Triangular Whitenization Weight Function Research Articles

Selection of Logistics Service Provider for port enterprises: Combination of the weighting-grey synthetic decision-making method

The purpose of this paper is to explore how port enterprises can scientifically select a better logistic service provider (LSP) to achieve a high efficiency. An empirical study is conducted to verify the effectiveness of the combination weighting-grey synthetic decision-making method by helping the LSP selection of a port enterprise in China. Data are collected from questionnaires administered to port logistics’ industry professionals. The method is proposed, which associates the analysis network process method with the entropy method to determine the combined weights of the evaluation indexes. The improved centre-point triangular whitenization weight function is introduced to cluster the alternative port LSPs and judge the corresponding grey classes. Subsequently, the synthetic weighted decision-making vectors are used to determine the grey synthetic decision-making coefficient vectors. The grey synthetic clustering decision-making coefficients are calculated to establish a synthetic decision-making rank of the alternative plans. The combined method can help the port enterprises realize the selection of better LSPs in a scientific manner.

Applying Grey Clustering Method and Pearson Correlation to Assess Water Quality

The Mantaro River travels through Junín, Ayacucho, and Huancavelica departments,in Peru, and receives not only domestic discharges from the population but also tailings fields and dumps containing lead, silver, copper, and zinc from mining companies. To be able to assess the water quality, the grey clustering method was applied, using Center-point Triangular Whitenization Weight Functions (CTWF) for this purpose. As well, Pearson correlation between parameters was used to understand the dynamics of pollution. In the watershed of the Mantaro river the results of the Monitoring of the Surface Water published in 2018 by the Mantaro Water Administrative Authority were compared to the Peruvian Environmental Quality Standards (ECA) Category 1, subcategory A parameters. The results obtained suggest that the main driver of pollution in the Mantaro river is not mining, but domestic waste in landfills and probably agriculture. Finally, this study shows responsible environmental management by mining companies, besides, could be helpful for regional and local authorities of Peru in making decisions to improve the management of the Mantaro river watershed and make the population aware of the sustainable use of water

Gray Evaluation of Water Inrush Risk in Deep Mining Floor.

With the increase of the mining intensity of coal resources in China, the geological conditions of minefields have become more and more complex. The mining conditions of high pressure and high stress bring great challenges to the safe mining of coal resources. To accurately evaluate the risk of water inrush from the broken floor under high pressure and high stress, a gray evaluation model coupling the work breakdown structure (WBS), the risk-based supervision (RBS) theory, ordered binary comparison quantization method, and the center-point triangular whitenization weight function was proposed in this paper. Taking the No. 21 coal seam of Shanxi Formation in Guhanshan minefield as an example, studying the distribution characteristics of high pressure and high stress and the water inrush mechanism from the broken floor during No. 21 coal seam mining and analyzing the hydrochemical characteristics of the main water inrush aquifers below the No. 21 coal seam floor, this paper determined five main factors, including fault fractal dimensions, aquifer pressure, water-richness, destroyed floor depth, and effective aquiclude thickness. First, the work breakdown structure (WBS), the risk-based supervision (RBS) theory, and the ordered binary comparison quantization method were used to calculate the weight vectors of each index. Then, the center-point triangular whitenization weight function based on the work breakdown structure (WBS), the risk-based supervision (RBS) theory, and the ordered binary comparison quantization method were constructed to evaluate the water inrush risk from the broken floor under high pressure and high stress. Finally, the risk of water inrush from the broken floor during No. 21 coal seam mining in Guhanshan minefield was predicted using the gray evolution trend, which effectively reflects the risk characteristics of water inrush from the coal seam floor under high pressure and high stress. The results show that the evaluation and prediction results are consistent with the actual situation in Guhanshan minefield, which indicates that the model is suitable for evaluating and predicting the risk of water inrush from the broken floor under high pressure and high stress.

