Tauberian theorems for weighted means of double sequences in intuitionistic fuzzy normed spaces

Mishra, Lakshmi Narayan; Raiz, Mohd; Rathour, Laxmi; Mishra, Vishnu Narayan

doi:10.2298/yjor210915005m

Cited by 12 publications

(4 citation statements)

References 12 publications

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“…Among these initiatives are the development of smart and AI-based devices to lessen stress (Jung & Yoon, 2017) in smart cities (Falco et al, 2018), AI practitioners' predictions of job displacement (Gruetzemacher et al, 2020) estimation of the rate of depression among workers using the Apriori algorithm, and forecasts of the susceptibility of occupations to computerization in the near future (Jena & Kamila, 2014). Mishra et al (2022) revealed that the results generated from the Tauberian conditions by the convergence of a dual sequenced intuitionistic fuzzy normed spaces (IFNS) are significant for obtaining the weighted mean of computed nodes in some special cases. The development of a neuro-fuzzybased model that can automatically predict task performance and fitness rate with accuracy comparison checks on three (3) machine learning models is our key addition to this body of knowledge.…”

Section: Literature Reviewmentioning

confidence: 99%

A Task Performance and Fitness Predictive Model Based on Neuro-Fuzzy Modeling

Johnson

Onashoga

Ojo

et al. 2023

AIA

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Recruiters' decisions in the selection of candidates for specific job roles are not only dependent on physical attributes and academic qualifications but also on the fitness of candidates for the specified tasks. In this paper, we propose and develop a simple neuro-fuzzy-based task performance and fitness model for the selection of candidates. This is accomplished by obtaining from Kaggle (an online database) samples of task performance-related data of employees in various firms. Data were preprocessed and divided into 60%, 20%, and 20% for training, validating, and testing the developed neuro-fuzzy-based task performance model respectively. The most significant factors influencing the performance and fitness rating of workers were selected from the database using the Principal Components Analysis (PCA) ranking technique. The effectiveness of the proposed model was assessed, and discovered to generate an accuracy of 0.997%, 0.08% Root Mean Square Error (RMSE), and 0.042% Mean Absolute Error (MAE).

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Section: Literature Reviewmentioning

confidence: 99%

A Task Performance and Fitness Predictive Model Based on Neuro-Fuzzy Modeling

Johnson

Onashoga

Ojo

et al. 2023

AIA

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“…fuzzy sets [ 17 , 23 ], approximation theory [ 24 – 26 ] etc. Intuitionistic fuzzy sets (IFS) was introduced by [ 27 ] to assign non membership grades and it was studied by [ 28 , 29 ]. Neutrosophic fuzzy set (NFS) was introduced in 1998 by [ 30 ] to assign incomplete, indeterminate, and inconsistent information.…”

Section: Introductionmentioning

confidence: 99%

A new multi-criteria decision making method for the selection of construction contractors using interval valued fuzzy set

Nithya,

Thota,

Rathour

et al. 2024

BMC Res Notes

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Objective This article introduces a novel approach called Digital Weighted Multi Criteria Decision Making (DWMCDM) that employs interval valued fuzzy sets to select the best contractor for building projects. The contractor is chosen based on the pre-qualification and bid evaluation phases. In the first phase, the distance between the actual and required skills of the significant criteria is determined, and it is then converted into digital weighted distances to identify the maximum number of criteria related to the specific project of each contractor. The second step ranks the best contractor based on the bid price and digital weighted distances. Results The suggested technique integrates the pre-qualification and bid review phases to address project award delays and other restrictions. Finally, a real-world application is addressed to demonstrate the applicability of the proposed approach to any type of interval valued fuzzy inputs.

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“…In 2022, Chandra, Srivastava, and Sinha [6]; Srivastava, Sinha and Chandra [17] introduced 2-norm and 2-inner product on fuzzy linear spaces over fuzzy field. For more recent work of the area under study, we refer to [7,12,13,14,15,16]. In the present paper we introduce the idea of anti-norm and anti-inner product function on anti-fuzzy linear space over anti-fuzzy field and also given fuzzy continuous and fuzzy bounded linear operators on anti-fuzzy linear space over anti-fuzzy field.…”

Section: Introductionmentioning

confidence: 99%