Analysis and Application of Animal Survival under Urban Ecological Space Based on Deep Learning Method

  • Xiangli Xia
Keywords: Deep Learning, Urban Ecological Space, Animal Survival and Protection, Evaluation System

Abstract

With the rapid development of the economy, the wave of urbanization has brought considerable
pressure on the urban living environment and the health of urban residents. To solve these problems, eco-city
construction provides basic solutions and ideas for urban development. Through the use of deep learning
methods, using convolutional neural network CNN and deep confidence neural network DBN and other
methods, Haizhu Eco-city construction - Haizhu wetland ecological restoration as the object, from the protection
of wild animals, wildlife in the eco-city ecosystem In terms of survival energy and evaluation of its protective
effects, 16 indicators were selected to establish a wild animal protection and survival evaluation system for
Haizhu Eco-city, and evaluated by analytic hierarchy process and fuzzy mathematics. The final result is that the
number of existing wild animal populations needs to be restored. The animal resources in the region are far from
the historical records and literature records. The various groups have failed to reach the historical records,
especially in the field of birds; the protection effect of wild animals the evaluation is on the upper-middle level,
16 indicators are selected, and the fuzzy comprehensive evaluation method is adopted. The comprehensive
evaluation value of wild animal protection in the construction of Haizhu Eco-city is 63.32. It can be seen from
the evaluation model that the protection effect of wild animals in the construction of Haizhu Eco-city is now at a
medium to upper level.

Published
2019-11-01