Modelamiento y evaluación del nivel de calidad del aire mediante el análisis de Grey Clustering, estudio de caso Lima Metropolitana

Actualmente los parámetros de la evaluación de la calidad del aire se analizan de manera independiente; dejando lado el enfoque sistémico del ambiente, el cual establece que la calidad del aire está influenciada y controlada por muchos tipos de factores, en donde varios parámetros interactúan y se restringen mutuamente, por tal razón se propone un sistema de evaluación superior, que tome en cuenta el alto grado de incertidumbre presente en el medio, dicho sistema es la metodología de análisis de Grey Clustering cuya base es la lógica difusa. La propuesta metodológica evaluará el nivel de calidad de aire en Lima Metropolitana, mediante el método de “Triangulación del punto medio en base a funciones de Whitenización – CTWF”, en donde se demostrará que el modelo propuesto es exacto, comparable y aplicable. Los datos de calidad del aire se obtuvieron del Servicio Nacional de Meteorología e Hidrología del Perú-Senamhi. El método CTWF se aplicó utilizando los principales indicadores de la calidad del aire, tales como, PM10, PM2.5, SO2 y N02. Los datos de muestreo se clasificaron usando el Índice de Calidad del Aire Anual –YACAQI; como resultado de la evaluación de la calidad del aire se determinó que la mayoría de distritos presentaban problemas muy graves de contaminación del aire. El diagnóstico permitirá que la sociedad en general y municipalidades tengan como resultado un instrumento técnico de análisis objetivo e integral, que brinda resultados fáciles de interpretar y permita enfocar los principales contaminantes persistentes en el medio.

A combined thermal power plant investment decision-making model based on intelligent fuzzy grey model and ito stochastic process and its application

Uncertainties are often involved in the investment decision making of the coal-fired power plant. They are often characterized by diversity and fuzziness. In order to minimize their adverse effects on the evaluation of investment, we proposed a novel combined thermal power plant investment decision-making model. This model takes the Net Present Value(NPV) as the objective function, and takes the predictions of revenue and cost as the center. With regard to revenue prediction, Self-adapting Intelligent Grey prediction Model (SIGM) combined with Interval Grey number Prediction Model based on the Triangular whitenization weight function(IGPM_T) model is employed to forecast the changing tendency of the on-grid price, which is the decisive factor for revenue of power plant. With respect to cost prediction, Ito stochastic process theory is utilized to simulate the variation tendency of the operating cost of power generation. In order to acquire the key drift and floating coefficients in the formula of Ito process, the combinatorial simulation experiment is conducted, and by visual comparison, rational coefficient combination is determined. Finally, the reliability and validity of the proposed combined model are verified through an example of a coal-fired power plant, and results show that the proposed model can provide satisfactory evaluation for thermal power plant investment.

Evaluation of the Attack Effect Based on Improved Grey Clustering Model

There are a lot of uncertainties and incomplete information problems on network attack. It is of great value to access the effect of the attack in the current network attack and defense. This paper examines the characteristics of network attacks, there are problems with traditional clustering that index attribution is not clear and the cross of clustering interval. A two-stage grey synthetic clustering evaluation model based on center-point triangular whitenization weight function was proposed for the attack effect. The authors studied the feasibility of applying this model to the evaluation of network attack effect. Finally, an example is given, which showed the model could evaluate the effect of the denial-of-service attack precisely. It is also shown that the model is viable to evaluate the attack effect.

A novel grey fixed weight cluster model based on interval grey numbers

PurposeNowadays, evaluation objects are becoming more and more complicated. The interval grey numbers can be used to more accurately express the evaluation objects. However, the information distribution of interval grey numbers is not balanced. The purpose of this paper is to introduce the central-point triangular whitenization weight function to solve the clustering process of this kind of numbers.Design/methodology/approachA new expression of the central-point triangular whitenization weight function is presented in this paper, in terms of the grey cluster problem based on interval grey numbers. By establishing the integral mean value function on the set of interval grey numbers, the application range of grey clustering model is extended to the interval grey number category, and, in this way, the grey fixed weight cluster model based on interval grey numbers is obtained.FindingsThe model is verified by a case which reveals a high distinguishability, validity and practicability.Practical implicationsThis model can be used in many fields, such as agriculture, economy, geology and medical science, and provides a feasible method for evaluation schemes in performance evaluation, scheme selection, risk evaluation and so on.Originality/valueThe central-point triangular whitenization weight function is introduced. The method reflects the thought “make full use of the information” in grey system theory and further enriches the system of grey clustering theory as well as expands the application scope of the grey clustering method.

