High-order Intuitionistic Fuzzy Cognitive Map Based on Evidential Reasoning Theory

2019 ◽  
Vol 27 (1) ◽  
pp. 16-30 ◽  
Author(s):  
Yingjun Zhang ◽  
Jiahu Qin ◽  
Peng Shi ◽  
Yu Kang
Keyword(s):  
Cognitive Map ◽  
High Order ◽  
Evidential Reasoning ◽  
Fuzzy Cognitive Map ◽  
Intuitionistic Fuzzy

The prediction of online time series with concept drift based on dynamic intuitionistic fuzzy cognitive map

2021 ◽  
Vol 25 (4) ◽  
pp. 949-972
Author(s):  
Nannan Zhang ◽  
Xixi Yao ◽  
Chao Luo
Keyword(s):  
Fuzzy Set ◽  
Sequence Data ◽  
Concept Drift ◽  
Intuitionistic Fuzzy Set ◽  
Cognitive Map ◽  
Fuzzy Cognitive Maps ◽  
Fuzzy Cognitive Map ◽  
Online Data ◽  
Intuitionistic Fuzzy ◽  
Public Data

Fuzzy cognitive maps (FCMs) have widely been applied for knowledge representation and reasoning. However, in real life, reasoning is always accompanied with hesitation, which is deriving from the uncertainty and fuzziness. Especially, when processing the online data, since the internal and external interference, the distribution and characteristics of sequence data would be considerably changed along with the passage of time, which further increase the difficulty of modeling. In this article, based on intuitionistic fuzzy set theory, a new dynamic intuitionistic fuzzy cognitive map (DIFCM) scheme is proposed for online data prediction. Combined with a novel detection algorithm of concept drift, the structure of DIFCM can be adaptively updated with the online learning scheme, which can effectively improve the representation of online information by capturing the real-time changes of sequence data. Moreover, in order to tackle with the possible hesitancy in the process of modeling, intuitionistic fuzzy set is applied in the construction of dynamic FCM, where hesitation degree as a quantitative index explicitly expresses the hesitancy. Finally, a series of experiments using public data sets verify the effectiveness of the proposed method.

scholarly journals Sustainable supply chain management framework in a higher education laboratory using intuitionistic fuzzy cognitive map

2020 ◽  
Vol 13 (2) ◽  
pp. 417
Author(s):  
Muhammad Ridwan Andi Purnomo ◽  
Adhe Rizky Anugerah ◽  
Bella Taradipa Dewipramesti
Keyword(s):  
Higher Education ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Causal Model ◽  
Service Industry ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Intuitionistic Fuzzy

Purpose: This research aims to develop framework in the sustainable supply chain management (SCM) and to provide causal model of service industry specifically in higher education laboratory.Design/methodology/approach: The concepts of sustainable SCM in higher education laboratory were obtained by in-depth interviews and organized using Delphi method. While to identify the relationship between concepts, intuitionistic fuzzy cognitive map was utilized.Findings: As many as 15 concepts were identified to assess sustainability in the higher education laboratory SCM. These 15 concepts were classified into four categories according to its importance level, and there are two most important concepts: legal requirement and social responsibility. It is recommended for higher education laboratories to constantly obey national and regional government regulations and to satisfy current and prospective employers by providing work-ready graduates. This suggestion is expected to make higher education achieving its sustainability goals.  Originality/value: This research is the first to develop a framework for sustainable SCM and to provide a causal model of the service industry especially in the education sector using intuitionistic fuzzy cognitive map.

scholarly journals An Analysis on Barriers to Biomass and Bioenergy Development in Rural China Using Intuitionistic Fuzzy Cognitive Map

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1598 ◽  
Author(s):  
Linmao Ma ◽  
Jing Yu ◽  
Long Zhang
Keyword(s):  
Rural China ◽  
Influence Factors ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Technical Problems ◽  
Intuitionistic Fuzzy ◽  
Influence Mechanism ◽  
Local Residents ◽  
The Government ◽  
Intuitionistic Fuzzy Logic

Biomass is viewed as one of the critical renewable energies and it widely exists in nature. Developing bioenergy has been promoted as a viable mean of dealing with environment issues that are related to the utilization of fossil fuel. However, due to many obstacles, the biomass and bioenergy technology has not won widespread support in developing countries, like China, with vast land area, particularly in rural area. Furthermore, most existing researches just focused on the description of the influence factors, along with the solution to the technical problems, while many social factors are overlooked. In fact, the process of developing biomass is indeed complicated due to the need for consensus and active participation of the various stakeholders, such as the government, the industry, and the local residents. Therefore, while integrating the intuitionistic fuzzy logic and fuzzy cognitive map, this study constructs an intuitionistic fuzzy cognitive map (IFCM) that is in line with experts’ suggestions and the current literature to investigate how to promote the development of biomass through enhancing public acceptance. We conduct several simulations from the perspective of different stakeholders, according to the IFCM. The analysis results reveal the influence mechanism in the system and illustrate the effect of various factors that are stressed by every stakeholder. The research design also provides a reference for future studies.

Time series prediction based on intuitionistic fuzzy cognitive map

2019 ◽  
Vol 24 (9) ◽  
pp. 6835-6850 ◽  
Author(s):  
Chao Luo ◽  
Nannan Zhang ◽  
Xingyuan Wang
Keyword(s):  
Time Series ◽  
Time Series Prediction ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Intuitionistic Fuzzy

scholarly journals An Extended Intuitionistic Fuzzy Cognitive Map via Dempster-Shafer Theory

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 23186-23196
Author(s):  
Zhuosheng Jia ◽  
Yingjun Zhang ◽  
Xuemin Dong
Keyword(s):  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Intuitionistic Fuzzy ◽  
Dempster Shafer Theory ◽  
Shafer Theory
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