Artificial Intelligence in Manufacturing
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portes grátis
Artificial Intelligence in Manufacturing
Concepts and Methods
Soroush, Masoud; D Braatz, Richard
Elsevier Science & Technology
01/2024
372
Mole
Inglês
9780323991346
15 a 20 dias
Descrição não disponível.
1. Data-driven Physics-based Digital Twins
2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge
3. Dynamical Systems-Guided Learning of PDEs from Data
4. Learning First-principles Knowledge from Data
5. Actual Learning through Machine Learning
6. Iterative Cross Learning
7. Learning an Algebraic Model from Data
8. Data-driven Optimization Algorithms
9. Interpretable Machine Learning
10. Learning Science and Algorithms
11. Reinforcement Learning
12. Machine Learning: Trends, Perspectives, and Prospects
13. Artificial Intelligence: Trends, Perspectives, and Prospects
14. Artificial Intelligence Education for Chemical Engineers
2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge
3. Dynamical Systems-Guided Learning of PDEs from Data
4. Learning First-principles Knowledge from Data
5. Actual Learning through Machine Learning
6. Iterative Cross Learning
7. Learning an Algebraic Model from Data
8. Data-driven Optimization Algorithms
9. Interpretable Machine Learning
10. Learning Science and Algorithms
11. Reinforcement Learning
12. Machine Learning: Trends, Perspectives, and Prospects
13. Artificial Intelligence: Trends, Perspectives, and Prospects
14. Artificial Intelligence Education for Chemical Engineers
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Cyber physical system; industry 4.0; manufacturing system; internet of things; factory; 3d printer; lean production; digitalization; big data; intelligent manufacturing; flexible manufacturing system
1. Data-driven Physics-based Digital Twins
2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge
3. Dynamical Systems-Guided Learning of PDEs from Data
4. Learning First-principles Knowledge from Data
5. Actual Learning through Machine Learning
6. Iterative Cross Learning
7. Learning an Algebraic Model from Data
8. Data-driven Optimization Algorithms
9. Interpretable Machine Learning
10. Learning Science and Algorithms
11. Reinforcement Learning
12. Machine Learning: Trends, Perspectives, and Prospects
13. Artificial Intelligence: Trends, Perspectives, and Prospects
14. Artificial Intelligence Education for Chemical Engineers
2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge
3. Dynamical Systems-Guided Learning of PDEs from Data
4. Learning First-principles Knowledge from Data
5. Actual Learning through Machine Learning
6. Iterative Cross Learning
7. Learning an Algebraic Model from Data
8. Data-driven Optimization Algorithms
9. Interpretable Machine Learning
10. Learning Science and Algorithms
11. Reinforcement Learning
12. Machine Learning: Trends, Perspectives, and Prospects
13. Artificial Intelligence: Trends, Perspectives, and Prospects
14. Artificial Intelligence Education for Chemical Engineers
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
