Review of artificial intelligence and machine learning technologies: classification, restrictions, opportunities and challenges

RI Mukhamediev, Y Popova, Y Kuchin, E Zaitseva… - Mathematics, 2022 - mdpi.com
Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of
applied issues. The core of AI is machine learning (ML)—a complex of algorithms and …

Multiple-criteria decision-making sorting methods: A survey

PA Alvarez, A Ishizaka, L Martínez - Expert Systems with Applications, 2021 - Elsevier
Abstract Multi-Criteria Decision Making (MCDM) is a complex process. It aims to support
decision makers in making their decisions more effective and consistent. MCDM provides a …

Multiple-criteria decision-making (MCDM) techniques for business processes information management

E Kazimieras Zavadskas, J Antucheviciene… - Information, 2018 - mdpi.com
Information management is a common paradigm in modern decision-making. A wide range
of decision-making techniques have been proposed in the literature to model complex …

Forecasting the importance of product attributes using online customer reviews and Google Trends

H Yakubu, CK Kwong - Technological Forecasting and Social Change, 2021 - Elsevier
During the early stage of product design, product manufacturers seek to identify the most
relevant product features that will meet the demands and needs of consumers …

Rough sets in COVID-19 to predict symptomatic cases

HR Bhapkar, PN Mahalle, GR Shinde… - COVID-19: prediction …, 2021 - Springer
Rough set theory is a new mathematical or set-theoretical practice to study inadequate
knowledge. There are many use cases in the real world where there is a lack of crisp …

Bibliometric analysis of rough sets research

D Yu, Z Xu, W Pedrycz - Applied Soft Computing, 2020 - Elsevier
Rough set (RS) is a mathematical framework used to deal with incomplete and uncertain
information. It has been widely used in decision analysis, data mining, artificial intelligence …

A fog based load forecasting strategy for smart grids using big electrical data

AH Rabie, SH Ali, HA Ali, AI Saleh - Cluster Computing, 2019 - Springer
Internet of things (IoT) enables the smart electrical grids (SEGs) to support a lot of tasks
throughout the generation, transmission, distribution and consumption of energy. Large …

Building a model to exploit association rules and analyze purchasing behavior based on rough set theory

DT Tran, JH Huh - The Journal of Supercomputing, 2022 - Springer
In recent years, the information technology industry around the world has grown strong. At
the same time, we also face a new challenge with the explosion in the amount of …

Neutrosophic fusion of rough set theory: An overview

C Zhang, D Li, X Kang, D Song, AK Sangaiah… - Computers in …, 2020 - Elsevier
Neutrosophic sets (NSs) and logic are one of the influential mathematical tools to manage
various uncertainties. Among diverse models for analyzing neutrosophic information, rough …

A hybrid approach for adaptive fuzzy network partitioning and rule generation using rough set theory: Improving data-driven decision making through accurate and …

J Sihotang, A Alesha, J Batubara, SE Gorat… - International Journal of …, 2022 - ieia.ristek.or.id
Data-driven decision making is vital in credit risk assessment and other areas. Complex
datasets are hard to rule. We use adaptive fuzzy network partitioning, rough set theory, and …