Yanti, Noor Hidayat, Dwi Mifta Mahanani

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Development of Machine Setting Calculation and Meshing Simulation Software for Oerlikon Cycloid Bevel Gear by Nie Shaowu, Deng Xiaozhong, Zhang Hua, Wei Bingyang, Li Jubo

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An efficient machine learning-enhanced DTCO framework for low-power and high-performance circuit design by Mingyang Liu, Zhengguang Tang, Hailong You, Cong Li, Guangxin Guo, Zeyuan Wang, Linying Zhang, Xingming Liu, Yu Wang, Yong Dai, Geng Bai, Xiaoling Lin

Subjects: “…Machine learning…”
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Rapid and Low-Cost Detection of Thyroid Dysfunction Using Raman Spectroscopy and an Improved Support Vector Machine by Xiangxiang Zheng, Guodong Lv, Guoli Du, Zhengang Zhai, Jiaqing Mo, Xiaoyi Lv

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Seven-parameter PEMFC model optimization using an battlefield optimization algorithm by Manish Kumar Singla, S.A. Muhammed Ali, Jyoti Gupta, Pradeep Jangir, Arpita, Ramesh Kumar, Reena Jangid, Mohammad Khishe

Subjects: “…Machine learning…”
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