On terrain coverage optimization by using a network approach for universal graph-based data mining and knowledge discovery

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Abstract

This conceptual paper discusses a graph-based approach for on-line terrain coverage, which has many important research aspects and a wide range of application possibilities, e.g in multi-agents. Such approaches can be used in different application domains, e.g. in medical image analysis. In this paper we discuss how the graphs are being generated and analyzed. In particular, the analysis is important for improving the estimation of the parameter set for the used heuristic in the field of route planning. Moreover, we describe some methods from quantitative graph theory and outline a few potential research routes. © 2014 Springer International Publishing.

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APA

Preuß, M., Dehmer, M., Pickl, S., & Holzinger, A. (2014). On terrain coverage optimization by using a network approach for universal graph-based data mining and knowledge discovery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8609 LNAI, pp. 564–573). Springer Verlag. https://doi.org/10.1007/978-3-319-09891-3_51

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