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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
Modeling for the agro ,[object Object]
Bio-inspired systems: family album  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],By studying, understanding and exploiting nature’s “tricks”  and “artifices”, engineers can provide innovative solutions  to engineering problems
Features of bio-inspired techniques ,[object Object],[object Object],[object Object],[object Object]
Modeling process numerical data noisy data non-numerical data training test design loop model validation loop model inputs prediction explanation/ visualization
hypothesis modeling simulation prediction explanation
Prediction-oriented experiments using the CENICA ÑA  database highly dimensional numerical data (temp,HR, radiacion, préc., edad cosecha, num. cortes) non-numerical data (zona agroecologica) supervised training simulation prediction
Characterization-oriented experiments using the CENICA ÑA  database highly dimensional numerical data (temp,HR, radiacion, préc.,  edad cosecha, corte ) non-numerical data (zona agroecologica) self-organization simulation test/prediction explanation & visualization
Research issues I ,[object Object],[object Object]
Research issues II ,[object Object],[object Object]
Research issues III ,[object Object],[object Object]
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

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The COCH project

  • 1. 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
  • 2.
  • 3.
  • 4.
  • 5. Modeling process numerical data noisy data non-numerical data training test design loop model validation loop model inputs prediction explanation/ visualization
  • 6. hypothesis modeling simulation prediction explanation
  • 7. Prediction-oriented experiments using the CENICA ÑA database highly dimensional numerical data (temp,HR, radiacion, préc., edad cosecha, num. cortes) non-numerical data (zona agroecologica) supervised training simulation prediction
  • 8. Characterization-oriented experiments using the CENICA ÑA database highly dimensional numerical data (temp,HR, radiacion, préc., edad cosecha, corte ) non-numerical data (zona agroecologica) self-organization simulation test/prediction explanation & visualization
  • 9.
  • 10.
  • 11.
  • 12. 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