Smart Electrical and Mechanical Systems: An Application of Artificial Intelligence and Machine Learning
Editat de Rakesh Sehgal, Neeraj Gupta, Anuradha Tomar, Mukund Dutt Sharma, Vigna Kumaranen Limba Engleză Paperback – 20 iun 2022
The book guides readers on not only how to effectively solve problems but also provide high accuracy needed for successful implementation. Interdisciplinary in nature, the book caters to the needs of the electrical and mechanical engineering industry by offering details on the application of AI and ML in robotics, design and manufacturing, image processing, power system operation and forecasting with suitable examples.
- Includes significant case studies related to application of Artificial Intelligence and Machine Learning in Energy and Power, Mechanical Design and Manufacturing
- Contains supporting illustrations and tables, along with a valuable set of references at the end of each chapter
- Provides original, state-of-the-art research material written by international and national respected contributors
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Specificații
ISBN-13: 9780323907897
ISBN-10: 032390789X
Pagini: 314
Ilustrații: Approx. 120 illustrations
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.42 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 032390789X
Pagini: 314
Ilustrații: Approx. 120 illustrations
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.42 kg
Editura: ELSEVIER SCIENCE
Public țintă
Researchers, professionals working in the field of Energy, Electrical and Mechanical EngineeringEngineers, energy experts, R&D organizations and industry professionals engaged in research in the field of smart systems
Cuprins
1. Basics of Artificial intelligence and Machine learning
2. Artificial Intelligence and machine learning based Robot Control
3. Smart Mechanical Design
4. Smart Manufacturing
5. Autonomous vehicles
6. Image processing for electrical and mechanical engineering
7. Machine learning in smart electric power systems
8. Renewable energy integration with ML
9. Machine learning applications in optimal power flow
10. Machine learning applications in power system control
11. Machine learning applications in power system forecasting
2. Artificial Intelligence and machine learning based Robot Control
3. Smart Mechanical Design
4. Smart Manufacturing
5. Autonomous vehicles
6. Image processing for electrical and mechanical engineering
7. Machine learning in smart electric power systems
8. Renewable energy integration with ML
9. Machine learning applications in optimal power flow
10. Machine learning applications in power system control
11. Machine learning applications in power system forecasting