Weighted Moore-Penrose Inverse of a Fuzzy Matrix

2009 ◽  
pp. 573-582
Author(s):  
Shi-zhen Cheng ◽  
Hong-xing Li
Keyword(s):  
Fuzzy Matrix

Comprehensive evaluation of kraft pulp properties from fast-growing woods

TAPPI Journal ◽  
2010 ◽  
Vol 9 (6) ◽  
pp. 34-39
Author(s):  
AIYU QU ◽  
YANHUI AO ◽  
JUN YAN ◽  
GUIGAN FANG
Keyword(s):  
Kraft Pulp ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Wood Cellulose ◽  
Fuzzy Matrix ◽  
Fast Growing ◽  
Pulp Properties ◽  
Evaluation Index Systems

To develop new wood cellulose resources and fast-growing pulpwood plantation fiber sources, it is very important to evaluate their pulping properties. A comprehensive multi-index pulping-suitability evaluation model is investigated in this paper by considering four fast-growing wood species. First, a new evaluation-index system for kraft pulp was developed based on traditional evaluation-index systems. Then, the membership degree of every index was analyzed to obtain a fuzzy matrix. The proportional contribution of each parameter to the main pulping properties could then be determined. Finally, a comprehensive evaluation model of kraft pulp properties was developed. The model is reliable compared with traditional assessment methods. The results confirmed the feasibility and rationality of developing new wood cellulose resources and fast-growing pulpwood plantations using fuzzy comprehensive evaluations.

scholarly journals Objective Evaluation of Drivability in Passenger Cars with Dual-Clutch Transmission: A Case Study of Static Gearshift Condition

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Wei Zhou ◽  
Xuexun Guo ◽  
Xiaofei Pei ◽  
Chengcai Zhang ◽  
Jun Yan ◽  
...  
Keyword(s):  
Fuzzy Ahp ◽  
Subjective Evaluation ◽  
Objective Evaluation ◽  
Dual Clutch Transmission ◽  
Evaluation Tool ◽  
Passenger Cars ◽  
Denoising Method ◽  
Fuzzy Matrix ◽  
Predictability Score

This paper is aimed at the problem that the subjective drivability evaluation by experienced test drivers is limited in time efficiency and is of high cost and poor repeatability. In this article, an intelligent drivability objective evaluation tool (I-DOET) for passenger cars with dual-clutch transmission (DCT) is developed and verified by real vehicle testing. First, the signal denoising method and its key parameters, which are suitable for drivability evaluation, are selected based on analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). Besides, combined with the uncertainty characteristics of subjective judgment, a mathematical model of the objective drivability evaluation FARODE (fuzzy AHP-RS based on objective drivability evaluation) is proposed by using the fuzzy comprehensive assessment (FCA) method. The AHP and rough set (RS) method are used to calculate the subjective and objective weights of the drivability evaluation, respectively, and the proportion of subjective and objective weights is determined by the principle of minimum relative information entropy. The fuzzy matrix is built by membership function of the evaluation indexes. Finally, the static gearshift condition focused on by the subjective evaluation experts is taken as a case study. The predictability score is obtained by combining the drivability quantization lever vector, comprehensive weight, and fuzzy matrix. The experimental results indicate that the proposed method is applicable for objective drivability evaluation in passenger cars with DCT.

scholarly journals Evaluation of Safety Degree at Railway Crossings in Order to Achieve Sustainable Traffic Management: A Novel Integrated Fuzzy MCDM Model

2021 ◽  
Vol 13 (2) ◽  
pp. 832
Author(s):  
Aleksandar Blagojević ◽  
Sandra Kasalica ◽  
Željko Stević ◽  
Goran Tričković ◽  
Vesna Pavelkić
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Assessment Model ◽  
Level Crossings ◽  
Fuzzy Matrix ◽  
Sustainable Performance ◽  
Current State ◽  
Criterion Weight ◽  
Railway System ◽  
Criteria Importance

Sustainable traffic system management under conditions of uncertainty and inappropriate road infrastructure is a responsible and complex task. In Bosnia and Herzegovina (BiH), there is a large number of level crossings which represent potentially risky places in traffic. The current state of level crossings in BiH is a problem of the greatest interest for the railway and a generator of accidents. Accordingly, it is necessary to identify the places that are currently a priority for the adoption of measures and traffic control in order to achieve sustainability of the whole system. In this paper, the Šamac–Doboj railway section and passive level crossings have been considered. Fifteen different criteria were formed and divided into three main groups: safety criteria, road exploitation characteristics, and railway exploitation characteristics. A novel integrated fuzzy FUCOM (full consistency method)—fuzzy PIPRECIA (pivot pairwise relative criteria importance assessment) model was formed to determine the significance of the criteria. When calculating the weight values of the main criteria, the fuzzy Heronian mean operator was used for their averaging. The evaluation of level crossings was performed using fuzzy MARCOS (measurement of alternatives and ranking according to compromise solution). An original integrated fuzzy FUCOM–Fuzzy PIPRECIA–Fuzzy MARCOS model was created as the main contribution of the paper. The results showed that level crossings 42 + 690 (LC4) and LC8 (82 + 291) are the safest considering all 15 criteria. The verification of the results was performed through four phases of sensitivity analysis: resizing of an initial fuzzy matrix, comparative analysis with other fuzzy approaches, simulations of criterion weight values, and calculation of Spearman’s correlation coefficient (SCC). Finally, measures for the sustainable performance of the railway system were proposed.

