Leke Collins. Deep Learning and Missing Data in Engineering Systems

Springer, 2018 (2019 Edition). — 188 p.Deep Learning and Missing Data in Engineering Systems discuss concepts and applications of artificial intelligence, specifically, deep learning. The artificial intelligence techniques that are studied include multilayer autoencoder networks and deep autoencoder networks. Also studied in this book are computational and swarm intelligence techniques which include ant colony optimization, ant lion optimizer, bat algorithm, cuckoo search optimization, firefly algorithm and invasive weed optimization algorithm. In addition, this book explores using deep autoencoder networks with a varying number of hidden layers. This book also studies the reconstruction of images from reduced dimensions obtained from the bottleneck layer of the deep autoencoder. These techniques are used to solve the missing data problem in an image recognition and reconstruction context.