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논문

Simulating the architecture of a termite incipient nest using a convolutional neural network

등록일자 :

https://doi.org/10.1016/j.ecoinf.2018.02.003

  • 저자Jeong-Kweon Seo,Seongbok Baik,이상희
  • 학술지Ecological Informatics (1574-9541), 44, 94 ~ 100
  • 등재유형SCIE
  • 게재일자 20180301
Subterranean termites form colonies containing thousands of individuals, and maintain these colonies by consuming wood and other materials containing cellulose. In this consumption process, they cause serious damage to wooden structures. Information on the population size of termites is an important factor in developing strategies aimed at controlling termites. In this study, we provide a reasonable possibility of estimating the population of an incipient nest dug by a colony that has not yet discovered any food source. We build an agentbased model to simulate termite tunnel patterns in which the behavior of simulated termites (agents) is governed by simple rules based on empirical data. The simulated termites do not communicate with each other using pheromones.

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