MACHINE LEARNING APPLICATIONS IN AUTOMOTIVE ENGINEERING: ENHANCING VEHICLE SAFETY AND PERFORMANCE by Surajit MONDAL, Shankha Shubhra GOSWAMI

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Comparative Analysis of Machine Learning Models for CO Emission Prediction in Engine Performance by Beytullah Eren, İdris Cesur

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Evaluation of machine learning models for predicting performance metrics of aero-engine combustors by Huan Yang, Shu Guo, Haolin Xie, Jian Wen, Jiarui Wang

“…Feature importance analysis indicates that the cooling hole diameter and the third-stage swirler angle significantly impact combustor performance. The findings highlight the promise of machine learning in optimizing combustor design and improving the reliability of the aero-engine.…”
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Advancing the Engineering Approach to Improving the Quality Cracking Efficiency of Palm Nut Crackiing Machine by Okunola Oluwatobi Israel, Olukunle Olawale John, Adetola Oluwafemi Adeyemi, Akinfiresoye Waleola

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Machine Learning and High-Performance Computing Hybrid Systems, a New Way of Performance Acceleration in Engineering and Scientific Applications by Pawel Gepner

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Influence of Different Machining Processes on Fatigue life Performance of Engineered Surfaces: a Short Review by Wit Grzesik

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Performance prediction of electronic fan and water pump of engine cooling system based on joint simulation and machine learning by Yujin Zou, Renwang Li, Honghua Pan, Xiao Sun, Jun Fu

“…Abstract The performance of fans and pumps is pivotal to the efficiency and responsiveness of the engine cooling system. …”
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Leveraging Feature Extraction to Perform Time-Efficient Selection for Machine Learning Applications by Duarte Coelho, Ana Madureira, Ivo Pereira, Ramiro Gonçalves, Susana Nicola, Inês César, Daniel Alves de Oliveira

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Machine learning techniques for predictive modelling in geotechnical engineering: a succinct review by Shrikant M. Harle, Rajan L. Wankhade

Subjects: “…Machine learning (ML) techniques…”
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Performance comparison between workshop-based and laboratory-based condition monitoring systems for operational and economic performances of sugarcane harvesting by Rasol Abedini, Mahmoud Ghasemi-Nejad-Raeini, Afshin Marzban, Majid Rahnama

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Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries by Harish Venu, Manzoore Elahi M. Soudagar, Tiong Sieh Kiong, N. M. Razali, Hua-Rong Wei, Armin Rajabi, V. Dhana Raju, T. M. Yunus Khan, Naif Almakayeel, Erdem Cuce, Huseyin Seker

“…Abstract This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. …”
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Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…This study examines the prediction accuracy of ensemble machine learning models by comparing local and global precision, recall, and accuracy for multiclass grading of engineering students. …”
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Transforming biomass into engineered biochar materials for high-performance supercapacitors: Recent advances, challenges, and prospects by Ruibo FAN, Liang CHEN, Beichen XUE, Ao WANG, Yinhai SU, Huiyan ZHANG, Xiangzhou YUAN

“…Machine learning (ML)-based predictions and inverse designs have contributed to the innovation of engineered biochar-based electrode materials for high-performance applications, clarifying the inherent mechanisms and complex relationships between the properties of engineering biochar and the electrochemical performance of supercapacitors. …”
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Conciliating accuracy and efficiency to empower engineering based on performance: a short journey by Chinesta, Francisco, Cueto, Elias

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Applied AMT machine learning and multi-objective optimization for enhanced performance and reduced environmental impact of sunflower oil biodiesel in compression ignition engine by Ali A. Al-jabiri, Hyder H. Balla, Mudhaffar S. Al-zuhairy, Hussein Alahmer, Ahmed Al-Manea, Raed Al-Rbaihat, Ali Alahmer

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Modelling and Prediction of Particulate Matter, NOx, and Performance of a Diesel Vehicle Engine under Rare Data Using Relevance Vector Machine by Ka In Wong, Pak Kin Wong, Chun Shun Cheung

“…To overcome the drawbacks, this paper proposes to apply one emerging technique, relevance vector machine (RVM), to model the diesel engine, and to predict the emissions and engine performance. …”
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A Data-Driven Approach to Engineering Instruction: Exploring Learning Styles, Study Habits, and Machine Learning by Lauren Genith Isaza Dominguez, Antonio Robles-Gomez, Rafael Pastor-Vargas

Subjects: “…Academic performance…”
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On Predicting Marine Engine Measurements with Synthetic Data in Scarce Dataset by Sandi Baressi Šegota, Igor Poljak, Nikola Anđelić, Vedran Mrzljak

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Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review by Bruno Matos Porto

“…Conclusion NLP methods improved ML algorithms' classification capability using triage nursing and medical notes and structured clinical data compared to algorithms using only structured data. Feature engineering (FE) and class imbalance correction methods enhanced ML workflows' performance, but FE and eXplainable Artificial Intelligence (XAI) were underexplored in this field. …”
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Intelligent Engine Health Monitoring System for Enhanced Vehicle Performance by Yogita Dubey, Khushal Damahe, Usha Ambule, Sanskruti Alone, Tanaya Deshpande, Roshan Umate

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