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논문

Hidden Markov Model and Self-organizing Map Applied to Exploration of Movement Behaviors of Daphnia magna (Cladocera: Daphniidae)

https://doi.org/10.3938/jkps.56.1003

  • 저자Chon, Tae-Soo
  • 학술지Journal of Korean Physical Society 56
  • 등재유형
  • 게재일자(2010)


Response behaviors of indicator species have been used for monitoring environmental disturbances. Markov processes were applied to elucidation of behavioral changes of animals. Movement of Daphnia magna in two dimensions was continuously observed before and after the treatments of an insecticide, diazinon, at low concentration. The Self-Organizing Map (SOM) was initially used to train complex ment data to classify different ment states. Subsequently, a hidden Markov model (HMM) was applied to sequencing the ment states identified by the SOM. Transition probability matrix (TPM) and emission probability matrix (EPM) were efficiently estimated by HMM. Markov processes were separately observed before and after the treatments, and the changes in the response behaviors of indicator organisms were demonstrated in stressful conditions


Response behaviors of indicator species have been used for monitoring environmental disturbances. Markov processes were applied to elucidation of behavioral changes of animals. Movement of Daphnia magna in two dimensions was continuously observed before and after the treatments of an insecticide, diazinon, at low concentration. The Self-Organizing Map (SOM) was initially used to train complex ment data to classify different ment states. Subsequently, a hidden Markov model (HMM) was applied to sequencing the ment states identified by the SOM. Transition probability matrix (TPM) and emission probability matrix (EPM) were efficiently estimated by HMM. Markov processes were separately observed before and after the treatments, and the changes in the response behaviors of indicator organisms were demonstrated in stressful conditions

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