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Title Advances in hybridization of intelligent methods : models, systems and applications / Ioannis Hatzilygeroudis, Vasile Palade, editors.

Published Cham, Switzerland : Springer, [2018]


Location Call No. Status
Physical description 1 online resource.
Series Smart innovation, systems and technologies, 2190-3018 ; volume 85
Smart innovation, systems, and technologies ; 85.
Springer Engineering eBooks 2018 English+International
Contents Deep Learning Approaches for Facial Emotion Recognition: A Case Study on FER-2013 -- Analysis of Biologically Inspired Swarm Communication Models -- Target-Dependent Sentiment Analysis of Tweets using Bi-directional Gated Recurrent Neural Networks -- Traffic Modelling, Visualisation and Prediction for Urban Mobility Management -- Assurance in Reinforcement Learning Using Quantitative Verification -- Distillation of Deep Learning Ensembles as a Regularisation method -- Heuristic Constraint Answer Set Programming for Manufacturing Problems.
Summary This book presents recent research on the hybridization of intelligent methods, which refers to combining methods to solve complex problems. It discusses hybrid approaches covering different areas of intelligent methods and technologies, such as neural networks, swarm intelligence, machine learning, reinforcement learning, deep learning, agent-based approaches, knowledge-based system and image processing. The book includes extended and revised versions of invited papers presented at the 6th International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2016), held in The Hague, Holland, in August 2016. The book is intended for researchers and practitioners from academia and industry interested in using hybrid methods for solving complex problems.
Other author Hatzilygeroudis, Ioannis, editor.
Palade, Vasile, 1964- editor.
SpringerLink issuing body.
Subject Artificial intelligence.
Soft computing.
Electronic books.
Electronic book.
ISBN 9783319667904 (electronic bk.)
3319667904 (electronic bk.)
9783319667898 (print)
Standard Number 10.1007/978-3-319-66790-4