Signal Analysis for Assessment and Prediction of the Artificial Habitat in Shrimp Aquaculture

  • Authors:

  • José Juan Hernández;Luis Pastor Sanchez Fernandez;José Luis Oropeza Rodríguez;Edgardo Manuel Felipe Riverón

  • Affiliations:

  • Centre of Computer Research, National Polytechnic Institute, México, México;Centre of Computer Research, National Polytechnic Institute, México, México;Centre of Computer Research, National Polytechnic Institute, México, México;Centre of Computer Research, National Polytechnic Institute, México, México

  • Venue:
  • CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
  • Year:
  • 2009

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Abstract

This paper presents a novel work for prediction of artificial habitat in shrimp aquaculture based on environmental signal analysis. The physical-chemical variables that are involved into the system are studied for modeling and predicting environmental patterns.The prediction model is built using AR models that reconstruct a partial section of a particular measured signal. The physical-chemical variables are classified based on the negative ecological impact using a new statistical model that calculates the frequency and the deviation of the measurements. A fuzzy inference system processes the level classifications using aquaculture rules that define all the cases calculating the condition of the shrimp habitat.