M. Barreto, D. Jimenez, H. Satizabal, Andrés Pérez-Uribe, Eduardo Sanchez REDS Institute (http://reds.eivd.ch) University of Applied Sciences of Western-Switzerland - HEIG-VD The COCH project 27.02.06
Construction of models using growing data bases is a challenging issue. In our case, the information of fruit crops will be continuously collected along the modeling process, for this reason, the model must be able to adapt its parameters according to the changes of incoming information. This process is closely related to continuous online learning systems in which the model structure has to be plastic but stable enough to be able to learn new characteristics of data while retaining previous information
The modeling methodology has to allow for the possibility to include information gathered from multiple sources. We are interested to include expert knowledge, traditional knowledge, and information obtained by agronomical and climate analysis. In order to deal with multiple sources of diverse nature of data, we propose to develop a so-called “mixture of experts” approach.
Building a model is rarely an end in itself; instead, the goal of most analysis is to make a decision. To assist in this analysis, we propose the development of intelligent interfaces that allow for visual decision support based in bio-inspired techniques and data mining.
COCH 3i (“triple I”) research I ncremental modeling I ntegration of heterogeneous data I ntelligent visualization 4th dimension: model validation (usefulness & biological response) model exploitation