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Assessing Activity Pattern Similarity with Multidimensional Sequence Alignment Based on a Multiobjective Optimization Evolutionary Algorithm
2014
Geographical Analysis
Due to the complexity and multidimensional characteristics of human activities, assessing the similarity of human activity patterns and classifying individuals with similar patterns remains highly challenging. This paper presents a new and unique methodology for evaluating the similarity among individual activity patterns. It conceptualizes multidimensional sequence alignment (MDSA) as a multiobjective optimization problem, and solves this problem with an evolutionary algorithm. The study
doi:10.1111/gean.12040
pmid:26190858
pmcid:PMC4501399
fatcat:ntbo5dcq35dqvmaslm2hafsshe