0
Your cart

Your cart is empty

Books > Computing & IT > Applications of computing > Artificial intelligence

Not currently available

Deep Learning and Missing Data in Engineering Systems (Hardcover, 1st ed. 2019) Loot Price: R3,245
Discovery Miles 32 450
You Save: R821 (20%)
Deep Learning and Missing Data in Engineering Systems (Hardcover, 1st ed. 2019): Collins Achepsah Leke, Tshilidzi Marwala

Deep Learning and Missing Data in Engineering Systems (Hardcover, 1st ed. 2019)

Collins Achepsah Leke, Tshilidzi Marwala

Series: Studies in Big Data, 48

 (sign in to rate)
List price R4,066 Loot Price R3,245 Discovery Miles 32 450 | Repayment Terms: R304 pm x 12* You Save R821 (20%)

Bookmark and Share

Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.

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; and the 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.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Studies in Big Data, 48
Release date: 2019
First published: 2019
Authors: Collins Achepsah Leke • Tshilidzi Marwala
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 179
Edition: 1st ed. 2019
ISBN-13: 978-3-03-001179-6
Categories: Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-03-001179-8
Barcode: 9783030011796

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!

Partners