DEVELOPMENT OF CLASSIFICATION MODEL TO PREDICT FLOOD-PRONE LOCATIONS USING GEOSPATIAL ARTIFICIAL INTELLIGENCE AND SNI 8197:2015 METHOD (CASE STUDY : GEOSPATIAL INFORMATION AGENCY)
Abstract— Geospatial information agency as data custodian of flood-prone requires a breakthrough innovation to predict flood-prone locations in real time. Currently, flood-prone data processing is carried out offline through a desktopbased spatial software. The emergence of integrated artificial i...
Saved in:
Main Author: | |
---|---|
Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/67211 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Be the first to leave a comment!