.png){kind=icon}
.png){kind=icon}
Return
The Spatial Disaggregation Problem: Simulating Reasoning Using a Fuzzy Inference System
.png){kind=icon}
PRE
AI
DOI：10.1109/TFUZZ.2016.2567452.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The spatial disaggregation problem is an interesting problem when investigating and processing geographically correlated data; it is a special case of the map overlay problem. The map overlay problem occurs when data that are presented in incompatible grids need to be combined or compared; the spatial disaggregation problem is a special case in which the cells of one grid partition the cells of the other grid. The main reason for spatial disaggregation is to increase the spatial resolution of the data. Traditionally, similar methods as for the map overlay problem are used; fairly straightforward assumptions on the geographical distribution of the data are made, but these assumptions do not match the real-world situation. The approach presented in this contribution uses additionally available data (proxy data) that provides information on the geographic distribution of the input data. As will be illustrated, having this proxy data still does not provide for a straightforward solution and incorporating it inquires some form of reasoning which will be achieved by means of a dynamically constructed fuzzy inference system.
Keywords:
Fuzzy inference system
fuzzy spatial reasoning
map overlay problem
spatial disaggregation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
11.9
Papers:
5.0K
Citations:
2.9W