Artificial neural networks /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Kwon, Seoyun J. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hauppauge, N.Y. : Nova Science Publishers, c2011.
Colección:Mathematics research developments series.
Engineering tools, techniques and tables.
Temas:
Neural networks (Computer science)
Neural Networks, Computer
Réseaux neuronaux (Informatique)
COMPUTERS > Neural Networks.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • ARTIFICIAL NEURAL NETWORKS
  • ARTIFICIAL NEURAL NETWORKS
  • CONTENTS
  • PREFACE
  • ARTIFICIAL NEURAL NETWORK MODELING OF WATER AND WASTEWATER TREATMENT PROCESSES
  • ABSTRACT
  • 1. INTRODUCTION
  • 2. TOPOLOGY OF ARTIFICIAL NEURAL NETWORKS
  • 2.1. Transfer Functions
  • 2.2. Learning Process
  • 2.2.1. Supervised Learning
  • 2.2.2. Reinforcement Learning
  • 2.2.3. Unsupervised Learning
  • 2.3. Training Algorithms
  • 2.3.1. Back Propagation Algorithm
  • 2.3.1.1. Conjugate Gradient Algorithm
  • 2.3.1.2. Scaled Conjugate Gradient Algorithm
  • 2.3.2. Quasi-Newton Algorithms 2.3.3. Levenberg-Marquardt Algorithm
  • 3. TRAINING, VALIDATION AND TEST OF A NEURAL NETWORK
  • 3.1. Test of the Fitted Model
  • 3.2. Relative Importance of Input Variables
  • 3.3. Improving Generalization
  • 3.3.1. Regularization
  • 3.3.2. Early Stopping
  • 4. APPLICATIONS OF ARTIFICIAL NEURAL NETWORK MODELING
  • 5. ANN MODELING OF ADSORPTION PROCESSES
  • 6. ANN MODELING OF BIOLOGICAL TREATMENT PROCESSES
  • 7. ANN MODELING OF ELECTROCHEMICAL TREATMENT PROCESSES
  • 8. ANN MODELING OF PHOTOCATALYTIC PROCESSES
  • 9. ANN MODELING OF PHOTOOXIDATIVE PROCESSES 9.1. Fenton and Photoâ€?Fenton Processes
  • 9.2. UV/H2O2, ozonation and chlorination processes
  • CONCLUSIONS
  • ACKNOWLEDGMENTS
  • REFERENCES
  • RECENT ADVANCES AND CHALLENGES IN THE APPLICATION OF ARTIFICIAL NEURAL NETWORKS (ANN) IN NEUROLOGICAL SCIENCES: AN OVERVIEW
  • SUMMARY
  • 1. INTRODUCTION
  • 2. CLASSIFICATION SYSTEMS AND MEASURES IN MEDICINE AND NEUROLOGY
  • 3. HISTORY AND BASIC DESCRIPTION OF ANN
  • 4. DEVELOPMENTS AND CURRENT UTILIZATION OF ANN IN NEUROLOGY
  • 4.1. ANN in Cerebrovascular Diseases 4.2. Sleep Apnea
  • 4.3. ANN in Neurodegenerative Disorders
  • 4.3.1. Alzheimerâ€?s Disease And Other Dementias
  • 4.3.2. Parkinsonâ€?s Disease
  • 4.4. ANN in Clinical Neurophysiology (EEG and EMG)
  • 4.5. ANN in Autism Research
  • 4.6. ANN in Brain Tumor Studies
  • 4.7. ANN in Brain Injuries
  • 5. FUTURE CHALLENGES OF ANN: APPLICATIONS IN NEUROLOGICAL SCIENCES
  • 6. CONCLUSIONS
  • APPENDIX 1. (ONLINE ONLY)
  • APPENDIX 2. (ONLINE ONLY)
  • APPENDIX 3. (ONLINE ONLY)
  • REFERENCES
  • DIFFERENT TYPES OF APPLICATIONS PERFORMED WITH DIFFERENT TYPES OF NEURAL NETWORKS ABSTRACT
  • 1. THEORETICAL ASPECTS
  • 2. NEURAL NETWORK TYPES
  • 3. NEURAL NETWORK APPLICATIONS
  • 3.1. Direct Neural Network Modeling
  • 3.2. Inverse Neural Network Modeling
  • 3.3. Neural Networks Used for the Chemical Process Monitoring
  • 3.4. Optimization Based on Neural Network Models
  • 3.5. Neural Networks Used in Process Control
  • 3.6. Neural Networks as Classification Tools
  • 3.7. Property Prediction and Molecular Design
  • CONCLUSIONS
  • REFERENCES

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