Artificial Neural Networks - ICANN 2007

Artificial Neural Networks - ICANN 2007
Author: Joaquim Marques de Sá
Publisher: Springer
Total Pages: 999
Release: 2007-09-14
Genre: Computers
ISBN: 3540746900

This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.

Nonlinear Modeling

Nonlinear Modeling
Author: Johan A. K. Suykens
Publisher: Springer Science & Business Media
Total Pages: 284
Release: 1998-06-30
Genre: Language Arts & Disciplines
ISBN: 9780792381952

This collection of eight contributions presents advanced black-box techniques for nonlinear modeling. The methods discussed include neural nets and related model structures for nonlinear system identification, enhanced multi-stream Kalman filter training for recurrent networks, the support vector method of function estimation, parametric density estimation for the classification of acoustic feature vectors in speech recognition, wavelet based modeling of nonlinear systems, nonlinear identification based on fuzzy models, statistical learning in control and matrix theory, and nonlinear time- series analysis. The volume concludes with the results of a time- series prediction competition held at a July 1998 workshop in Belgium. Annotation copyrighted by Book News, Inc., Portland, OR.

Advances in Neural Networks -- ISNN 2011

Advances in Neural Networks -- ISNN 2011
Author: Derong Liu
Publisher: Springer
Total Pages: 667
Release: 2011-05-20
Genre: Computers
ISBN: 3642211054

The three-volume set LNCS 6675, 6676 and 6677 constitutes the refereed proceedings of the 8th International Symposium on Neural Networks, ISNN 2011, held in Guilin, China, in May/June 2011. The total of 215 papers presented in all three volumes were carefully reviewed and selected from 651 submissions. The contributions are structured in topical sections on computational neuroscience and cognitive science; neurodynamics and complex systems; stability and convergence analysis; neural network models; supervised learning and unsupervised learning; kernel methods and support vector machines; mixture models and clustering; visual perception and pattern recognition; motion, tracking and object recognition; natural scene analysis and speech recognition; neuromorphic hardware, fuzzy neural networks and robotics; multi-agent systems and adaptive dynamic programming; reinforcement learning and decision making; action and motor control; adaptive and hybrid intelligent systems; neuroinformatics and bioinformatics; information retrieval; data mining and knowledge discovery; and natural language processing.

Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022

Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022
Author: Aboul Ella Hassanien
Publisher: Springer Nature
Total Pages: 844
Release: 2022-11-17
Genre: Technology & Engineering
ISBN: 3031206010

This proceedings book constitutes the refereed proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics (AISI 2021), which took place in Cairo, Egypt, during November 20–22, 2022, and is an international interdisciplinary conference that presents a spectrum of scientific research on all aspects of informatics and intelligent systems, technologies, and applications.

Advances in Data Analysis with Computational Intelligence Methods

Advances in Data Analysis with Computational Intelligence Methods
Author: Adam E Gawęda
Publisher: Springer
Total Pages: 417
Release: 2017-09-21
Genre: Technology & Engineering
ISBN: 3319679465

This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few. At the same time, the book recognizes and honors Professor Żurada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields. The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.

A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation
Author: Hongjun Guan
Publisher: Infinite Study
Total Pages: 18
Release:
Genre: Mathematics
ISBN:

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data.

Hybridization, Diagnostic and Prognostic of PEM Fuel Cells

Hybridization, Diagnostic and Prognostic of PEM Fuel Cells
Author: Samir Jemei
Publisher: John Wiley & Sons
Total Pages: 190
Release: 2018-10-22
Genre: Science
ISBN: 1119563445

Hydrogen is the most abundant element in the universe. It has a place in the energy mix of the future, especially regarding fuel cells (FCs). This book is an investigation into FCs. Prominence is given to the subject of PEMFCs (proton exchange membrane fuel cells) as they offer interesting perspectives on transport and stationary applications. This being said, a number of technological and scientific obstacles remain to be overcome before an industrial level of development can be reached.

Advances in Computational Intelligence

Advances in Computational Intelligence
Author: Ignacio Rojas
Publisher: Springer
Total Pages: 938
Release: 2019-06-05
Genre: Computers
ISBN: 3030205185

This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on machine learning in weather observation and forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface systems; random-weights neural networks; pattern recognition; deep learning and natural language processing; software testing and intelligent systems; data-driven intelligent transportation systems; deep learning models in healthcare and biomedicine; deep learning beyond convolution; artificial neural network for biomedical image processing; machine learning in vision and robotics; system identification, process control, and manufacturing; image and signal processing; soft computing; mathematics for neural networks; internet modeling, communication and networking; expert systems; evolutionary and genetic algorithms; advances in computational intelligence; computational biology and bioinformatics.