MINIMAL SPANNING TREE ALGORITHMS IN COMPLEX BIPOLAR NEUTROSOPHIC ENVIRONMENTS: PRIM’S AND KRUSKAL’S

Abstract

In real-world circumstance where conclusion are ambiguity and inconsistent, fuzzy model graphs
frequently have a no good time appearing bipolar details that is confusion and complex. The present study
involving a new methodology for point-out minimal spanning trees (MSTs) in Bipolar Complex Neutrosophic
Weighted Connected Graphs (BCNWCGs) to correct this defect. We better the conventional algorithms,
specifically Kruskal’s and Prim’s , by attaching new function called score functions that are block out to
deal with the different levels of values like falsehood membership, truth, uncertainty memberships, and these
values are define in different intervals with positive and negative values these are involving in Bipolar Complex
Neutrosophic Weighted Connected Graphs (BCNWCGs). This work is completely based on the algorithms
and neutrosophic graph theory and its complex bipolar extension. The study decorate the two algorithms
Prim’s and Kruskal’s produces compatible weights which are minimal within the bipolar neutrosophic complex
framework, achieved through careful algorithmic mathematical formulation and comparing numerical values.
For Wi-Fi apps to work well, the signal strength must be right and the signal loss over distance must be kept
to a minimum.