Applied Machine Learning for Solar Data Processing: Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning - Brossura
Sinossi
It is becoming increasingly important to understand the possible cause and effect relationships between these solar events and features to produce timely and reliable computer-based forecasting of extreme solar events. These forecasts are very important for protecting our technological infra-structures and human life on earth and in space. The need to develop automated tools to process solar data is also increasing because existing space missions are sending huge amounts of data and scientists back on Earth are struggling to keep pace. In this book, we present our research work introducing novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this book consists of three stages: (1) designing computer tools to find the associations among solar events and features (2) applying machine learning algorithms to the associations’ datasets and (3) studying the evolution patterns of sunspot groups using time-series methods.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Dr. Alomari is an Assistant Prof. of IT in ASU, Jordan. BEng(2005) & MEng(2006) in EE from JUST, Jordan & PhD(2009) from UoB, UK. Dr. Qahwaji is a Reader in Visual Computing in UoB, UK. BSc(1994) & MSc(1997) in EE from UoM, Iraq & PhD(2002) from UoB, UK. Dr. Ipson is a Senior Lecturer in UoB, UK. BSc in Applied Physics & PhD in Nuclear Physics.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Applied Machine Learning for Solar Data Processing
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LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10: 3845477768
ISBN 13: 9783845477763
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -It is becoming increasingly important to understand the possible cause and effect relationships between these solar events and features to produce timely and reliable computer-based forecasting of extreme solar events. These forecasts are very important for protecting our technological infra-structures and human life on earth and in space. The need to develop automated tools to process solar data is also increasing because existing space missions are sending huge amounts of data and scientists back on Earth are struggling to keep pace. In this book, we present our research work introducing novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this book consists of three stages: (1) designing computer tools to find the associations among solar events and features (2) applying machine learning algorithms to the associations datasets and (3) studying the evolution patterns of sunspot groups using time-series methods. 152 pp. Englisch. Codice articolo 9783845477763
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Applied Machine Learning for Solar Data Processing
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LAP LAMBERT Academic Publishing, 2011
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ISBN 13: 9783845477763
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Alomari Mohammad H.Dr. Alomari is an Assistant Prof. of IT in ASU, Jordan. BEng(2005) & MEng(2006) in EE from JUST, Jordan & PhD(2009) from UoB, UK. Dr. Qahwaji is a Reader in Visual Computing in UoB, UK. BSc(1994) & MSc(1997) in EE . Codice articolo 5484376
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Applied Machine Learning for Solar Data Processing
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LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10: 3845477768
ISBN 13: 9783845477763
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Taschenbuch. Condizione: Neu. Neuware -It is becoming increasingly important to understand the possible cause and effect relationships between these solar events and features to produce timely and reliable computer-based forecasting of extreme solar events. These forecasts are very important for protecting our technological infra-structures and human life on earth and in space. The need to develop automated tools to process solar data is also increasing because existing space missions are sending huge amounts of data and scientists back on Earth are struggling to keep pace. In this book, we present our research work introducing novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this book consists of three stages: (1) designing computer tools to find the associations among solar events and features (2) applying machine learning algorithms to the associations¿ datasets and (3) studying the evolution patterns of sunspot groups using time-series methods.Books on Demand GmbH, Überseering 33, 22297 Hamburg 152 pp. Englisch. Codice articolo 9783845477763
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Applied Machine Learning for Solar Data Processing : Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845477768
ISBN 13: 9783845477763
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It is becoming increasingly important to understand the possible cause and effect relationships between these solar events and features to produce timely and reliable computer-based forecasting of extreme solar events. These forecasts are very important for protecting our technological infra-structures and human life on earth and in space. The need to develop automated tools to process solar data is also increasing because existing space missions are sending huge amounts of data and scientists back on Earth are struggling to keep pace. In this book, we present our research work introducing novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this book consists of three stages: (1) designing computer tools to find the associations among solar events and features (2) applying machine learning algorithms to the associations datasets and (3) studying the evolution patterns of sunspot groups using time-series methods. Codice articolo 9783845477763
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Applied Machine Learning for Solar Data Processing | Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning
Editore:
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845477768
ISBN 13: 9783845477763
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Taschenbuch. Condizione: Neu. Applied Machine Learning for Solar Data Processing | Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning | Mohammad H. Alomari (u. a.) | Taschenbuch | 152 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845477763 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Codice articolo 106791064
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Applied Machine Learning for Solar Data Processing: Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning
Editore:
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845477768
ISBN 13: 9783845477763
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Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA79638454777686
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