Engineering Applications of Neural Networks

1. Front Matter

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2. Intelligent Agents Networks Employing Hybrid Reasoning: Application in Air Quality Monitoring and Improvement

   • Lazaros S. Iliadis, A. Papaleonidas

   Pages 1-16

3. Neural Network Based Damage Detection of Dynamically Loaded Structures

   • David Lehký, Drahomír Novák

   Pages 17-27

4. Reconstruction of Cross-Sectional Missing Data Using Neural Networks

   • Iffat A. Gheyas, Leslie S. Smith

   Pages 28-34

5. Municipal Creditworthiness Modelling by Kernel-Based Approaches with Supervised and Semi-supervised Learning

   • Petr Hajek, Vladimir Olej

   Pages 35-44

6. Clustering of Pressure Fluctuation Data Using Self-Organizing Map

   • Masaaki Ogihara, Hideyuki Matsumoto, Tamaki Marumo, Chiaki Kuroda

   Pages 45-54

7. Intelligent Fuzzy Reasoning for Flood Risk Estimation in River Evros

   • Lazaros S. Iliadis, Stephanos Spartalis

   Pages 55-66

8. Fuzzy Logic and Artificial Neural Networks for Advanced Authentication Using Soft Biometric Data

   • Mario Malcangi

   Pages 67-78

9. Study of Alpha Peak Fitting by Techniques Based on Neural Networks

   • Javier Miranda, Rosa Pérez, Antonio Baeza, Javier Guillén

   Pages 79-85

10. Information Enhancement Learning: Local Enhanced Information to Detect the Importance of Input Variables in Competitive Learning

    • Ryotaro Kamimura

    Pages 86-97

11. Flash Flood Forecasting by Statistical Learning in the Absence of Rainfall Forecast: A Case Study

    • Mohamed Samir Toukourou, Anne Johannet, Gérard Dreyfus

    Pages 98-107

12. An Improved Algorithm for SVMs Classification of Imbalanced Data Sets

    • Cristiano Leite Castro, Mateus Araujo Carvalho, Antônio Padua Braga

    Pages 108-118

13. Visualization of MIMO Process Dynamics Using Local Dynamic Modelling with Self Organizing Maps

    • Ignacio Díaz, Abel A. Cuadrado, Alberto B. Diez, Juan J. Fuertes, Manuel Domínguez, Miguel A. Prada

    Pages 119-130

14. Data Visualisation and Exploration with Prior Knowledge

    • Martin Schroeder, Dan Cornford, Ian T. Nabney

    Pages 131-142

15. Reducing Urban Concentration Using a Neural Network Model

    • Leandro Tortosa, José F. Vicent, Antonio Zamora, José L. Oliver

    Pages 143-152

16. Dissimilarity-Based Classification of Multidimensional Signals by Conjoint Elastic Matching: Application to Phytoplanktonic Species Recognition

    • Émilie Caillault, Pierre-Alexandre Hébert, Guillaume Wacquet

    Pages 153-164

17. Revealing the Structure of Childhood Abdominal Pain Data and Supporting Diagnostic Decision Making

    • Adam Adamopoulos, Mirto Ntasi, Seferina Mavroudi, Spiros Likothanassis, Lazaros Iliadis, George Anastassopoulos

    Pages 165-177

18. Relating Halftone Dot Quality to Paper Surface Topography

    • Pekka Kumpulainen, Marja Mettänen, Mikko Lauri, Heimo Ihalainen

    Pages 178-189

19. Combining GRN Modeling and Demonstration-Based Programming for Robot Control

    • Wei-Po Lee, Tsung-Hsien Yang

    Pages 190-199

20. Discriminating Angry, Happy and Neutral Facial Expression: A Comparison of Computational Models

    • Aruna Shenoy, Sue Anthony, Ray Frank, Neil Davey

    Pages 200-209

A cursory glance at the table of contents of EANN 2009 reveals the am- ing range of neural network and related applications. A random but revealing sample includes: reducing urban concentration, entropy topography in epil- tic electroencephalography, phytoplanktonic species recognition, revealing the structure of childhood abdominal pain data, robot control, discriminating angry and happy facial expressions, ?ood forecasting, and assessing credit worthiness. The diverse nature of applications demonstrates the vitality of neural comp- ing and related soft computing approaches, and their relevance to many key contemporary technological challenges. It also illustrates the value of EANN in bringing together a broad spectrum of delegates from across the world to learn from each other’s related methods. Variations and extensions of many methods are well represented in the proceedings, ranging from support vector machines, fuzzy reasoning, and Bayesian methods to snap-drift and spiking neurons. This year EANN accepted approximately 40% of submitted papers for fu- length presentation at the conference. All members of the Program Committee were asked to participate in the reviewing process. The standard of submissions was high, according to the reviewers, who did an excellent job. The Program and Organizing Committees thank them. Approximately 20% of submitted - pers will be chosen, the best according to the reviews, to be extended and - viewedagainfor inclusionin a specialissueofthe journalNeural Computing and Applications. We hope that these proceedings will help to stimulate further research and development of new applications and modes of neural computing.

• Fuzzy
• Software
• artificial intelligence
• cluster analysis
• data mining
• data reconstruction
• development
• face recognition
• fuzzy logic
• intelligent agents
• modeling
• programming
• quality
• quality assurance
• visualization

• Faculty of Computing, London Metropolitan University, London, UK

  Dominic Palmer-Brown

• School of Computing, IT and Engineering, University of East London, London, UK

  Chrisina Draganova, Elias Pimenidis, Haris Mouratidis

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