Isbn: 9783030011796 - deep learning and missing data in engineering systems: 48 (studies in big data, 48) (10 resultados)

25 cm. XIV, 179 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Studies in Big Data. Volume 48. Sprache: Englisch. …

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Deep Learning and Missing Data in Engineering Systems uses deep learning and swarm intelligence methods to cover missing data estimation in engineering systems. The missing data estimation processes proposed in the book can be applied in image recognition and reconstruction. To facilitate the imputation of missing data, several artificial intelligence approaches are presented, including:deep autoencoder neural networks;deep denoising autoencoder networks;the bat algorithm;the cuckoo search algorithm; andthe firefly algorithm. The hybrid models proposed are used to estimate the missing data in high-dimensional data settings more accurately. Swarm intelligence algorithms are applied to address critical questions such as model selection and model parameter estimation. The authors address feature extraction for the purpose of reconstructing the input data from reduced dimensions by the use of deep autoencoder neural networks. They illustrate new models diagrammatically, report their findings in tables, so as to put their methods on a sound statistical basis. The methods proposed speed up the process of data estimation while preserving known features of the data matrix. This book is a valuable source of information for researchers and practitioners in data science. Advanced undergraduate and postgraduate students studying topics in computational intelligence and big data, can also use the book as a reference for identifying and introducing new research thrusts in missing data estimation.…

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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Deep Learning and Missing Data in Engineering Systems uses deep learning and swarm intelligence methods to cover missing data estimation in engineering systems. The missing data estimation processes proposed in the book can be applied in image recognition and reconstruction. To facilitate the imputation of missing data, several artificial intelligence approaches are presented, including:deep autoencoder neural networks;deep denoising autoencoder networks;the bat algorithm;the cuckoo search algorithm; andthe firefly algorithm. The hybrid models proposed are used to estimate the missing data in high-dimensional data settings more accurately. Swarm intelligence algorithms are applied to address critical questions such as model selection and model parameter estimation. The authors address feature extraction for the purpose of reconstructing the input data from reduced dimensions by the use of deep autoencoder neural networks. They illustrate new models diagrammatically, report their findings in tables, so as to put their methods on a sound statistical basis. The methods proposed speed up the process of data estimation while preserving known features of the data matrix. This book is a valuable source of information for researchers and practitioners in data science. Advanced undergraduate and postgraduate students studying topics in computational intelligence and big data, can also use the book as a reference for identifying and introducing new research thrusts in missing data estimation. 196 pp. Englisch.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Adopts and applies&nbspswarm intelligence algorithms&nbspto address critical questions such as model selection and model parameter estimationProposes new paradigms of machine learning and computational intelligence in missing data esti.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Introduction to Missing Data Estimation.- Introduction to Deep Learning.- Missing Data Estimation Using Bat Algorithm.- Missing Data Estimation Using Cuckoo Search Algorithm.- Missing Data Estimation Using Firefly Algorithm.- Missing Data Estimation Using Ant Colony Optimization Algorithm.- Missing Data Estimation Using Ant-Lion Optimizer Algorithm.- Missing Data Estimation Using Invasive Weed Optimization Algorithm.- Missing Data Estimation Using Swarm Intelligence Algorithms from Reduced Dimensions.- Missing Data Estimation Using Swarm Intelligence Algorithms: Deep Learning Framework Analysis.- Conclusion.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 196 pp. Englisch.…

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.