Multi criteria decision analysis for classification and ranking problems in uncertain and non-deterministic environment
| dc.contributor.advisor | Sanjay Kumar | |
| dc.contributor.author | Singh, Akanksha | |
| dc.date.accessioned | 2021-02-01T06:48:39Z | |
| dc.date.available | 2021-02-01T06:48:39Z | |
| dc.date.issued | 2020-10 | |
| dc.description.abstract | Multi-criteria decision analysis (MCDA) which consists of classification and multi criteria decision making (MCDM). MCDA has various applications in many real life problems of pattern recognition, medical diagnosis, image recognition, speech recognition, banking, water resource location, human resource development, resource allocation and portfolio selection. The present research work mainly focus on development and implementation of MCDA models in environment of uncertainty and hesitation. In this study, 7 different models of MCDA are developed in intuitionistic fuzzy, picture fuzzy, dual hesitant fuzzy and hesitant probabilistic fuzzy linguistic environment. Model 1 is a novel construction method of IFS from fuzzy set which address limitations of existing conversion method of Jurio et al. (2010). Further, a novel dice similarity measure for IFSs also proposed and applied in pattern and face recognition. Model 2 is dual hesitant fuzzy set and intuitionistic fuzzy ideal based computational method for MCGDM problem. In this model new semi ring is used to idealize IF preference relations. Model 3 is picture fuzzy parameterized soft set based decision making method. In this model a conversion method of PFS from IFS is also developed. Model 4 is picture fuzzy Choquet integral-based VIKOR for MCDM problems. Model 5 is a novel MCDM method combining QFD with Choquet integral for social networking site selection from user’s perspective in intuitionistic fuzzy environment. Model 6 is QFD approach for MCDM in picture fuzzy environment. In this model an innovative way of dealing with negative correlation is developed. Model 7 is AHP for HPFLS with applications to MCDM method. All developed models (Models [1-7]) are implemented in real life problems of pattern recognition, medical diagnosis, face recognition, supplier selection problem, candidate selection problem, real estate investment problem ranking of organizations and ranking of social networking sites. To examine the validity of results validity test of all models (Model [2-7]) under certain criteria are also done along with comparative analysis. | en_US |
| dc.identifier.uri | https://krishikosh.egranth.ac.in/handle/1/5810160763 | |
| dc.keywords | decision analysis, classification, ranking | en_US |
| dc.language.iso | English | en_US |
| dc.pages | 230 | en_US |
| dc.publisher | G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand) | en_US |
| dc.research.problem | Fuzzy Logic | en_US |
| dc.sub | Mathematics | en_US |
| dc.theme | Decision Making | en_US |
| dc.these.type | Ph.D | en_US |
| dc.title | Multi criteria decision analysis for classification and ranking problems in uncertain and non-deterministic environment | en_US |
| dc.type | Thesis | en_US |