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

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. © 2009 Springer-Verlag Berlin Heidelberg.