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Predictive Analytics for Reducing Human-Animal Conflict

Nitin Singh & K M Baharul Islam

International Journal of Development and Conflict2017article
ABDC B
Weight
0.26

Abstract

Forest-adjoining areas are prone to human-animal conflict. In such areas, there is an urgent need to develop methods that prevent animal intrusion in human habitats while also ensuring that wild animals are not harmed. We have applied data science to track animal (in this case, the Indian panther) movement in forests and animal intrusion in villages adjoining the forest environment. The Indian panther (Panthera pardus fusca) is a panther subspecies distributed across the Indian subcontinent. We find that analytics on pugmark data can be effectively applied to simulate movement of the animal and thus undertake preventive measures.

Cite this paper

@article{nitin2017,
  title        = {{Predictive Analytics for Reducing Human-Animal Conflict}},
  author       = {Nitin Singh & K M Baharul Islam},
  journal      = {International Journal of Development and Conflict},
  year         = {2017},
}

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Predictive Analytics for Reducing Human-Animal Conflict

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Evidence weight

0.26

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.00 × 0.4 = 0.00
M · momentum0.20 × 0.15 = 0.03
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.