scholarly journals Research on Evaluation of Sustainable Development of New Urbanization from the Perspective of Urban Agglomeration under the Pythagorean Fuzzy Sets

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lingyan Meng ◽  
Xiaoyan Wei

In this study, considering the traditional geometric operation laws and Pythagorean fuzzy information, we propose a variety of new distance measures of Pythagorean fuzzy sets such as generalized Pythagorean fuzzy geometric distance (GPFGD) measures and generalized Pythagorean fuzzy weighted geometric distance (GPFWGD) measures. Besides, some special issues including Hamming distance, Euclidean distance, and Hausdorff distance of these raised geometric distance measures are investigated. To testify the valid of these new presented distance measures, we build a decision-making model illustrated by a mathematical calculation example to evaluate the sustainable development of new urbanization from the perspective of urban agglomeration using Pythagorean fuzzy information.

Author(s):  
Bo Peng ◽  
Chunming Ye ◽  
Shouzhen Zeng

The ordered weighted distance (OWD) measure developed by Xu and Chen having been proved suitable to deal with the situation where the input arguments are represented in exact numerical values. In this paper, we develop some new geometric distance measures with intuitionistic fuzzy information, which are the generalization of some widely used distance measures, including the intuitionistic fuzzy weighted geometric distance (IFWGD) measure, the intuitionistic fuzzy ordered weighted geometric distance (IFOWGD) measure, the intuitionistic fuzzy ordered weighted geometric Hamming distance (IFOWGHD) measure, the intuitionistic fuzzy ordered weighted geometric Euclidean distance (IFOWGED) measure, the intuitionistic fuzzy hybrid weighted geometric distance (IFHWGD) measure. These developed weighted geometric distance measures are very suitable to deal with the situation where the input arguments are represented in intuitionistic fuzzy values. And then, we present a consensus reaching process based on the developed distance measures with intuitionistic fuzzy preference information for group decision making. Finally, we apply the developed approach with a numerical example to group decision making under intuitionistic fuzzy environment.


2020 ◽  
Vol 12 (18) ◽  
pp. 7460
Author(s):  
Shidong Liu ◽  
Peiyi Ding ◽  
Binrui Xue ◽  
Hongbing Zhu ◽  
Jun Gao

The sustainability of urban cities has been the focus of significant academic research in recent years and is emphasized in Goal 11 of the Sustainable Development Goals (SDGs). In this study, we adopted the Drive-Pressure-State-Impact-Response model (DPSIR) to promote a conceptual study of sustainable development index (SDI) to compare the different urban sustainable development status and try to find the factors that affect the urban sustainable development. The framework of indicators we used is mainly based on Goal 11 of the SDGs’ targets and indicators. We chose six cities in the Shaanxi Province of China and studied them from 2008 to 2018. The results show that: (1) the sustainable development of urban cities is greatly influenced by China’s national economic development plans and urban development strategies; (2) the economic growth and management level of authorities can significantly promote urban sustainability; (3) the urban sustainability of the six cities in Shaanxi Province showed a significant imbalance and this imbalance affected the overall development of the region; (4) compared with Guanzhong urban agglomeration, Shannan urban agglomeration is subject to the policy needs of environmental protection in the Qinling mountain area and its economic development is restricted; therefore, its urban sustainability is relatively low. Theoretical contributions are presented to assist in addressing these challenges and to support policies and initiatives that move these cities in China towards achieving SDG 11.


2020 ◽  
Vol 39 (3) ◽  
pp. 3351-3374
Author(s):  
Peide Liu ◽  
Zeeshan Ali ◽  
Tahir Mahmood

The information measures (IMs) of complex fuzzy information are very useful tools in the areas of machine learning and decision making. In some multi-attribute group decision making (MAGDM) problems, the decision makers can make a decision mostly according to IMs such as similarity measures (SMs), distance measures (DIMs), entropy measures (EMs) and cross-entropy measures (C-EMs) in order to choose the best one. However, the relation between C-EMs and DIMs in the environment of complex fuzzy sets (CFSs) has not been developed and verified. In this manuscript, the notions of DIMs and C-EMs in the environment of CFSs are investigated and the relation between DIMs and EMs in the environment of CFSs is also discussed. The complex fuzzy discrimination measures (CFDMs), the complex fuzzy cross-entropy measures (CFC-EMs), and the symmetry complex fuzzy cross-entropy measures (SCFC-EMs) are proposed. We also examined that the C-EMs satisfied all the conditions of DIMs, and finally proved that C-EMs including CFC-EMs were also a DIMs. In last, we used some practical examples to illustrate the validity and superiority of the proposed method by comparing with other existing methods.


Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 383 ◽  
Author(s):  
Arshad Khan ◽  
Shahzaib Ashraf ◽  
Saleem Abdullah ◽  
Muhammad Qiyas ◽  
Jianchao Luo ◽  
...  

Keeping in mind the importance and well growing Pythagorean fuzzy sets, in this paper, some novel operators for Pythagorean fuzzy sets and their properties are demonstrated. In this paper, we develop a comprehensive model to tackle decision-making problems where strong points of view are in the favour and against the some projects, entities or plans. Therefore, a new approach, based on Pythagorean fuzzy set models by means of Pythagorean fuzzy Dombi aggregation operators is proposed. An approach to deal with decision-making problems using Pythagorean Dombi averaging and Dombi geometric aggregation operators is established. This model has a stronger capability than existing averaging, geometric, Einstein, logarithmic averaging and logarithmic geometric aggregation operators for Pythagorean fuzzy information. Finally, the proposed method is demonstrated through an example of how the proposed method helps us and is effective in decision-making problems.


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