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International Journal for Uncertainty Quantification
IF: 3.259 5-Year IF: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2018020362
pages 101-117


Ganeshsree Selvachandran
Department of Actuarial Science and Applied Statistics, Faculty of Business & Information Science, UCSI University, Jalan Menara Gading, 56000 Cheras, Kuala Lumpur, Malayasia
Prem Kumar Singh
Amity Institute of Information Technology, Amity University, Sector-125, Noida – 201313, UP, India


This paper is focused on handling complex data sets using the properties of interval-valued complex fuzzy sets (IVCFSs). We extend the IV-CFS model to include a generalization parameter that reflects the opinion of experts to validate the information provided by the users. Our proposed generalized interval-valued complex fuzzy soft set model allows users to indicate their confidence in the data through the interval-based membership structure. The built-in validation mechanism in the model provides a robust framework that allows experts to ratify the individual hesitancy of the users supplying data to the system. To further enhance the utility of the proposed model, we introduce a weighted geometric aggregation operator and an accompanying score function. This aggregation operator reduces the multiple components in the proposed model into a single component with the aim of analyzing the decision-making process in a precise manner. An application of the aggregation operator and score function is demonstrated via a MADM problem related to measuring the effects of the implementation of TPPA by the Malaysian government on selected sectors of the Malaysian economy, and the time taken for these effects to manifest itself on the economic sectors that are considered. The results derived from this method is then corroborated using the interval-valued complex fuzzy concept lattice method.