Advances in Hybridization of Intelligent Methods

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.

Inhalt
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.