Hiryuu Analysis
Revision as of 19:12, 21 February 2017 by Qianpin.lin.2013 (talk | contribs)
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| Data Preparation | Analysis |
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Contents
Exploratory
Exploratory
Time-Series
Time-Series
Clustering
Clustering
Geospatial
Geospatial
Simple Plot
Neighbouring Polygons Patterns
We observed that neighbouring cities around a city with a high number of inbounds tended to have higher inbounds than others as well. So hence we suspect that neigbouring inbound might be affected. Spatial randomness analysis will be relevant here, specifically Moran I and Geary’s C. We suspect that with time when we input failure points into this map and perform the same analysis, we might be able to find some pattern. Such that areas that tend to have high failures have neighbouring cities that also have failures. And possible explanations could be the transport mode, or transport companies that are assigned to handle these areas. These kind of information is rather useful to our sponsor.
