On the power sequence of a fuzzy matrix convergent power sequence

1997 ◽  
Vol 4 (1) ◽  
pp. 147-165 ◽  
Author(s):  
Zhou -Tian Fan ◽  
De -Fu Liu
Keyword(s):  
Fuzzy Matrix ◽  
Power Sequence

A note on the power sequence of a fuzzy matrix

1999 ◽  
Vol 102 (2) ◽  
pp. 281-286 ◽  
Author(s):  
Zhou-Tian Fan
Keyword(s):  
Fuzzy Matrix ◽  
Power Sequence

On the power sequence of a fuzzy matrix with convex combination of max-product and max-min operations

2016 ◽  
Vol 289 ◽  
pp. 157-163 ◽  
Author(s):  
Chia-Cheng Liu ◽  
Yan-Kuen Wu ◽  
Yung-Yih Lur ◽  
Chia-Lun Tsai
Keyword(s):  
Convex Combination ◽  
Fuzzy Matrix ◽  
Power Sequence

On the oscillating power sequence of a fuzzy matrix

1998 ◽  
Vol 93 (1) ◽  
pp. 75-85 ◽  
Author(s):  
Zhou-Tian Fan ◽  
De-Fu Liu
Keyword(s):  
Fuzzy Matrix ◽  
Power Sequence

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.

A Two-Stage Combination Model for Wind Power Forecasting

2015 ◽  
Vol 737 ◽  
pp. 9-13
Author(s):  
Jun Zhang ◽  
Yuan Hao Wang ◽  
Ying Yi Li ◽  
Feng Guo
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Wind Farm ◽  
General Trend ◽  
Two Stage ◽  
Combination Model ◽  
Second Stage ◽  
Combination Forecasting ◽  
The Mean ◽  
Power Sequence

With the wind farm data from the southeast coast this paper builds a two-stage combination forecasting model of output power based on data preprocessing which include filling up missing data and pre-decomposition. The first stage is a composite prediction of decomposed power sequence in which a time series and optimized BP neural network predict the general trend and the correlation of various factors respectively. The second stage is BP neural network with its input is the results of first stage. The effectiveness and accuracy of the two-stage combination model are verified by comparing the mean square error of the combination model and other models.

Sign in / Sign up

Export Citation Format

Share Document