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Application of neural networks and other learning technologies in process engineering [[electronic resource] /] / editors, I.M. Mujtaba, M.A. Hussain
| Application of neural networks and other learning technologies in process engineering [[electronic resource] /] / editors, I.M. Mujtaba, M.A. Hussain |
| Pubbl/distr/stampa | River Edge, NJ, : ICP, 2001 |
| Descrizione fisica | 1 online resource (423 p.) |
| Disciplina | 006.3/2 |
| Altri autori (Persone) |
MujtabaI. M
HussainM. A <1958-> (Mohamed Azlan) |
| Soggetto topico |
Neural networks (Computer science)
Process control Manufacturing processes |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-86600-8
9786611866006 1-84816-146-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents ; Foreword ; Acknowledgements ; Part I: Modelling and Identification ; 1. Simulation of Liquid-Liquid Extraction Data with Artificial Neural Networks ; 2. RBFN Identification of an Industrial Polymerization Reactor Model ; 3. Process Identification with Self-Organizing Networks
4. Training Radial Basis Function Networks for Process Identification with an Emphasis on the Bayesian Evidence Approach 5. Process Identification of a Fed-Batch Penicillin Production Process - Training with the Extended Kalman Filter ; Part II: Hybrid Schemes 6. Combining Neural Networks and First Principle Models for Bioprocess Modeling 7. Neural Networks in a Hybrid Scheme for Optimisation of Dynamic Processes: Application to Batch Distillation ; 8. Hierarchical Neural Fuzzy Models as a Tool for Process Identification: A Bioprocess Application Part III: Estimation and Control 9. Adaptive Inverse Model Control of a Continuous Fermentation Process Using Neural Networks ; 10. Set Point Tracking in Batch Reactors: Use of PID and Generic Model Control with Neural Network Techniques 11. Inferential Estimation and Optimal Control of a Batch Polymerisation Reactor Using Stacked Neural Networks Part IV: New Learning Technologies ; 12. Reinforcement Learning in Batch Processes ; 13. Knowledge Discovery through Mining Process Operational Data Part V: Experimental and Industrial Applications |
| Record Nr. | UNINA-9910454335403321 |
| River Edge, NJ, : ICP, 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Application of neural networks and other learning technologies in process engineering [[electronic resource] /] / editors, I.M. Mujtaba, M.A. Hussain
| Application of neural networks and other learning technologies in process engineering [[electronic resource] /] / editors, I.M. Mujtaba, M.A. Hussain |
| Pubbl/distr/stampa | River Edge, NJ, : ICP, 2001 |
| Descrizione fisica | 1 online resource (423 p.) |
| Disciplina | 006.3/2 |
| Altri autori (Persone) |
MujtabaI. M
HussainM. A <1958-> (Mohamed Azlan) |
| Soggetto topico |
Neural networks (Computer science)
Process control Manufacturing processes |
| ISBN |
1-281-86600-8
9786611866006 1-84816-146-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents ; Foreword ; Acknowledgements ; Part I: Modelling and Identification ; 1. Simulation of Liquid-Liquid Extraction Data with Artificial Neural Networks ; 2. RBFN Identification of an Industrial Polymerization Reactor Model ; 3. Process Identification with Self-Organizing Networks
4. Training Radial Basis Function Networks for Process Identification with an Emphasis on the Bayesian Evidence Approach 5. Process Identification of a Fed-Batch Penicillin Production Process - Training with the Extended Kalman Filter ; Part II: Hybrid Schemes 6. Combining Neural Networks and First Principle Models for Bioprocess Modeling 7. Neural Networks in a Hybrid Scheme for Optimisation of Dynamic Processes: Application to Batch Distillation ; 8. Hierarchical Neural Fuzzy Models as a Tool for Process Identification: A Bioprocess Application Part III: Estimation and Control 9. Adaptive Inverse Model Control of a Continuous Fermentation Process Using Neural Networks ; 10. Set Point Tracking in Batch Reactors: Use of PID and Generic Model Control with Neural Network Techniques 11. Inferential Estimation and Optimal Control of a Batch Polymerisation Reactor Using Stacked Neural Networks Part IV: New Learning Technologies ; 12. Reinforcement Learning in Batch Processes ; 13. Knowledge Discovery through Mining Process Operational Data Part V: Experimental and Industrial Applications |
| Record Nr. | UNINA-9910782123103321 |
| River Edge, NJ, : ICP, 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Application of neural networks and other learning technologies in process engineering / / editors, I.M. Mujtaba, M.A. Hussain
| Application of neural networks and other learning technologies in process engineering / / editors, I.M. Mujtaba, M.A. Hussain |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | River Edge, NJ, : ICP, 2001 |
| Descrizione fisica | 1 online resource (423 p.) |
| Disciplina | 006.3/2 |
| Altri autori (Persone) |
MujtabaI. M
HussainM. A <1958-> (Mohamed Azlan) |
| Soggetto topico |
Neural networks (Computer science)
Process control Manufacturing processes |
| ISBN |
1-281-86600-8
9786611866006 1-84816-146-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents ; Foreword ; Acknowledgements ; Part I: Modelling and Identification ; 1. Simulation of Liquid-Liquid Extraction Data with Artificial Neural Networks ; 2. RBFN Identification of an Industrial Polymerization Reactor Model ; 3. Process Identification with Self-Organizing Networks
4. Training Radial Basis Function Networks for Process Identification with an Emphasis on the Bayesian Evidence Approach 5. Process Identification of a Fed-Batch Penicillin Production Process - Training with the Extended Kalman Filter ; Part II: Hybrid Schemes 6. Combining Neural Networks and First Principle Models for Bioprocess Modeling 7. Neural Networks in a Hybrid Scheme for Optimisation of Dynamic Processes: Application to Batch Distillation ; 8. Hierarchical Neural Fuzzy Models as a Tool for Process Identification: A Bioprocess Application Part III: Estimation and Control 9. Adaptive Inverse Model Control of a Continuous Fermentation Process Using Neural Networks ; 10. Set Point Tracking in Batch Reactors: Use of PID and Generic Model Control with Neural Network Techniques 11. Inferential Estimation and Optimal Control of a Batch Polymerisation Reactor Using Stacked Neural Networks Part IV: New Learning Technologies ; 12. Reinforcement Learning in Batch Processes ; 13. Knowledge Discovery through Mining Process Operational Data Part V: Experimental and Industrial Applications |
| Record Nr. | UNINA-9910824289303321 |
| River Edge, NJ, : ICP, 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||