Focus on artificial neural networks /:
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York :
Nova Science Publishers,
©2011.
|
| Schriftenreihe: | Mathematics research developments series.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource (xiv, 410 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781619421004 1619421003 9781613242858 1613242859 |
Internformat
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| 300 | |a 1 online resource (xiv, 410 pages) : |b illustrations | ||
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| 490 | 1 | |a Mathematics research developments | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 650 | 0 | |a Neural networks (Computer science) |0 http://id.loc.gov/authorities/subjects/sh90001937 | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 7 | |a COMPUTERS |x Neural Networks. |2 bisacsh | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast | |
| 700 | 1 | |a Flores, John A. |0 http://id.loc.gov/authorities/names/n2011031923 | |
| 758 | |i has work: |a Focus on artificial neural networks (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGgV3gdkM3HTRqPD8MphgX |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-ocn770675486 |
|---|---|
| _version_ | 1816881781645770752 |
| adam_text | |
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| author2 | Flores, John A. |
| author2_role | |
| author2_variant | j a f ja jaf |
| author_GND | http://id.loc.gov/authorities/names/n2011031923 |
| author_facet | Flores, John A. |
| author_sort | Flores, John A. |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
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| callnumber-search | QA76.87 .F623 2011eb |
| callnumber-sort | QA 276.87 F623 42011EB |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-4-EBA |
| 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 |
| ctrlnum | (OCoLC)770675486 |
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| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/2 |
| dewey-search | 006.3/2 |
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| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-ocn770675486 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:18:11Z |
| institution | BVB |
| isbn | 9781619421004 1619421003 9781613242858 1613242859 |
| language | English |
| oclc_num | 770675486 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xiv, 410 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Nova Science Publishers, |
| record_format | marc |
| series | Mathematics research developments series. |
| series2 | Mathematics research developments |
| spelling | Focus on artificial neural networks / John A. Flores, editor. New York : Nova Science Publishers, ©2011. 1 online resource (xiv, 410 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file Mathematics research developments Includes bibliographical references and index. Print version record. 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. Sulimanâ€?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 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Réseaux neuronaux (Informatique) COMPUTERS Neural Networks. bisacsh Neural networks (Computer science) fast Flores, John A. http://id.loc.gov/authorities/names/n2011031923 has work: Focus on artificial neural networks (Text) https://id.oclc.org/worldcat/entity/E39PCGgV3gdkM3HTRqPD8MphgX https://id.oclc.org/worldcat/ontology/hasWork Print version: Focus on artificial neural networks. New York : Nova Science Publishers, ©2011 9781613242858 (DLC) 2011012975 (OCoLC)723528612 Mathematics research developments series. http://id.loc.gov/authorities/names/no2009139785 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=400772 Volltext |
| spellingShingle | Focus on artificial neural networks / Mathematics research developments series. 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. Sulimanâ€?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 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Réseaux neuronaux (Informatique) COMPUTERS Neural Networks. bisacsh Neural networks (Computer science) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh90001937 |
| title | Focus on artificial neural networks / |
| title_auth | Focus on artificial neural networks / |
| title_exact_search | Focus on artificial neural networks / |
| title_full | Focus on artificial neural networks / John A. Flores, editor. |
| title_fullStr | Focus on artificial neural networks / John A. Flores, editor. |
| title_full_unstemmed | Focus on artificial neural networks / John A. Flores, editor. |
| title_short | Focus on artificial neural networks / |
| title_sort | focus on artificial neural networks |
| topic | Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Réseaux neuronaux (Informatique) COMPUTERS Neural Networks. bisacsh Neural networks (Computer science) fast |
| topic_facet | Neural networks (Computer science) Réseaux neuronaux (Informatique) COMPUTERS Neural Networks. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=400772 |
| work_keys_str_mv | AT floresjohna focusonartificialneuralnetworks |