Forest Fires Prediction by an Organization Based System
Fecha de publicación
Springer Science + Business Media
Advances in Practical Applications of Agents and Multiagent Systems Advances in Intelligent and Soft Computing. Advances in Intelligent and Soft Computing. Volumen 70, pp. 135-144.
In this study, a new organization based system for forest fires prediction is presented. It is an Organization Based System for Forest Fires Forecasting (OBSFFF). The core of the system is based on the Case-Based Reasoning methodology, and it is able to generate a prediction about the evolution of the forest fires in certain areas. CBR uses historical data to create new solutions to current problems. The system employs a distributed multi-agent architecture so that the main components of the system can be remotely accessed. All the elements building the final system, communicate in a distributed way, from different type of interfaces and devices. OBSFFF has been applied to generate predictions in real forest fire situations, using historical data both to train the system and to check the results. Results have demonstrated that the system accurately predicts the evolution of the fires. It has been demonstrated that using a distributed architecture enhances the overall performance of the system.
978-3-642-12383-2 (Print) / 978-3-642-12384-9 (Online)
1867-5662 (Print) / 1867-5670 (Online)
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