Applications and Innovations in Intelligent Systems XIII Proceedings of AI2005, the Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artifical Intelligence /
The papers in this volume are the refereed application papers presented at AI-2005, the Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2005. The papers in this volume present new and innovative developmen...
Clasificación: | Libro Electrónico |
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Autor Corporativo: | |
Otros Autores: | , , |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
London :
Springer London : Imprint: Springer,
2006.
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Edición: | 1st ed. 2006. |
Temas: | |
Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Application Keynote Address
- Legal Engineering: A structural approach to Improving Legal Quality
- Best Application Paper
- Case-Based Reasoning Investigation of Therapy Inefficacy
- Applied Al in Information Processing
- Hybrid search algorithm applied to the colour quantisation problem
- The Knowledge Bazaar
- Generating Feedback Reports for Adults Taking Basic Skills Tests
- A Neural Network Approach to Predicting Stock Exchange Movements using External Factors
- Techniques for Applied Al
- A Fuzzy Rule-Based Approach for the Collaborative Formation of Design Structure Matrices
- Geometric Proportional Analogies In Topographic Maps: Theory and Application
- Experience with Ripple-Down Rules
- Applying Bayesian Networks for Meteorological Data Mining
- Industrial Applications
- WISE Expert: An Expert System for Monitoring Ship Cargo Handling
- A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot
- An Application of Artificial Intelligence to the Implementation of Virtual Automobile Manufacturing Enterprise
- Medical Applications
- Web-based Medical Teaching using a Multi-Agent System
- Building an Ontology and Knowledge Base of the Human Meridian-Collateral System
- The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data.