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In many applications of Wireless Sensor Networks (WSN), it is crucial to know the location of sensor nodes. Although several methods have been proposed, most of them have poor performance in irregularly shaped networks. MDS-MAP is one of the localization methods based on multidimensional scaling (MDS) technique. It uses the connectivity information to derive the location of the nodes in the network. In presence of additional data such as estimated distances between adjacent neighbors, it can also enhance the localization precision. Since MDS-MAP uses the length of the shortest path as Euclidian distance between the nodes, it is sensitive to the shape of the network. In this paper we present MDS-MAP(I), a modified algorithm based on MDS-MAP which improves the localization task in irregular networks. The simulation results show that the algorithm is more reliable in various topologies and achieves a significant performance improvement upon existing method.