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E-raamat: Advances in Hybridization of Intelligent Methods: Models, Systems and Applications

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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.


Deep Learning Approaches for Facial Emotion Recognition: A Case Study on FER-2013
1(16)
Panagiotis Giannopoulos
Isidoros Perikos
Ioannis Hatzilygeroudis
Analysis of Biologically Inspired Swarm Communication Models
17(22)
Musad Haque
Electa Baker
Christopher Ren
Douglas Kirkpatrick
Julie A. Adams
Target-Dependent Sentiment Analysis of Tweets Using Bidirectional Gated Recurrent Neural Networks
39(18)
Mohammed Jabreel
Fadi Hassan
Antonio Moreno
Traffic Modelling, Visualisation and Prediction for Urban Mobility Management
57(14)
Tomasz Maniak
Rahat Iqbal
Faiyaz Doctor
Assurance in Reinforcement Learning Using Quantitative Verification
71(26)
George Mason
Radu Calinescu
Daniel Kudenko
Alec Banks
Distillation of Deep Learning Ensembles as a Regularisation Method
97(22)
Alan Mosca
George D. Magoulas
Heuristic Constraint Answer Set Programming for Manufacturing Problems
119
Erich C. Teppan
Gerhard Friedrich