Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
A knowledge-intensive, integrated approach to problem solving and sustained learning
A knowledge-intensive, integrated approach to problem solving and sustained learning
Machine Learning
Self-organizing maps
Measures for the organization of self-organizing maps
Self-Organizing neural networks
FSfRT: Forecasting System for Red Tides
Applied Intelligence
Case base building with similarity relations
Information Sciences: an International Journal
A new hybrid case-based architecture for medical diagnosis
Information Sciences—Informatics and Computer Science: An International Journal
eParticipative process learning: process-oriented experience management and conflict solving
Data & Knowledge Engineering - Special issue: Collaborative business process technologies
Explanation in Case-Based Reasoning---Perspectives and Goals
Artificial Intelligence Review
Distributed case-based reasoning
The Knowledge Engineering Review
A case-based reasoning system for PCB principal process parameter identification
Expert Systems with Applications: An International Journal
Applying lazy learning algorithms to tackle concept drift in spam filtering
Expert Systems with Applications: An International Journal
Hybrid multi-agent architecture as a real-time problem-solving model
Expert Systems with Applications: An International Journal
Modelling surface radioactive, chemical and oil spills in the Strait of Gibraltar
Computers & Geosciences
GerAmi: Improving Healthcare Delivery in Geriatric Residences
IEEE Intelligent Systems
Recognizing yield patterns through hybrid applications of machine learning techniques
Information Sciences: an International Journal
Incremental construction of classifier and discriminant ensembles
Information Sciences: an International Journal
Case-based retrieval to support the treatment of end stage renal failure patients
Artificial Intelligence in Medicine
Case-based reasoning in the health sciences: What's next?
Artificial Intelligence in Medicine
Current data assimilation modelling for oil spill contingency planning
Environmental Modelling & Software
ViSOM ensembles for visualization and classification
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Boosting unsupervised competitive learning ensembles
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Hybrid artificial intelligence methods in oceanographic forecast models
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Neural Networks
A dynamic classifier ensemble selection approach for noise data
Information Sciences: an International Journal
Genetic algorithms to simplify prognosis of endocarditis
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
A novel CBR system for numeric prediction
Information Sciences: an International Journal
A bio-inspired fusion method for data visualization
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Sparsely connected neural network-based time series forecasting
Information Sciences: an International Journal
Information Sciences: an International Journal
Case-based strategies for argumentation dialogues in agent societies
Information Sciences: an International Journal
(OBIFS) isotropic image analysis for improving a predicting agent based systems
Expert Systems with Applications: An International Journal
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Oil spills represent one of the most destructive environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be critical in reducing environmental risks. The system presented here uses the Case-Based Reasoning (CBR) methodology to forecast the presence or absence of oil slicks in certain open sea areas after an oil spill. CBR is a computational methodology designed to generate solutions to certain problems by analysing previous solutions given to previously solved problems. The proposed CBR system includes a novel network for data classification and retrieval. This type of network, which is constructed by using an algorithm to summarize the results of an ensemble of Self-Organizing Maps, is explained and analysed in the present study. The Weighted Voting Superposition (WeVoS) algorithm mainly aims to achieve the best topographically ordered representation of a dataset in the map. This study shows how the proposed system, called WeVoS-CBR, uses information such as salinity, temperature, pressure, number and area of the slicks, obtained from various satellites to accurately predict the presence of oil slicks in the north-west of the Galician coast, using historical data.