India is progressing economically, but it needs to pay more attention to social and human development together with women empowerment. The economic contribution and empowerment of women are pertinent to strengthen female’s rights andenable them have control on their lives and influence the society. Sustainable development can be achieved through economic empowerment of women. Empowered women and gender equality lead in multiplying the development efforts. Under the SDG-5, India has stated that it will ensure women and girls contribute as equivalent partners to growth and development of the country by 2030. At the global level too, it has been observed that if women participate equally with men in the economic activity, the world will add $11 trillion in the annual 2025 GDP. Investing on education and skill enhancement through Vocation education and training. has been a pertinent issue for the Indian government for the last decade. The current paper identifies the constructs of women empowerment and observes the role of formal and informal training in female empowerment. In all 317 women participated in the study through two stage sample design involving area sampling followed by convenience sampling. The study identified five constructs of women empowerment Economic Empowerment, Family Health and Well Being, Civic Empowerment, Social Empowerment, Educational Empowerment through exploratory factor analysis confirmed through confirmatory factor analysis.Further, the mean scores of all the constructs of women empowerment for formally trained respondents were higher than informally trained respondents but no significant difference between women empowerment, constructs of formally and informally trained womenobserved in the study.
Interval-valued intuitionistic fuzzy environment is appropriate for most of the practical scenarios involving uncertainty, vagueness, and insufficient information. Entropy, similarity, distance, inclusion, and cross entropy measures are a few methods used for measuring uncertainty and classifying fuzzy sets and its generalizations. Entropy of a fuzzy set describes fuzziness degree of the set and similarity measure measures similarity between two fuzzy or members of its extended family. This paper presents generalized entropy and similarity measures for interval-valued intuitionistic fuzzy sets. Further, the proposed similarity measure is compared with some existing measure of similarity with the help of an illustrative example, and a method is used to define optimal point using the existing information. Finally, entropy and similarity measures are used to identify best alternatives to solve multi-attribute decision making.
Soft and fuzzy sets are generic tools to deal with uncertainty. Both contemporary sets are not suitable to deal with all type of uncertain parameters. In this paper the hybridization of soft with extended fuzzy set information measures are derived. Interval-valued intuitionistic fuzzy soft set theory is a powerful tool for dealing with uncertainty of knowledge in information systems. In this paper, firstly some distance and similarity measures for interval-valuefvd intuitionistic fuzzy soft sets were proposed. Further, some new entropy measures are also introduced by using the similarity measures. The validity of these measures is also proved. Applications of the distance measures is also used in the field of multi attribute decision making and medical diagnosis. The proposed measures are also compared with an existing measure to prove its significance.
This paper presents new axiomatic definitions of entropy measure using concept of probability and distance for interval-valued intuitionistic fuzzy sets (IvIFSs) by considering degree of hesitancy which is consistent with the definition of entropy given by De Luca and Termini. Thereafter, we propose some entropy measures and also derived relation between distance, entropy and similarity measures for IvIFSs. Further, we checked the performance of proposed entropy and similarity measures on the basis of intuition and compared with the existing entropy and similarity measures using numerical examples. Lastly, proposed similarity measures are used to solve problems in the field of pattern recognition and medical diagnoses. Povzetek: V prispevku so predstavljene nove aksiomatske definicije entropijske mere za intervalno intuicionistične mehke množice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.