Advances in Applications of Data-Driven Computing

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Éditeur :

Springer


Collection :

Advances in Intelligent Systems and Computing

Paru le : 2021-04-16

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Description

This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today’s software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. Original research and review works with model and build data-driven applications using computational algorithm are included as chapters in this book. 
Pages
182 pages
Collection
Advances in Intelligent Systems and Computing
Parution
2021-04-16
Marque
Springer
EAN papier
9789813369184
EAN PDF
9789813369191

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
18
Taille du fichier
6871 Ko
Prix
126,59 €
EAN EPUB
9789813369191

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
18
Taille du fichier
26296 Ko
Prix
126,59 €