The Comprehensive Evaluation Analysis of the Fruit Quality in Actinidia eriantha Pollinated with Different Pollen Donors Based on the Membership Function Method

2022 ◽  
Author(s):  
Guanglian Liao ◽  
Zhiqiang Jiang ◽  
Yanqun He ◽  
Min Zhong ◽  
Chunhui Huang ◽  
...  
Keyword(s):  
Membership Function ◽  
Fruit Quality ◽  
Function Method ◽  
Comprehensive Evaluation ◽  
The Membership Function

scholarly journals A Cultural and Functional Approach to the Assessment of Logical Thinking Ability in English Writing

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Cao Juan
Keyword(s):  
Influencing Factors ◽  
Membership Function ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Mathematics ◽  
Logical Thinking ◽  
English Writing ◽  
Thinking Ability ◽  
And Function ◽  
The Membership Function

The analysis of influencing factors of logical thinking ability in English writing is the key effective factor of evaluating logical thinking ability in English writing. In order to accurately evaluate logical thinking ability in English writing, this paper studies the evaluation method of logical thinking ability in English writing from the perspective of culture and function. This paper analyzes the relationship between the influencing factors of logical thinking ability in English writing. The factors of text structure and language expression reflect the culture and function of logical thinking ability in English writing, respectively, which have a direct impact on logical thinking ability in English writing. From these two aspects, 15 evaluation indexes are selected to construct the evaluation system of logical thinking ability in English writing. Considering the significant fuzziness of logical thinking ability in English writing from the perspective of culture and function, the comprehensive evaluation method of fuzzy mathematics is used for the process, the evaluation criteria are determined, the evaluation matrix is constructed, and the membership function is calculated, to complete the comprehensive evaluation of fuzzy mathematics based on the membership function and weight matrix. The experimental results show that this method can accurately evaluate the logical thinking ability of English writing and can be effectively used in the area of research.

Construction Project Bid Evaluation of Group Decision-Making Model Based on Triangular Fuzzy Number

2013 ◽  
Vol 405-408 ◽  
pp. 3451-3454
Author(s):  
Ming Xuan Zhang ◽  
Dong Lei Zhang
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Group Decision Making ◽  
Fuzzy Number ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Triangular Fuzzy Number ◽  
Bid Evaluation ◽  
Decision Making Model

A new comprehensive evaluation based on triangular fuzzy number method is put forward in this paper, according to the principle of fuzzy comprehensive evaluation and using trichotomy to determine membership function. And a calculation example is illustrated by using the method presented. The method is a reference to the bid evaluation in the future.

Possibility-Based Design Optimization Method for Design Problems With Both Statistical and Fuzzy Input Data

2005 ◽  
Vol 128 (4) ◽  
pp. 928-935 ◽  
Author(s):  
Liu Du ◽  
K. K. Choi ◽  
Byeng D. Youn ◽  
David Gorsich
Keyword(s):  
Design Optimization ◽  
Optimum Design ◽  
Membership Function ◽  
Input Data ◽  
Performance Measure ◽  
Sufficient Data ◽  
Design Problems ◽  
Fuzzy Variables ◽  
Fuzzy Input ◽  
The Membership Function

The reliability based design optimization (RBDO) method is prevailing in stochastic structural design optimization by assuming the amount of input data is sufficient enough to create accurate input statistical distribution. If the sufficient input data cannot be generated due to limitations in technical and/or facility resources, the possibility-based design optimization (PBDO) method can be used to obtain reliable designs by utilizing membership functions for epistemic uncertainties. For RBDO, the performance measure approach (PMA) is well established and accepted by many investigators. It is found that the same PMA is a very much desirable approach also for the PBDO problems. In many industry design problems, we have to deal with uncertainties with sufficient data and uncertainties with insufficient data simultaneously. For these design problems, it is not desirable to use RBDO since it could lead to an unreliable optimum design. This paper proposes to use PBDO for design optimization for such problems. In order to treat uncertainties as fuzzy variables, several methods for membership function generation are proposed. As less detailed information is available for the input data, the membership function that provides more conservative optimum design should be selected. For uncertainties with sufficient data, the membership function that yields the least conservative optimum design is proposed by using the possibility-probability consistency theory and the least conservative condition. The proposed approach for design problems with mixed type input uncertainties is applied to some example problems to demonstrate feasibility of the approach. It is shown that the proposed approach provides conservative optimum design.

