Decomposition of fuzzy exponential mathematical quantitative process in industrial manufacturing design

2020 ◽  
pp. 1-10
Author(s):  
Yuan Cheng ◽  
Kunqian Wang
Keyword(s):  
Fuzzy Sets ◽  
Influencing Factors ◽  
Evaluation System ◽  
Fuzzy Inference ◽  
Uncertain Reasoning ◽  
Fuzzy Decision ◽  
Manufacturing Enterprises ◽  
Industrial Manufacturing ◽  
Manufacturing Design ◽  
The Evaluation System

Small and medium-sized manufacturing enterprises have the characteristics of large numbers and small scales. Problems such as backward manufacturing technology, lack of talents, small amount of information resources, and insufficient product research and development capabilities have severely restricted the development of enterprises. The backward manufacturing design model cannot adapt to the development trend of modern manufacturing informatization. This paper proposes and designs a fuzzy inference model and fuzzy inference engine algorithm with threshold. In order to describe the numerical multiple input and multiple output variables in the industrial manufacturing design industry, the relevant experience is used to make numerical reasoning decisions. Applying fuzzy sets and fuzzy theory to the expert system, a fuzzy rule model containing the membership function information and thresholds of the corresponding fuzzy sets is proposed and established, and a fuzzy reasoning system suitable for numerical and uncertain reasoning decisions is constructed. The improved grey relational analysis method is used to decompose and evaluate the exponential mathematical quantitative process of manufacturing enterprises. Based on the fuzzy Decision Analytic Network Process (DANP) method to calculate the relative weight of the influencing factors in the evaluation system, the evaluation index of the enterprise is obtained. Starting from the industrial manufacturing design process, this article constructs a relatively comprehensive and reasonable enterprise exponential mathematical quantitative process decomposition evaluation system. Considering that there are complex interactions between the various influencing factors in the system, the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method is selected to process the direct impact matrix of the evaluation system, and the causal relationship between the indicators is obtained. The fuzzy exponential gray correlation method is used to evaluate the quantitative process of industrial manufacturing design, avoiding the shortcomings of traditional methods that only consider ideal values.

Study a Fuzzy Inference System on the Supplier Evaluation in E-Manufacturing

2009 ◽  
Vol 16-19 ◽  
pp. 189-192 ◽  
Author(s):  
Jian Chen ◽  
Ming Hong Wu ◽  
Wen Rong Jiang ◽  
An Bao Wang ◽  
Ji Hong Yan
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Fuzzy Inference System ◽  
Evaluation System ◽  
Supplier Selection ◽  
Fuzzy Inference ◽  
Supplier Evaluation ◽  
Inference System ◽  
Key Factor

The supplier selection and evaluation is a key factor of the intelligent supplier selection & evaluation system in e-manufacturing. The model used for supplier selection is Fuzzy inference system which is introduced in the paper. The paper started with the brief introduction of the intelligent internet supplier selection & evaluation system. It concentrated to introduce the application of the fuzzy set model for supplier selection. This paper will introduce the design of the fuzzy sets model, and the evaluation results.

scholarly journals Type-II Fuzzy Decision Support System for Fertilizer

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ather Ashraf ◽  
Muhammad Akram ◽  
Mansoor Sarwar
Keyword(s):  
Decision Support ◽  
Fuzzy Sets ◽  
Membership Function ◽  
Fuzzy Set ◽  
Fuzzy Inference ◽  
Type I ◽  
Type Ii ◽  
Membership Functions ◽  
Fuzzy Decision ◽  
Fuzzy Decision Support System

Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, whether to go for a triangle membership function or a trapezoidal membership function. In this paper we use a type-II fuzzy set to overcome this uncertainty, and develop a fuzzy decision support system of fertilizers based on a type-II fuzzy set. This type-II fuzzy system takes cropping time and soil nutrients in the form of spatial surfaces as input, fuzzifies it using a type-II fuzzy membership function, and implies fuzzy rules on it in the fuzzy inference engine. The output of the fuzzy inference engine, which is in the form of interval value type-II fuzzy sets, reduced to an interval type-I fuzzy set, defuzzifies it to a crisp value and generates a spatial surface of fertilizers. This spatial surface shows the spatial trend of the required amount of fertilizer needed to cultivate a specific crop. The complexity of our algorithm isO(mnr), wheremis the height of the raster,nis the width of the raster, andris the number of expert rules.