Grey-Markov prediction model based on background value optimization and central-point triangular whitenization weight function

Grey-Markov forecasting model is a combination of grey prediction model and Markov chain which show obvious optimization effects for data sequences with characteristics of non-stationary and volatility. However, the state division process in traditional Grey-Markov forecasting model is mostly based on subjective real numbers that immediately affects the accuracy of forecasting values. To seek the solution, this paper introduces the central-point triangular whitenization weight function in state division to calculate possibilities of research values in each state which reflect preference degrees in different states in an objective way. On the other hand, background value optimization is applied in the traditional grey model to generate better fitting data. By this means, the improved Grey-Markov forecasting model is built. Finally, taking the grain production in Henan Province as an example, it verifies this model's validity by comparing with GM(1,1) based on background value optimization and the traditional Grey-Markov forecasting model.

An uncertain programming model for preventive maintenance scheduling

PurposeThe purpose of this paper is to illustrate an uncertain programming model for scheduling of preventive maintenance (PM) actions. The PM scheduling, in which PM actions are performed under fixed intervals, is solved by grey systems theory.Design/methodology/approachThe paper applied the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint evaluation method and center-point evaluation method.FindingsTwo methods give the same results based on endpoint and center-point triangular whitenization weight functions. For validation, the results were compared by Cassady’s method.Originality/valueThe scheduling of PM is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. It is helpful to reduce the outage loss on frequent repair/replacement parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency.

Evaluation of the derivative environment in coal mine safety production systems: Case study in China

The derivative environment can be separated into five elements: the production condition, job security condition, management regulation, organizational interaction, and culture diffusion. Through field research at three large state-owned coal mining groups in China, all elements of the derivative environment are evaluated in five grey classes from the perspective of reality, expectation, and ideality by using the mixed center-point triangular whitenization weight function method. The results indicate that the derivative environment sends out inferior signals on the whole. From the reality perspective, the production condition is in the “poor” grey class, while the elements of job security condition, management regulation, and organization interaction are in the “pass” grey class. Culture diffusion is located in the “good” grey class. From the expectation perspective, management regulation shows a positive trend, among which the operation pattern, awards and penalty system, and basic safety management system is highlighted the most, while organization interaction shows a negative trend, with caring features prominent therein. From the ideality perspective, there is a deviating phenomenon in key derivative sub-elements such as facility level, working time, labor intensity, wages, feedback of basic rights, organizational respect, and communication, which are far beyond an ideal level. The results are of great reference value, improving the level of the derivative environment and promoting the balance between the industrial development and safety control of coal mines.

Evaluation of the Modernization of Hydraulic Projects Management Compact-Center-Point Triangular Whitenization Weight Function

In the actual analysis of grey clustering evaluation, it has been found that the length of the grey clustering interval is partially larger, which is determined by the method of grey clustering evaluation based on the center-point triangular whitenization weight function. In order to solve this problem, a new grey evaluation method based on reformative triangular whitenization weight function is researched. The existing end-point triangular whitenization weight function and center-point triangular whitenization weight function are revised, and a new compact-center-point triangular whitenization weight function is constructed. Then the rules for grey category intervalof the three triangular whitenization weight functions are compared, and an example about the evaluation of the modernization of hydraulic projects management is proposed for analyzing the three methods to further verify that the improved grey clustering evaluation method based on the compact-center-point triangular whitenization weight function is feasible and effective. The results show that the compact-center-point triangular whitenization weight function is superior to both the end-point triangular whitenization weight function and the center-point triangular whitenization weight function.

