A New Approach to Interval-Valued Fuzzy Soft Sets and Its Application in Decision-Making

Tripathy, B. K.; Sooraj, T. R.; Mohanty, Ramakanta

doi:10.1007/978-981-10-2525-9_1

Cited by 26 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Maji et al discussed an application of soft sets in decision making problems [3]. Some applications of various hybrid soft set models are discussed in [1,[7][8][9][10][11][12]. This study was further extended to the context of FSSs [6] where they identified some drawbacks in [3] and took care of these drawbacks while introducing an algorithm for decision making [6].…”

Section: Introductionmentioning

confidence: 94%

Fuzzy Soft Set Theory and Its Application in Group Decision Making

Sooraj

Mohanty

Tripathy

2016

Advanced Computing and Communication Technologies

Self Cite

View full text Add to dashboard Cite

Soft set theory was introduced by Molodtsov to handle uncertainty. It uses a family of subsets associated with each parameter. Hybrid models have been found to be more useful than the individual components. Earlier fuzzy set and soft set were combined to form fuzzy soft sets (FSS). Soft sets were defined from a different point of view in Tripathy et al. (Int J Reasoning-Based Intell Syst 7(3/4), 2015) where they used the notion of characteristic functions. Hence, many related concepts were also redefined. In Tripathy et al. (Proceedings of ICCIDM-2015 membership function for FSSs was defined. We propose a new algorithm by following this approach which provides an application of FSSs in group decision making. The performance of this algorithm is substantially improved than that of the earlier algorithm.

show abstract

Section: Introductionmentioning

confidence: 94%

Fuzzy Soft Set Theory and Its Application in Group Decision Making

Sooraj

Mohanty

Tripathy

2016

Advanced Computing and Communication Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…[8,26,31,34]. Due to advent of Internet of Things, smart cities, advanced medical devices, treatment through remote monitoring [1], etc., huge amount of data is being generated these days [40,41]. In order to reduce the comlexity of the machine learning and deep learning algorithms there exists a need for dimensionality reduction techniques which choose optimal dimensions for training the algorithms [28].…”

Section: Antlion Optimizationmentioning

confidence: 99%

Antlion re-sampling based deep neural network model for classification of imbalanced multimodal stroke dataset

Gadekallu

Bhattacharya

Maddikunta

et al. 2020

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“… Ashtiani et al (2009) and Mokhtarian (2015) extended TOPSIS method to interval-valued fuzzy sets. Tripathy, Sooraj & Mohanty (2017) employed a novel approach to IVFS-set for discussing DM situation. The HS-set provides a more simplistic modified version of the S-set that settles the barriers of the FS-set by making use of the multi-argument approximation operator (MAAO) instead of the single-argument approximation operator (SAAO).…”

Section: Introductionmentioning

confidence: 99%

A robust algorithmic cum integrated approach of interval-valued fuzzy hypersoft set and OOPCS for real estate pursuit

Arshad

Saeed

Rahman

et al. 2023

PeerJ Computer Science

View full text Add to dashboard Cite

Due to the vast variety of aspects that must be made—many of which are in opposition to one another—choosing a home can be difficult for those without much experience. Individuals need to spend more time making decisions because they are difficult, which results in making poor choices. To overcome residence selection issues, a computational approach is necessary. Unaccustomed people can use decision support systems to help them make decisions of expert quality. The current article explains the empirical procedure in that field in order to construct decision-support system for selecting a residence. The main goal of this study is to build a weighted product mechanism-based decision-support system for residential preference. The said house short-listing estimation is based on several key requirements derived from the interaction between the researchers and experts. The results of the information processing show that the normalized product strategy can rank the available alternatives to help individuals choose the best option. The interval valued fuzzy hypersoft set (IVFHS-set) is a broader variant of the fuzzy soft set that resolves the constraints of the fuzzy soft set from the perspective of the utilization of the multi-argument approximation operator. This operator maps sub-parametric tuples into a power set of universe. It emphasizes the segmentation of every attribute into a disjoint attribute valued set. These characteristics make it a whole new mathematical tool for handling problems involving uncertainties. This makes the decision-making process more effective and efficient. Furthermore, the traditional TOPSIS technique as a multi-criteria decision-making strategy is discussed in a concise manner. A new decision-making strategy, “OOPCS” is constructed with modifications in TOPSIS for fuzzy hypersoft set in interval settings. The proposed strategy is applied to a real-world multi-criteria decision-making scenario for ranking the alternatives to check and demonstrate their efficiency and effectiveness.

show abstract

A New Approach to Interval-Valued Fuzzy Soft Sets and Its Application in Decision-Making

Cited by 26 publications

References 13 publications

Fuzzy Soft Set Theory and Its Application in Group Decision Making

Fuzzy Soft Set Theory and Its Application in Group Decision Making

Antlion re-sampling based deep neural network model for classification of imbalanced multimodal stroke dataset

A robust algorithmic cum integrated approach of interval-valued fuzzy hypersoft set and OOPCS for real estate pursuit

Contact Info

Product

Resources

About