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Open AccessArticle

Using Intelligent Clustering to Implement Geometric Computation for Electoral Districting

1
Department of Mechatronic Engineering, Huafan University, New Taipei 22301, Taiwan
2
Department of Biotechnology, Mingchuan University, Taoyuan 33348, Taiwan
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(9), 369; https://doi.org/10.3390/ijgi8090369
Received: 30 June 2019 / Revised: 14 August 2019 / Accepted: 21 August 2019 / Published: 23 August 2019
(This article belongs to the Special Issue Deep Learning and Computer Vision for GeoInformation Sciences)
Traditional electoral districting is mostly carried out by artificial division. It is not only time-consuming and labor-intensive, but it is also difficult to maintain the principles of fairness and consistency. Due to specific political interests, objectivity is usually distorted and controversial in a proxy-election. In order to reflect the spirit of democracy, this study uses computing technologies to automatically divide the constituency and use the concepts of “intelligent clustering” and “extreme arrangement” to conquer many shortcomings of traditional artificial division. In addition, various informational technologies are integrated to obtain the most feasible solutions within the maximum capabilities of the computing system, yet without sacrificing the global representation of the solutions. We take Changhua County, Taiwan as an example of complete electoral districting, and find better results relative to the official version, which obtained a smaller difference in the population of each constituency, more complete and symmetrical constituencies, and fewer regional controversies. Our results demonstrate that multidimensional algorithms using a geographic information system could solve many problems of block districting to make decisions based on different needs. View Full-Text
Keywords: gerrymandering; plurality voting system; majority rule; NP-hard; cluster analysis; symmetry computing gerrymandering; plurality voting system; majority rule; NP-hard; cluster analysis; symmetry computing
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Hung, Y.-C.; Chen, L.-Y. Using Intelligent Clustering to Implement Geometric Computation for Electoral Districting. ISPRS Int. J. Geo-Inf. 2019, 8, 369.

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