Grey cluster evaluation models based on mixed triangular whitenization weight functions

Purpose – The purpose of this paper is to present two novel grey cluster evaluation models to solve the difficulty in extending the bounds of each clustering index of grey cluster evaluation models. Design/methodology/approach – In this paper, the triangular whitenization weight function corresponding to class 1 is changed to a whitenization weight function of its lower measures, and the triangular whitenization weight function corresponding to class s is changed to a whitenization weight function of its upper measures. The difficulty in extending the bound of each clustering indicator is solved with this improvement. Findings – The findings of this paper are the novel grey cluster evaluation models based on mixed centre-point triangular whitenization weight functions and the novel grey cluster evaluation models based on mixed end-point triangular whitenization weight functions. Practical implications – A practical evaluation and decision problem for some projects in a university has been studied using the new triangular whitenization weight function. Originality/value – Particularly, compared with grey variable weight clustering model and grey fixed weight clustering model, the grey cluster evaluation model using whitenization weight function is more suitable to be used to solve the problem of poor information clustering evaluation. The grey cluster evaluation model using endpoint triangular whitenization weight functions is suitable for the situation that all grey boundary is clear, but the most likely points belonging to each grey class are unknown; the grey cluster evaluation model using centre-point triangular whitenization weight functions is suitable for those problems where it is easier to judge the most likely points belonging to each grey class, but the grey boundary is not clear.

Grey clustering evaluation of urban low-carbon transport development based on triangular whitenization weight function

Purpose – The purpose of this paper is to establish a grey clustering evaluation model based on center-point triangular whitenization weight function to evaluate the situation of urban low-carbon transport development (LTD). The study results intend to provide some theoretical basis and tool support for transport management departments and related researchers who are engaged in low-carbon transport (LT). Design/methodology/approach – The study uses analytical hierarchy process based on expert investigations to determine the weight of each criteria, classifies the grey clusters based on center-point triangular whitenization weight function, calculates the membership of each development criteria and ranks the development level of all dimensions. Findings – The research results of case city show that low-carbon technology is in “poor” level, transport facility is in “superior” level, low-carbon policy and environmental coordination is in “intermediate” level, transport management is in “good” level and the overall LTD level is in “intermediate” level. Practical implications – Reducing the carbon emissions of urban transport and achieving LT is the key to promote urban sustainable development, the scientific judgment of transport development situation is the premise of promoting LTD. Therefore, based on the practices of LT in China, the study systematically clarifies LTD from five dimensions of reflecting LTD. Originality/value – From the perspective of sustainable development, the evaluation index system of LTD is built with five dimensions consisting of low-carbon technology, low-carbon policy, transport facility, transport management and environmental coordination. Then assess the LTD by using the grey clustering evaluation model based on center-point triangular whitenization weight. This paper presents a new research idea for LTD evaluation.

Evaluation of scheduling using triangular whitenization functions

Purpose – The time required for a certain task to be performed normally reduces on its frequent completion, as more units are produced over time, it is expected to have an increase in the total worker’s output performance. Learning curve (LC) is a mathematical representation to estimate the time of tasks which occurs repeatedly. The parameter prediction is considered a major disadvantage from which LC suffers. The purpose of this paper is to investigate grey systems theory as a method for the standard time. Design/methodology/approach – The proposed method starts with data which are obtained by traditional time study and then, models LC for an assembling activity of Electrogen Company. The paper studies the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint triangular whitenization functions and center-point triangular whitenization functions. The grey system results are compared with those of the LC. Findings – The results show that the standard time given by grey systems theory is closer than the standard time given by LC to standard time with 100 per cent performance level. Originality/value – Scheduling problems are complex and uncertain, and it is very rare for such systems to be exactly determined in all their complexity. According to grey systems theory, the job processing time can be considered as the object that extension is definite but intension is uncertain. Consequently, grey systems theory with its focus on the uncertainty problems of small samples and incomplete information is proposed in the paper.