Study on Echo Fidelity of Radar Simulator

2014 ◽  
Vol 687-691 ◽  
pp. 1117-1120
Author(s):  
Yin Hui Xu ◽  
Fu Zhi Wang ◽  
Yi Long Liu ◽  
Da Zhi Zeng
Keyword(s):  
Numerical Calculation ◽  
Evaluation System ◽  
Calculation Methods ◽  
Simulation Fidelity ◽  
Research Status ◽  
Similarity Calculation ◽  
Radar Echo ◽  
Echo Simulation ◽  
Radar Simulator ◽  
The Evaluation System

Echo fidelity is an important characteristic of radar simulator and it influences accuracy and reliability of radar test directly. This paper introduces the research status of simulator fidelity and sort out the definition and property of radar echo simulation fidelity. Then we propose the numerical calculation methods for individual indicators, including similarity calculation, dissimilarity computing and interval changes three parts. Finally, on the basis of the evaluation system, we propose two calculation methods for entirety fidelity, they are weighted numerical calculation and umbrella figure methods.

The evaluation system in the degree course in medicine

1993 ◽  
Vol 14 (S7) ◽  
pp. 575-578
Author(s):  
A. Bonetto ◽  
E. S. Curtoni
Keyword(s):  
Evaluation System ◽  
The Evaluation System

Evaluation Indexes of Sand Liquefaction Analysed by Rough Set

2011 ◽  
Vol 243-249 ◽  
pp. 3087-3091
Author(s):  
Nian Ping Liu ◽  
Hong Tu Wang ◽  
Zhi Gang Yuan
Keyword(s):  
Rough Set ◽  
Groundwater Level ◽  
Analytical Method ◽  
Evaluation System ◽  
Evaluation Index ◽  
Determination Method ◽  
Sand Liquefaction ◽  
Evaluation Indexes ◽  
Result Show ◽  
The Evaluation System

Sand liquefaction is a problem of complex evolution of the disaster, there is no accurate way to judge at present, this study put forward an analytical method to improve and optimize the evaluation system of sand liquefaction based on rough set. The significance of indexes are confirmed by calculating rough dependability between indexes and result for appraisement, the result show that SPT blow count has the greatest impact on the evaluation system, the groundwater level has greater impact, followed by the sand depth, epicenteral distance and duration. The proposed approach overcame the subjectivity of traditional weight determination method, so it is more objective and accurate, and it is reasonable and effective to optimize the evaluation index of sand liquefaction.

Research on Horizontal Well Development Effect Assessment in Super-Low-Abundance Thin Reservoir

2012 ◽  
Vol 524-527 ◽  
pp. 1261-1265
Author(s):  
Bin Nie ◽  
Yue Tian Liu ◽  
Ting Jing Zhang
Keyword(s):  
Evaluation System ◽  
Horizontal Well ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Evaluation Approach ◽  
Analysis Process ◽  
Statistical Analysis Method ◽  
Well Development ◽  
Thin Reservoir ◽  
The Evaluation System

Based on the actual production data, this paper selected some evaluation parameters and established reasonable evaluation criterion for the horizontal well development effect in the ultra low-abundance and thin zone reservoir by using statistical analysis method，reservoir engineering analysis process and reservoir numerical simulation technology .In addition, a development effect evaluation system specially for the horizontal well development effect in the ultra low-abundance and thin layer reservoir was build up with the fuzzy comprehensive evaluation approach. Finally, the evaluation system were applied in several low-abundance and thin reservoir blocks. It was shown that the evaluation system can scientifically estimate the development effect of this kind of reservoir and has a practical application value.

STEREOVISION-BASED FUZZY OBSTACLE AVOIDANCE METHOD

2011 ◽  
Vol 08 (01) ◽  
pp. 169-183 ◽  
Author(s):  
LAZAROS NALPANTIDIS ◽  
ANTONIOS GASTERATOS
Keyword(s):  
Obstacle Avoidance ◽  
Efficient Solution ◽  
Fuzzy Inference ◽  
Autonomous Mobile Robots ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Inference System ◽  
Depth Maps ◽  
Complex Processes ◽  
Stereo Algorithm

This work presents a stereovision-based obstacle avoidance method for autonomous mobile robots. The decision about the direction on each movement step is based on a fuzzy inference system. The proposed method provides an efficient solution that uses a minimum of sensors and avoids computationally complex processes. The only sensor required is a stereo camera. First, a custom stereo algorithm provides reliable depth maps of the environment in frame rates suitable for a robot to move autonomously. Then, a fuzzy decision making algorithm analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on a variety of self-captured outdoor images and the results are presented and discussed.

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