Hesitant fuzzy linguistic entropy and cross-entropy measures and alternative queuing method for multiple criteria decision making

X Gou, Z Xu, H Liao - Information Sciences, 2017 - Elsevier
Hesitant fuzzy linguistic term set (HFLTS) is a useful tool for describing people's subjective
cognitions in the process of decision making. Multiple criteria decision making (MCDM) …

Dual hesitant fuzzy VIKOR method for multi-criteria group decision making based on fuzzy measure and new comparison method

Z Ren, Z Xu, H Wang - Information Sciences, 2017 - Elsevier
In the process of group decision making, dual hesitant fuzzy sets (DHFSs) are a very flexible
tool for decision makers (DMs) to express their preferences for alternatives. Based on an …

Fuzzy time series forecasting based on proportions of intervals and particle swarm optimization techniques

SM Chen, XY Zou, GC Gunawan - Information Sciences, 2019 - Elsevier
In this paper, we propose a new fuzzy time series (FTS) forecasting method based on the
proportions of intervals and particle swarm optimization (PSO) techniques. First, it uses PSO …

Hotel recommendation approach based on the online consumer reviews using interval neutrosophic linguistic numbers

JQ Wang, X Zhang, HY Zhang - Journal of Intelligent & Fuzzy …, 2018 - content.iospress.com
With the popularity of online hotels booking, increasing attention has been paid to hotel
recommendation methods. To provide personalized hotel recommendation for different …

Structural rule-based modeling with granular computing

T Ouyang - Applied Soft Computing, 2022 - Elsevier
In order to analyze the dynamic behaviors of complex systems in the era of big data, a new
rule-based modeling approach is proposed in this paper. This approach considers structural …

A development of granular input space in system modeling

X Zhu, W Pedrycz, Z Li - IEEE transactions on cybernetics, 2019 - ieeexplore.ieee.org
In this paper, we elaborate on a new design approach to the development and analysis of
granular input spaces and ensuing granular modeling. Given a numeric model (no matter …

WHO: A new evolutionary algorithm bio-inspired by wildebeests with a case study on bank customer segmentation

MM Motevali, AM Shanghooshabad… - … Journal of Pattern …, 2019 - World Scientific
Numerous evolutionary algorithms have been proposed which are inspired by the amazing
lives of creatures, such as animals, insects, and birds. Each inspired algorithm has its own …

A granular approach to interval output estimation for rule-based fuzzy models

X Zhu, W Pedrycz, Z Li - IEEE transactions on cybernetics, 2020 - ieeexplore.ieee.org
Rule-based fuzzy models play a dominant role in fuzzy modeling and come with extensive
applications in the system modeling area. Due to the presence of system modeling error, it is …

Granular computing-based approach of rule learning for binary classification

H Liu, M Cocea - Granular Computing, 2019 - Springer
Rule learning is one of the most popular types of machine-learning approaches, which
typically follow two main strategies:'divide and conquer'and 'separate and conquer'. The …

A granular computing framework for approximate reasoning in situation awareness

G D'Aniello, A Gaeta, V Loia, F Orciuoli - Granular Computing, 2017 - Springer
We present our results on the adoption of a set-theoretic framework for granular computing
to situation awareness. The proposed framework guarantees a high degree of flexibility in …