基于区间语言的灰Vague联系数信息集结方法

在集对分析联系数理论基础上,给出了一种Vague语言区间的信息集结的联系数问题的新思路及算法.其主要方法是将Vague语言区间标度变量转化为集对分析的同、异、反联系数形式,并将其对应的决策矩阵转化为相应灰联系数矩阵,建立计算Vague语言区间的灰联系数属性的记分函数的信任度和不确定因子.通过集结不确定因子的大小进行排序决策.最后,通过具体算例说明该算法的计算步骤及过程.

煤矿安全管理系统的灰色评价及其研究

本文运用灰色关联分析技术对煤矿生产状况的各项安全指标进行综合评价,从而抓住管理工作的重点,为决策者提供可靠依据,保证安全生产的正常进行。

Relationship between Housing Price and Land Price Based on Grey Relational Analysis

In recent Years, China＇s real estate market has been rapid developed, and real estate has become a hot spot of consumption and investment. In some large and medium-sized cities there has been a rapid rise in housing prices. The rapid rise in housing prices has led to difficulties in the purchase of houses in some cities and towns, and this phenomenon has aroused the attention and con- cern of all walks of life. Housing is the basic human life needs. Housing problem is not only an economic problem, but also a social problem. The relationship between house price and land price and the effective control of housing prices have become the focus of government and scholars. Thus, grey relational analysis is used to ana- lyze the relationship between housing prices and land prices, and the grey relational coefficients are calculated.

Structural damage identification using test static data based on grey system theory

A new structural damage identification method using limited test static displacement based on grey system theory is proposed in this paper. The grey relation coefficient of displacement curvature is defined and used to locate damage in the structure, and an iterative estimation scheme for solving nonlinear optimization programming problems based on the quadratic programming technique is used to identify the damage magnitude. A numerical example of a cantilever beam with single or multiple damages is used to examine the capability of the proposed grey-theory-based method to localize and identify damages. The factors of meas-urement noise and incomplete test data are also discussed. The numerical results showed that the damage in the structure can be localized correctly through using the grey-related coefficient of displacement curvature, and the damage magnitude can be iden-tified with a high degree of accuracy, regardless of the number of measured displacement nodes. This proposed method only requires limited static test data, which is easily available in practice, and has wide applications in structural damage detection.

Damage Identification in Beam-Type Structures Using Pseudo Strain Energy Density and Grey Relation Coefficient

Based on pseudo strain energy density (PSED) and grey relation coefficient (GRC), an index is proposed to locate the damage of beam-type structures in time-domain. The genetic algorithm (GA) is utilized to identify the structural damage severity of confirmed damaged locations. Furthermore, a systematic damage identification program based on GA is developed on MATLAB platform. ANSYS is employed to conduct the finite element analysis of complicated civil engineering structures, which is embedded with interface technique. The two-step damage identification is verified by a finite element model of Xinxingtang Highway Bridge and a laboratory beam model based on polyvinylidens fluoride (PVDF). The bridge model was constructed with 57 girder segments, and simulated with 58 measurement points. The damaged segments were located accurately by GRC index regardless of damage extents and noise levels. With stiffness reduction factors of detected segments as variables, the GA program evolved for 150 generations in 6 h and identified the damage extent with the maximum errors of 1% and 3% corresponding to the noise to signal ratios of 0 and 5%, respectively. In contrast, the common GA-based method without using GRC index evolved for 600 generations in 24 h, but failed to obtain satisfactory results. In the laboratory test, PVDF patches were used as dynamic strain sensors, and the damage locations were identified due to the fact that GRC indexes of points near damaged elements were smaller than 0.6 while those of others were larger than 0.6. The GA-based damage quantification was also consistent with the value of crack depth in the beam model.

Multi-attributed decision making for mining methods based on grey system and interval numbers

In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Models for Analyzing the Driving Force of Cultivated Land Supply Change

This paper focuses on a series of quantitative an al ysis models, such as grey relational analysis model, hierarchical cluster an alysis model, principal component analysis model, linear regression model and elastic coefficient model. These models are used to analyze the comprehensive function and effect of driving forces systemically, including analysis on featur es, analysis for differentiating the primary and the secondary, analysis on comp rehensive effects, analysis of elasticity, analysis of prediction. The primary a nd characteristic factors can be extracted by analysis of features and analysis for differentiating the primary and the secondary. Analysis on prediction an d elasticity can predict the area of cultivated land in the future and find out which factors exert great influence on the cultivated land supply.

Evaluation of measurement uncertainty based on grey system theory for small samples from an unknown distribution

To evaluate measurement uncertainty for small sample size and measurement data from an unknown distribution, we propose a grey evaluation method of measurement uncertainty based on the grey relation coefficient. The uncertainty of measurement is analyzed using grey system theory, and the defects of the grey evaluation model of measurement uncertainty (GEMU) are studied. We then establish an improved grey evaluation model of measurement uncertainty (IGEMU). Simulations show that the precision of IGEMU is greater than that of GEMU, and that sample size has only a small effect on the precision of IGEVU. In particular, IGEMU is applied to evaluating measurement uncertainty for small sample size and measurement data from an unknown distribution. The measurement uncertainty of total profile deviation, which is measured by the CNC gear measuring center, can be evaluated by a combination of IGEMU and the Monte Carlo method.

Evaluation and Driving Force Analysis of Marine Sustainable Development based on the Grey Relational Model and Path Analysis

With the rapid development of the marine economy,the demand for marine resources development and the pressure on marine environmental protection are gradually increasing.It is critical to evaluate and analyze the driving forces of marine sustainable development in order to promote the coordinated development of the marine economy,resources and environment.Taking Jiangsu Province of China as an example,this paper constructs an evaluation index system for marine sustainable development from the three aspects of marine economy,resources and environment,and calculates the weight of the variation coefficient for each indicator.Based on the grey relational model,the average value of the relational degree,calculated by the average value method of correlation coefficients and the weighting method,is then used to evaluate the status of marine sustainable development in this province.The comprehensive index model is used to analyze the dynamic trend of the evolution of marine sustainable development.The driving forces of marine sustainable development are analyzed by the path analysis method combined with the average values of the grey relational degree for each indicator.This analysis found that the marine sustainable development in 2016 and 2012 was good,the situation in 2007 was bad,and the remaining years were intermediate.Compared with the previous years,the optimal conditions of 2008 and 2012 were obvious.The main driving factors of marine sustainable development are cargo throughput of coastal ports,economic losses caused by storm surges in coastal areas,the area of marine nature reserves in coastal areas,coastal wind power generation capacity,and marine biodiversity.