Artificial intelligence and data driven optimization of internal combustion engines. (2022)

• Record Type: Book
• Further Information: Note: Edited by Jihad Badra, Pinaki Pal, Yuanjiang Pei, Sibendu Som.
• Editors: Badra, Jihad; Pal, Pinaki; Pei, Yuanjiang; Som, Sibendu
• Contents: 1. Active-learning for fuel optimization 2. High throughput screening for fuel formulation 3. Engine optimization using computational fluid dynamics-Genetic algorithms (CFD-GA) 4. Engine optimization using computational fluid dynamics-design of experiments (CFD-DoE) 5. Engine optimization using machine learning-genetic algorithms (ML-GA) 6. Machine learning driven sequential optimization using dynamic exploration and exploitation 7. Optimization of after-treatment systems using machine learning 8. Engine cycle-to-cycle variation control 9. Prediction of low pressure preignition using machine learning 10. AI aided optimization of experimental engine calibration 11. AI aided optimization of vehicle control calibration
• Publisher Details: Amsterdam : Elsevier
• Publication Date: 2022
• Extent: 1 online resource, illustrations (black and white, and colour)
• Subjects: 621.43028563; Internal combustion engines -- Data processing; Artificial intelligence -- Industrial applications
• Languages: English
• ISBNs: 9780323884587
• Related ISBNs: 9780323884570
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.