Signal analysis for assessment and prediction of the artificial habitat in shrimp aquaculture

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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 physicalchemical 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.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision and Applications - 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Proceedings
Pages353-360
Number of pages8
DOIs
StatePublished - 2009
Event14th Iberoamerican Conference on Pattern Recognition, CIARP 2009 - Guadalajara, Jalisco, Mexico
Duration: 15 Nov 200918 Nov 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5856 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Iberoamerican Conference on Pattern Recognition, CIARP 2009
Country/TerritoryMexico
CityGuadalajara, Jalisco
Period15/11/0918/11/09

Keywords

  • Assessment
  • Fuzzy inference systems
  • Prediction
  • Signal analysis

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