The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series.

This book provides a gentle introduction to redescription mining, a versatile data mining tool that is useful to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions.

The author first introduces the basic framework for cultural algorithms and he then explains the social structure of a cultural system as a mechanism for the distribution of problem-solving information throughout a population.

This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. In particular, the authors derive gradient descent algorithms in a unified way for several neural network structures, including multilayer perceptrons, convolutional neural networks, deep autoencoders and recurrent neural networks.

The application of bioinformatics approaches in drug design involves an interdisciplinary array of sophisticated techniques and software tools to elucidate hidden or complex biological data.

This book focuses on exploring the use of software fault prediction in building reliable and robust software systems. Chapter 4 describes the software fault datasets and diverse issues concerning fault datasets when building fault prediction models.

The book, while introducing readers to the auction mechanism for resource provisioning in cloud computing, also endeavors to provide structured literature on the subject.