ScholarGate
सहायक

विधियों की तुलना करें

चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।

PCA भारण×व्यापक दूरी-आधारित रैंकिंग×
क्षेत्रनिर्णयननिर्णयन
परिवारMCDMMCDM
उद्भव वर्ष19012022
प्रवर्तकPearson, K.Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P.
प्रकारWeight_Objective (PCA variance explained, eigenvector-based)Distance from PIS/NIS/AS (Euclidean × Taxicab combined)
मौलिक स्रोतPearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. (2022). A Novel Axiomatic DEA-COBRA Framework for Evaluating the Sustainable Performance of Agri-Food Systems. Sustainability link ↗
उपनाम
संबंधित88
सारांशPCA-WEIGHT (PCA Weighting — Principal Component Analysis based objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Pearson, K. in 1901. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.COBRA (COmprehensive distance Based RAnking) is a ranking multi-criteria decision-making (MCDM) method introduced by Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGateडेटासेट
  1. v1
  2. 1 स्रोत
  3. PUBLISHED
  1. v1
  2. 1 स्रोत
  3. PUBLISHED

खोज पर जाएँ स्लाइड डाउनलोड करें

ScholarGateविधियों की तुलना करें: PCA-WEIGHT · COBRA. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare