Type Accounting: A Mechanism for Growing Implicit Geo-Number Chains for Multi-Objective Evolutionary Geometry

Abstract

Empirical evidence from studies linking geographic factors such as topography and natural resources to map artifacts is often weak, and procedural management of different samples or codes is unreliable. We found a general weakness in these investigations: Although most map products are limited in their historical conception to the functional validity study component, the analysis of implicit geo-data therein relies almost exclusively on national-level data. Based on algorithmic interventions, We extrapolated the use of GIS to accurately measure spatial variation factors in conflicting map products. A comparison of several relevant variables measured at the national and conflict scale showed that national statistics were found to be poor approximations of conflict areas (areas where civilizations meet). The computational analysis further shows that some of the survey results do depend on the scale of measurement, and that a suture mechanism for the implicit geo-number chain can be identified. Finally, we discuss how multi-objective optimization algorithms can be applied in future research for rapid ranking and improvement of GIS and space to increase our understanding of conflict regions, durations, and biased outcomes during the multi-objective evolution of this type of map products.