Grey Clustering Evaluation Model Based on D-S Evidence Theory to Evaluate the Scheme of Basin Initial Water Rights Allocation

In view of the characteristics of the randomness and uncertainty of basin initial water rights allocation scheme evaluation, this paper, integrating the Dempster-Shafer (D-S) evidence theory and the grey clustering evaluation method, researches on the evaluation method of allocation scheme. Taking advantages of D-S evidence theory and the compact- center-point triangular whitenization weight function (CCTWF) in processing and integrating the uncomplete information, the grey clustering evaluation model based on D-S evidence theory is proposed. The integrated clustering coeffi- cients matrix is obtained by using the grey clustering evaluation method based on CCTWF, and we look each clustering object as an evidence. Then, D-S evidence theory is used to obtain the belief function of every evidence with application of Dempster's combination rule, and the result of scheme evaluation in terms of the principle of selecting maximum value of belief functions. Finally, we take the evaluation of basin initial water rights allocation scheme of Dalinghe River in China for instance to demonstrate the practicability and effectiveness of this model.

Grey clustering evaluation based on triangular whitenization weight function of enterprise's management innovation performance

Purpose– The purpose of this paper is to attempt to establish a grey clustering evaluation model of center-point triangular whitenization weight function to measure the performance of enterprise's management innovation (MI). The author intends to provide some theory basis and tool support for enterprise's managers and other researchers who are engaged in performance measuring.Design/methodology/approach– The study uses questionnaire survey and expert interviews to determine the index weight of enterprise's MI performance (MIP), classifies the grey clusters based on center-point triangular whitenization weight function, calculates the membership of performance criteria and ranks the performance level of all dimensions.Findings– The survey data of case company shows that production performance is in superior level, employee and society influence performance are in satisfied level, finance and market performance are in intermediate level, total MIP is in satisfied level.Practical implications– MI is the fundamental way to keep enterprise's core competitiveness and achieve its strategic objectives. Performance is an effective tool to measure the MI. Therefore, based on the practices of MI in China, the study systematically clarifies the performance level of MI from five dimensions.Originality/value– The evaluation index of enterprise's MIP is built with five dimensions which contain production, market, finance, employee and social influence. The grey clustering evaluation model based on triangular whitenization weight function is applied to assess the performance criteria. This paper presents a new research idea for enterprise's performance evaluation.

Grey evaluation empirical study based on center-point triangular whitenization weight function of Jiangsu Province industrial technology innovation strategy alliance

Purpose– This paper aims to investigate the performance of Jiangsu Province industrial technology innovation strategy alliance.Design/methodology/approach– Through a preliminary investigation of 30 Jiangsu industrial technology innovation strategic alliances, this paper analyzed the status and extracted 18 alliances to conduct an in-depth investigation. By grey evaluation method based on center-point triangular whitenization weight function, the paper classified and analyzed alliances.Findings– The results show that university or research institutions-oriented alliance perform better, but the government/enterprise-oriented alliance perform diverse, and majority is rated “general”.Originality/value– The paper succeeds in clustering analysis to Jiangsu Province industrial technology innovation strategy alliance with insufficient data. And according to the result of clustering, it analyzes the causes, which provide value information for the sustainable development of Jiangsu Province industrial technology innovation strategy alliance.

Grey Evaluation Model Based on Reformative Triangular Whitenization Weight Function and Its Application in Water Rights Allocation System

In the actual analysis of grey clustering evaluation, the length of a grey clustering interval was partially longer, which is determined by the grey clustering evaluation method based on the center-point triangular whitenization weight function. In response to problems like this, this paper proposes a new grey evaluation method on the basis of the reformative triangular whitenization weight function. Motivated by ideas of the end-point and the center-point triangular whitenization weight functions, we construct a new compact-center-point triangular whitenization weight function. Then, several aspects of the three kinds of triangular whitenization weight functions are compared, such as the crossing properties of grey cluster, clustering coefficients, rules for grey clustering interval, rules for choosing end-points and clustering performance. In the following, this paper proposes an example about the evaluation of a basin initial water rights allocation scheme, which analyzes the three methods to further verify that the new grey clustering evaluation method is feasible and effective. The results indicate that the compact-center-point triangular whitenization weight function precedes the end-point triangular whitenization weight function and the center-point triangular whitenization weight function soundly.