scholarly journals Controllable Effective Threshold Based Fusion Coverage Algorithm in Mobile Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yong Lu ◽  
Na Sun
Keyword(s):  
Sensor Networks ◽  
Membership Function ◽  
Network Lifetime ◽  
Physical Parameters ◽  
Network Coverage ◽  
Target Node ◽  
Effective Threshold ◽  
Coverage Quality ◽  
Monitoring Area ◽  
The Membership Function

The coverage quality and network lifetime are two key parameters in the research of sensor networks. The coverage quality shows direct influences on the network lifetime. Meanwhile, it is influenced by many other factors such as physical parameters and environmental parameters. To reveal the connection between the coverage quality and the parameters of target node concerned, a fusion coverage algorithm with controllable effective threshold is proposed based on the sensing probability model. We give the model for the membership function of coverage intensity as well as the prediction model for the fusion operator. The range for the effective threshold is presented according to the membership function model. Meanwhile, the maximum of the effective coverage intensity for the target nodes within the monitoring area is derived. The derivation of the maximal fusion coverage intensity is elaborated utilizing a processing function on the distances from the target node to the ones in the sensor node set. Furthermore, we investigate different network properties within the monitoring area such as network coverage quality, the dynamic change of parameters, and the network lifetime, based on the probability theory and the geometric theory. Finally, we present numerical simulations to verify the performances of our algorithm. It is shown under different settings that, compared with the demand coverage quality, the proposed algorithm could improve the network coverage quality by 15.66% on average. The simulation experiment results show that our proposed algorithm has an average improvement by 10.12% and 13.23% in terms of the performances on network coverage quality and network lifetime, respectively. The research results are enlightening to the edge coverage and nonlinear coverage problems within the monitoring area.

FUZZY CLUSTERING OF FEATURE VECTORS WITH SOME ORDINAL VALUED ATTRIBUTES USING GRADIENT DESCENT FOR LEARNING

2008 ◽  
Vol 16 (02) ◽  
pp. 195-218
Author(s):  
ROELOF K. BROUWER
Keyword(s):  
Objective Function ◽  
Membership Function ◽  
Fuzzy Clustering ◽  
Gradient Descent ◽  
Ratio Scale ◽  
Interval Scale ◽  
Real Numbers ◽  
Fuzzy C Means Clustering ◽  
Feature Values ◽  
The Membership Function

There are well established methods for fuzzy clustering especially for the cases where the feature values are numerical of ratio or interval scale. Not so well established are methods to be applied when the feature values are ordinal or nominal. In that case there is no one best method it seems. This paper discusses a method where unknown numeric variables are assigned to the ordinal values. Part of minimizing an objective function for the clustering is to find numeric values for these variables. Thus real numbers of interval scale and even ratio scale for that matter are assigned to the original ordinal values. The method uses the same objective function as used in fuzzy c-means clustering but both the membership function and the ordinal to real mapping are determined by gradient descent. Since the ordinal to real mapping is not known it cannot be verified for its legitimacy. However the ordinal to real mapping that is found is best in terms of the clustering produced. Simulations show the method to be quite effective.

scholarly journals Effect of Heat Stress on Growth and Physiological Traits of Alfalfa (Medicago sativa L.) and a Comprehensive Evaluation for Heat Tolerance

Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 597 ◽  
Author(s):  
Misganaw Wassie ◽  
Weihong Zhang ◽  
Qiang Zhang ◽  
Kang Ji ◽  
Liang Chen
Keyword(s):  
Heat Stress ◽  
Medicago Sativa ◽  
Membership Function ◽  
Heat Tolerance ◽  
Comprehensive Evaluation ◽  
Soluble Sugar ◽  
Fluorescence Analysis ◽  
Relative Water ◽  
Medicago Sativa L ◽  
Heat Tolerant

