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Mahyar Kamali Saraji

Researcher at Vilnius University

Publications -  20
Citations -  387

Mahyar Kamali Saraji is an academic researcher from Vilnius University. The author has contributed to research in topics: Computer science & Fuzzy logic. The author has an hindex of 5, co-authored 12 publications receiving 112 citations. Previous affiliations of Mahyar Kamali Saraji include Yazd University.

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A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak

TL;DR: This study extended a new fuzzy approach under Hesitant Fuzzy Set approach using Stepwise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) method to evaluate and rank the critical challenges of DTs intervention to control the COVID-19 outbreak.
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Fermatean Fuzzy CRITIC-COPRAS Method for Evaluating the Challenges to Industry 4.0 Adoption for a Sustainable Digital Transformation

TL;DR: In this article, the authors identify the challenges to the adoption of Industry 4.0 in fintech companies and develop a novel Fermatean fuzzy CRITIC-COPRAS method to rank the identified challenges and evaluate the performance of companies concerning the weighted challenges based on three decision experts' support.
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An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions.

TL;DR: An integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed and the identified challenges were systemic, pedagogical, and psychological challenges.
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An extended new approach for forecasting short-term wind power using modified fuzzy wavelet neural network: A case study in wind power plant

TL;DR: This article aims to predict a wind power plant’s power output using weather and power plant parameters and employ an extended fuzzy wavelet neural network (FWNN) and shows that compared to other methods reported, the proposed method was a more efficient tool and had higher precision for short-term wind power forecasting.
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A hybrid data envelopment analysis and game theory model for performance measurement in healthcare.

TL;DR: This study proposes a hybrid data envelopment analysis (DEA) and game theory model for measuring the performance and productivity in the healthcare centers and reveals useful information and insights on the efficiency levels of the regional healthcare centers.