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Implementation of wavelets and artificial neural networks to detection of toxic response behavior of chironomids (Chironomidae: Diptera) for water quality monitoring
- Source :
- Ecological Modelling. 195:61-71
- Publication Year :
- 2006
- Publisher :
- Elsevier BV, 2006.
-
Abstract
- Movement behavior of Chironomus samoensis larvae was observed in response to the treatments of carbofuran, an anticholinesterase insecticide, at a low concentration (0.1 mg/l) in semi-natural conditions. Two typical movement patterns were selected before and after the treatments, and the variables characterizing movement tracks in two dimensions were analyzed by discrete wavelet transform (DWT) with Daubechie's 4 functions. The variables were selected based on the feature coefficients of DWT and were subsequently used as input for training with the multi-layer perceptron network. The trained network efficiently detected changes in movement patterns before and after the treatments. We demonstrated that the combined use of the wavelets and artificial neural networks would be a useful tool for automatic behavioral monitoring for water quality assessment.
- Subjects :
- Discrete wavelet transform
biology
Artificial neural network
Ecology
business.industry
Ecological Modeling
Pattern recognition
biology.organism_classification
Perceptron
Chironomidae
Wavelet
Environmental monitoring
Feature (machine learning)
Water quality
Artificial intelligence
business
Mathematics
Subjects
Details
- ISSN :
- 03043800
- Volume :
- 195
- Database :
- OpenAIRE
- Journal :
- Ecological Modelling
- Accession number :
- edsair.doi...........af8b1bdd00e7917800513171b05359a0