Matrix, Fuzzy Relation and Fuzzy Matrix

2018 ◽  
pp. 41-71
Author(s):  
Hao-Ran Lin ◽  
Bing-Yuan Cao ◽  
Yun-zhang Liao
Keyword(s):  
Fuzzy Relation ◽  
Fuzzy Matrix

On the max-generalized mean powers of a fuzzy matrix

2010 ◽  
Vol 161 (5) ◽  
pp. 750-762 ◽  
Author(s):  
Yung-Yih Lur ◽  
Yan-Kuen Wu ◽  
Sy-Ming Guu
Keyword(s):  
Fuzzy Matrix ◽  
Generalized Mean

Interval-Valued Intuitionistic Fuzzy Partition Matrices

2017 ◽  
pp. 64-81
Author(s):  
Amal Kumar Adak
Keyword(s):  
Kronecker Product ◽  
Kronecker Sum ◽  
Fuzzy Partition ◽  
Fuzzy Matrix ◽  
Direct Sum ◽  
Intuitionistic Fuzzy ◽  
Different Types ◽  
Interval Valued

If in an interval-valued intuitionistic fuzzy matrix each element is again a smaller interval-valued intuitionistic fuzzy matrix then the interval-valued intuitionistic fuzzy matrix is called interval-valued intuitionistic fuzzy partion matrix (IVIFPMs). In this paper, the concept of interval-valued intuitionistic fuzzy partion matrices (IVIFPMs) are introduced and defined different types of interval-valued intuitionistic fuzzy partion matrices (IVIFPMs). The operations like direct sum, Kronecker sum, Kronecker product of interval-valued intuitionistic fuzzy matrices are presented and shown that their resultant matrices are also interval-valued intuitionistic fuzzy partion matrices (IVIFPMs).

Some Remarks on Sections of a Fuzzy Matrix

1992 ◽  
Vol 4 (1) ◽  
pp. 145-155 ◽  
Author(s):  
F. SIDKY ◽  
E. EMAM
Keyword(s):  
Fuzzy Matrix

Business Process Model Abstraction Based on Fuzzy Clustering Analysis

2019 ◽  
Vol 28 (03) ◽  
pp. 1950007
Author(s):  
Nan Wang ◽  
Shanwu Sun ◽  
Ying Liu ◽  
Senyue Zhang
Keyword(s):  
Business Process ◽  
Fuzzy Clustering ◽  
Process Model ◽  
Control Flow ◽  
Business Process Model ◽  
Model Abstraction ◽  
Fuzzy Matrix ◽  
Fuzzy Clustering Analysis ◽  
Complex Process ◽  
Hard Clustering

The most prominent Business Process Model Abstraction (BPMA) use case is a construction of a process “quick view” for rapidly comprehending a complex process. Researchers propose various process abstraction methods to aggregate the activities most of which are based on [Formula: see text]-means hard clustering. This paper focuses on the limitation of hard clustering, i.e. it cannot identify the special activities (called “edge activities” in this paper) and each activity must be classified to some subprocess. A new method is proposed to classify activities based on fuzzy clustering which generates a fuzzy matrix by computing the possibilities of activities belonging to subprocesses. According to this matrix, the “edge activities” can be located. Considering the structure correlation feature of the activities in subprocesses, an approach is provided to generate the initial clusters based on the close connection characteristics of subprocesses. A hard partition algorithm is proposed to classify the edge activities and it evaluates the generated abstract models according to a new index designed by control flow order preserving requirement and the evaluation results guide the edge activities to be classified to the optimal hard partition. The proposed method is applied to a process model repository in use. The results verify the validity of the measurement based on the virtual document to generating fuzzy matrix. Also it mines the threshold parameter in the real world process model collection enriched with human designed subprocesses to compute the fuzzy matrix. Furthermore, a comparison is made between the proposed method and the [Formula: see text]-means clustering and the results show our approach more closely approximating the decisions of the involved modelers to cluster activities and it contributes to the development of modeling support for effective process model abstraction.

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