Alfalfa (Medicago sativa L.) is a valuable forage legume, but its production is largely affected by high temperature. In this study, we investigated the effect of heat stress on 15 alfalfa cultivars to identify heat-tolerant and -sensitive cultivars. Seedlings were exposed to 38/35 °C day/night temperature for 7 days and various parameters were measured. Heat stress significantly reduced the biomass, relative water content (RWC), chlorophyll content, and increased the electrolyte leakage (EL) and malondialdehyde (MDA) content of heat-sensitive alfalfa cultivars. However, heat-tolerant cultivars showed higher soluble sugar (SS) and soluble protein (SP) content. The heat tolerance of each cultivar was comprehensively evaluated based on membership function value. Cultivars with higher mean membership function value of 0.86 (Bara310SC) and 0.80 (Magna995) were heat tolerant, and Gibraltar and WL712 with lower membership function value (0.24) were heat sensitive. The heat tolerance of the above four cultivars were further evaluated by chlorophyll a fluorescence analysis. Heat stress significantly affected the photosynthetic activity of heat-sensitive cultivars. The overall results indicate that Bara310SC and WL712 are heat-tolerant and heat-sensitive cultivars, respectively. This study provides basic information for understanding the effect of heat stress on growth and productivity of alfalfa.

Using Cloud Model to Improve the Membership Function in Fuzzy Risk Assessment of Reservoir-Induced Seismicity

2013 ◽  
Vol 664 ◽  
pp. 270-275 ◽  
Author(s):  
Ming Zhong ◽  
Qiu Wen Zhang
Keyword(s):  
Risk Assessment ◽  
Membership Function ◽  
Induced Seismicity ◽  
Cloud Model ◽  
Reservoir Induced Seismicity ◽  
Fuzzy Risk Assessment ◽  
The One ◽  
The Relationship ◽  
The Membership Function

Due to the uncertainty and complexity of the causes in reservoir-induced seismicity, the relationship between the environmental factor and the possible earthquake magnitude can be described by membership function. This study aims to propose a fuzzy method to contribute the membership function in which the normal cloud model is applied. Firstly, the cloud model is introduced in detail. Based on normal cloud model, the one-to-many mapping model is presented to deal with the fuzziness and randomness in the membership function. Finally, the case study in Yangtze Three Gorges Reservoir is presented to illustrate the membership cloud function in fuzzy risk assessment of reservoir-induced seismicity. The obtained results show that the proposed method is the viable approaches in solving the problem when the memberships are vague and imprecise.

Analysis and Simulation of Geomagnetic Map Suitability Based on Vague Set

2016 ◽  
Vol 69 (5) ◽  
pp. 1114-1124 ◽  
Author(s):  
Lihui Wang ◽  
Le Yu ◽  
Nan Qiao ◽  
Desheng Sun
Keyword(s):  
Membership Function ◽  
Evaluation Method ◽  
Score Function ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Vague Set ◽  
Weighted Score ◽  
Optimisation Model ◽  
Optimal Area ◽  
The Membership Function

An evaluation method named vague set is proposed to describe the suitability of a geomagnetic map. It is based on the Fuzzy Decision Making (FDM) method, and overcomes the FDM model's shortcomings that favouring and opposing content cannot be taken into account simultaneously. The membership function and non-membership function are used to define the influence of the geomagnetic map parameters on map suitability, including standard deviation, information entropy, roughness and slope variance. The weight of each geomagnetic map parameter is calculated by establishing an optimisation model. Vague set data are divided into four types after classification, and Weighted Score Function Values (WSFVs) of matching areas are obtained by using the Weighted Score Function (WSF) method. Then, WSFV of each matching area are compared to select an optimal area. Simulation results demonstrate that geomagnetic map suitability is positively proportional to the function value, and matching error is negatively proportional to the WSFV of the matching area.

Comparison and comprehensive evaluation of fruit quality of different blueberry (Vaccinium spp.) cultivars

2019 ◽  
pp. 1-10
Author(s):  
Binghua Liu ◽  
Kaifang Wang ◽  
Dengchao Zhao ◽  
Min Jia ◽  
Xiaofang Wang ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Comprehensive Evaluation
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