Articles liés à Applied Machine Learning for Solar Data Processing:...
Applied Machine Learning for Solar Data Processing: Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning - Couverture souple
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
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.
Biographie de l'auteur
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 48,50
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisRésultats de recherche pour Applied Machine Learning for Solar Data Processing:...
Image fournie par le vendeur
Applied Machine Learning for Solar Data Processing
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3845477768
ISBN 13 : 9783845477763
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : 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 . N° de réf. du vendeur 5484376
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Applied Machine Learning for Solar Data Processing : Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3845477768
ISBN 13 : 9783845477763
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783845477763
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Applied Machine Learning for Solar Data Processing
Edité par
LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10 : 3845477768
ISBN 13 : 9783845477763
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783845477763
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Applied Machine Learning for Solar Data Processing
Edité par
LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10 : 3845477768
ISBN 13 : 9783845477763
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783845477763
Quantité disponible : 2 disponible(s)
Image d'archives
Applied Machine Learning for Solar Data Processing: Developing Automated Technologies for Knowledge Extraction and Prediction of Solar Activities using Machine Learning
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3845477768
ISBN 13 : 9783845477763
Ancien ou d'occasion
Paperback
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA79638454777686
Quantité disponible : 1 disponible(s)