Focus on artificial neural networks / John A. Flores, editor.

Format:

Book

Contributor:

Flores, John A.

Series:

Mathematics Research Developments

Mathematics research developments

Language:

English

Subjects (All):

Neural networks (Computer science).

Artificial intelligence.

Physical Description:

1 online resource (426 p.)

Edition:

1st ed.

Place of Publication:

New York : Nova Science Publishers, c2011.

Language Note:

English

Summary:

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include artificial neural networks in environmental sciences and chemical engineering; application of artificial neural networks in the development of pharamceutical microemulsions; massive-training artificial neural networks for supervised enhancement/suppression of lesions/patterns in medical images; evidences of new biophysical properties of microtubules; neural network applications in modern induction machine control systems and wavelet neural networks.

Contents:

""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""CONTENTS ""; ""PREFACE ""; ""APPLICATION OF ARTIFICIAL NEURAL NETWORKS (ANNS) IN DEVELOPMENT OF PHARMACEUTICAL MICROEMULSIONS ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""3. MICROEMULSIONS ""; ""4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS ""; ""4.1. Prediction of Phase Behaviour ""; ""4.1.1. The influence of ANNs type/architecture ""; ""4.2. Screening of the Microemulsion Constituents ""

""4.3. Prediction of Structural Features of Microemulsions """"5. CONCLUSION ""; ""Symbols and Terminologies ""; ""REFERENCES ""; ""INVESTGATIONS OF APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR FLOW SHOP SCHEDULING PROBLEMS ""; ""ABSTRACT ""; ""1.0 INTRODUCTION ""; ""1.1. Flow Shop Scheduling""; ""1.2. Methodologies used In Flow shop Scheduling ""; ""2.0. ANN APPROACH FOR SCHEDULING A BICRITERION FLOW SHOP ""; ""2.1. Problem Description ""; ""2.2. Architecture of the Proposed System ""; ""2.2.1. Initial learning stage""; ""2.2.2. Implementation stage ""

""2.3. Bidirectional Neural Network Structure """"2.4. An Illustration ""; ""2.5. Results and Discussions ""; ""3.0. ANN APPROACH FOR SCHEDULING A MULTI CRITERION FLOW SHOP""; ""3.1. Illustration ""; ""3.2. Results and Discussions ""; ""4.0. A HYBRID NEURAL NETWORK-META HEURISTIC APPROACH FOR PERMUTATION FLOW SHOP SCHEDULING ""; ""4.1. Introduction ""; ""4.2. Architecture of the ANN ""; ""4.3. Methodology ""; ""4.4. Results and Discussion ""; ""4.4.1. Suliman�s heuristic""; ""4.4.2. Genetic algorithm ""; ""Generation of initial population""; ""4.4.3. Simulated annealing ""

""4.5. Results and Discussions """"4.6. Inferences ""; ""5.0. CONCLUSIONS AND FUTURE DIRECTIONS ""; ""REFERENCES ""; ""ARTIFICIAL NEURAL NETWORKS IN ENVIRONMENTAL SCIENCES AND CHEMICAL ENGINEERING ""; ""ABSTRACT ""; ""INTRODUCTION ""; ""BRIEF DESCRIPTION OF ANN ""; ""LITERATURE REVIEW ""; ""ENVIRONMENTAL SCIENCES ""; ""CHEMICAL ENGINEERING ""; ""Modelling ""; ""Control""; ""Software Sensors ""; ""CONCLUSIONS ""; ""ACKNOWLEDGMENTS ""; ""REFERENCES ""; ""ESTABLISHING PRODUCTIVITY INDICES FOR WHEAT IN THE ARGENTINE PAMPAS BY AN ARTIFICIAL NEURAL NETWORK APPROACH""; ""ABSTRACT ""

""ENVIRONMENTAL FACTORS CONTROLLING WHEAT YIELD IN THE PAMPAS """"Attempts for Predicting Wheat Yield in the Pampas Using Regression Techniques ""; ""Use of Artificial Neural Networks to Predict Wheat Yield ""; ""Establishing Productivity Indices by an Artificial Neural Network Approach""; ""CONCLUDING REMARKS""; ""REFERENCES ""; ""DESIGN OF ARTIFICIAL NEURAL NETWORK PREDICTORS IN MECHANICAL SYSTEMS PROBLEMS ""; ""ABSTRACT ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""2.1. Feedforward Neural Networks ""; ""2.2. Recurrent Neural Networks ""

""2.1.1. Back Propagation neural network (BPNN) ""

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

1-61942-100-3

OCLC:

923654107