Machine-learning-driven feature importance analysis for guiding the protonic ceramic fuel cell manufacturing by Jinwoo Kim, Jaewan Baek, Mingi Choi

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A Method for Prediction and Analysis of Student Performance That Combines Multi-Dimensional Features of Time and Space by Zheng Luo, Jiahao Mai, Caihong Feng, Deyao Kong, Jingyu Liu, Yunhong Ding, Bo Qi, Zhanbo Zhu

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AI driven prediction of early age compressive strength in ultra high performance fiber reinforced concrete by Mohamed Abdellatief, Wafa Hamla, Hassan Hamouda

Subjects: “…Gaussian process regression- feature importance analysis…”
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Work Place Safety: Machine Learning Techniques for Assessing Workplace Incident Severity by Munayr Hasan Khalleefah Hassan, Wagdi M. S. Khalifa

Subjects: “…permutation feature importance analysis…”
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Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing by Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang

Subjects: “…permutation feature importance analysis…”
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Solid Oxide Fuel Cell Voltage Prediction by a Data-Driven Approach by Hristo Ivanov Beloev, Stanislav Radikovich Saitov, Antonina Andreevna Filimonova, Natalia Dmitrievna Chichirova, Egor Sergeevich Mayorov, Oleg Evgenievich Babikov, Iliya Krastev Iliev

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Change in Fractional Vegetation Cover and Its Prediction during the Growing Season Based on Machine Learning in Southwest China by Xiehui Li, Yuting Liu, Lei Wang

Subjects: “…feature importance analysis…”
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Comparative analysis of boosting algorithms for predicting personal default by Nhat Nguyen, Duy Ngo

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Predicting Sugar Yield From Sugarcane Using Machine Learning for Jaggery Production by Kathirvel Narayanasamy, Ilayaraja Venkatachalam

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Advanced Machine Learning Techniques for Predicting Concrete Compressive Strength by Mohammad Saleh Nikoopayan Tak, Yanxiao Feng, Mohamed Mahgoub

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Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

Subjects: “…permutation feature importance analysis…”
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A hybrid deep learning-based approach for optimal genotype by environment selection by Zahra Khalilzadeh, Motahareh Kashanian, Saeed Khaki, Lizhi Wang

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Hydraulic Performance Modeling of Inclined Double Cutoff Walls Beneath Hydraulic Structures Using Optimized Ensemble Machine Learning by Mohamed Kamel Elshaarawy, Martina Zeleňáková, Asaad M. Armanuos

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Experimental 5G Network Performance Analysis in a Semi-Anechoic and Semi-Reverberation Chamber by Felix Delgado-Ferro, Alejandro Ramirez-Arroyo, Jorge Navarro-Ortiz, Juan F. Valenzuela-Valdes

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Clinical Applicability of Machine Learning Models for Binary and Multi-Class Electrocardiogram Classification by Daniel Nasef, Demarcus Nasef, Kennette James Basco, Alana Singh, Christina Hartnett, Michael Ruane, Jason Tagliarino, Michael Nizich, Milan Toma

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