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Algorithms after Dijkstra and Kruskal for Big Data and IoT Toolkit

Ovak Technologies

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The Algorithms after Dijkstra and Kruskal for Big Data and IoT Toolkit provides shortest-path and minimum-spanning tree-finding algorithms.

The Algorithms after Dijkstra and Kruskal for Big Data and IoT Toolkit is a software add-on for LabVIEW. This add-on helps you find the shortest path between two points for vehicle routing problems, survivable network design problem, and more. It includes the autoconfig protocol for Ethernet bridging to avoid cycles in a network. The add-on’s features include approximation algorithms for NP-hardness problems, feature-learning for real-time face verification, image registration with Rényi entropy, and model locality of particle interactions in turbulent fluid flows. The Algorithms after Dijkstra and Kruskal for Big Data and IoT Toolkit also helps you find the minimum-spanning tree of a graph.

Part Number(s): 784952-35

Disclaimer: The Third-Party Add-Ons for LabVIEW on this page are offered by independent third-party providers who are solely responsible for these products. NI has no responsibility whatsoever for the performance, product descriptions, specifications, referenced content, or any and all claims or representations of these third-party providers. NI makes no warranty whatsoever, neither express nor implied, with respect to the goods, the referenced contents, or any and all claims or representations of the third-party providers.