Hesitant fuzzy linguistic entropy and cross-entropy measures and alternative queuing method for multiple criteria decision making
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) …
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 …
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 …
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
With the popularity of online hotels booking, increasing attention has been paid to hotel
recommendation methods. To provide personalized hotel recommendation for different …
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 …
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 …
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 …
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 …
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
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 …
typically follow two main strategies:'divide and conquer'and 'separate and conquer'. The …
A granular computing framework for approximate reasoning in situation awareness
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 …
to situation awareness. The proposed framework guarantees a high degree of flexibility in …