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.
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Hernández, J.J.C., Sanchez Fernandez, L.P., Oropeza Rodríguez, J.L., Felipe Riverón, E.M. (2009). Signal Analysis for Assessment and Prediction of the Artificial Habitat in Shrimp Aquaculture. In: Bayro-Corrochano, E., Eklundh, JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10268-4_42
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DOI: https://doi.org/10.1007/978-3-642-10268-4_42
Publisher Name: Springer, Berlin, Heidelberg
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