Akademik Veri Yönetim Sistemi
Neutrosophic Computing and Vague Data Analysis, Florentin Smarandache,Zahid Khan, Editör, Chapman & Hall/Crc Press, Florida, ss.64-87, 2026
This chapter introduces an innovative method for determining the correlation coefficient between single-valued neutrosophic sets and applies it to the selection of suitable renewable energy sources using a decision-making framework. The proposed method addresses the limitations of existing approaches, which often lack reliability, precision, and accuracy. Several theoretical properties are established to validate the soundness of the new correlation coefficient measure. Furthermore, comparative analyses with existing single-valued neutrosophic correlation methods demonstrate the enhanced performance and compliance of the proposed method with the fundamental conditions of a correlation coefficient. The findings confirm that the developed method produces consistent and reliable results, offering improved analytical accuracy over current techniques. Its application to renewable energy source selection further shows that uncertainties inherent in decision-making can be effectively managed. Overall, this chapter underscores the potential of soft computing techniques–particularly the single-valued neutrosophic correlation coefficient–in addressing vagueness and supporting more informed decision-making processes.