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An intuitionistic fuzzy rough model is a hybrid model that combines intuitionistic fuzzy sets and rough sets, addressing soft computing and ambiguity. It uses lower and upper approximation spaces in various fields, including science, technology, database systems, computer networks, and expert system architecture. The matrix of adjacency of an intuitionistic fuzzy rough graph is described in the article. The matrix of adjacency also provides the upper and lower bounds for Laplacian energy. These are used to define the Laplacian energies of intuitionistic fuzzy rough graphs and the weight function of Laplacian energy within these graphs. The intuitionistic fuzzy rough preference relation method is used for processing the intuitionistic fuzzy rough weighted average. This technique is applied in data visualizations, which make data understandable by displaying it in a graphical or pictorial style. It supports decision-making and provides factual justification. This approach benefits any field that needs creative methods for presenting large volumes of complex data. Modern computer graphics have significantly influenced visualization.
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