J
Jalil Heidary Dahooie
Researcher at University of Tehran
Publications - 42
Citations - 603
Jalil Heidary Dahooie is an academic researcher from University of Tehran. The author has contributed to research in topics: Computer science & Fuzzy logic. The author has an hindex of 9, co-authored 33 publications receiving 303 citations. Previous affiliations of Jalil Heidary Dahooie include Amirkabir University of Technology.
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A Novel Approach for Evaluation of Projects Using an Interval–Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects
Jalil Heidary Dahooie,Edmundas Kazimieras Zavadskas,Mahdi Abolhasani,Amir Salar Vanaki,Zenonas Turskis +4 more
TL;DR: Given the limited research on performance evaluation in oil & gas well-drilling projects, the research identifies a set of performance criteria and proposes an evaluation model using fuzzy Delphi method that was used to solve real case study of oil and gas well drilling projects evaluation.
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Competency-based IT personnel selection using a hybrid SWARA and ARAS-G methodology
TL;DR: In this paper, the authors present a competency framework with five criteria for choosing the best information technology (IT) expert from five alternatives, using stepwise weight assessment ratio analysis (SWARA) and grey additive ratio assessment (ARAS-G) methods.
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Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick
TL;DR: A novel forecasting model for stock markets on the basis of the wrapper ANFIS-ICA (Adaptive Neural Fuzzy Inference System)-ICA (Imperialist Competitive Algorithm) and technical analysis of Japanese Candlestick is presented.
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An intuitionistic fuzzy data-driven product ranking model using sentiment analysis and multi-criteria decision-making
TL;DR: An integrated framework that combines sentiment analysis (SA) and multi-criteria decision-making (MCDM) techniques based on intuitionistic fuzzy sets (IFS) is proposed and used in a real-world case to rank five mobile phone products using the OCRs on the Amazon site to illustrate the availability and utility of the proposed methodology.
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An activity‐based framework for quantification of knowledge work
TL;DR: This study attempts to identify the different types of activities that comprise a worker's job, and provide a framework for quantitative definition and segmentation of knowledge works (KWs).