Sudarshan 01 03 This work uses a random point bipartite graph to present a new genetic algorithmbased graph clusteringmodel The model makes use of uniformly distributed random points in the data space and gap between these pointsand the test points is measured and regarded as closeness An adjacency matrix is produced using test points andrandom points Correlation coefficients are calculated using the provided bipartite graph to produce a similaritymatrix To find the cluster centers the eigenvectors of the weighted similarity matrixs singular value decompositionare taken into account and fed into an exclusive GA model The models performance has been compared to currentstandard algorithms and it has been tested using standard datasets Copyright (c) Journal of Engineering Technology and Sciences. All rights reserved 2026