Fuzzy Statistical Method Research Articles

A scientific decision-making framework for supplier outsourcing using hesitant fuzzy information

Supply chain management (SCM) is an attractive area for research which has seen tremendous growth in the past decades. From the literature we observe that, supplier outsourcing (SO) is a highly explored research field in SCM which lacks significant scientific contribution. The major concern in SO is the decision makers’ (DMs) viewpoint which are often vague and imprecise. To better handle such imprecision, in this paper, we propose a new two-stage decision-making framework called TSDMF, which uses hesitant fuzzy information as input. In the first stage, the DMs’ preferences are aggregated using a newly proposed simple hesitant fuzzy-weighted geometry operator, which uses hesitant fuzzy weights for better understanding the importance of each DM. Following this, in the second stage, criteria weights are estimated using newly proposed hesitant fuzzy statistical variance method and finally, a new ranking method called three-way hesitant fuzzy VIKOR (TWHFV) is proposed by extending the VIKOR ranking method to hesitant fuzzy environment. This ranking method uses three categories viz., cost, benefit and neutral along with Euclid distance for its formulation. The practicality of the proposed TSDMF is verified by demonstrating a supplier outsourcing example in an automobile factory. The robustness of TWHFV is realized by using sensitivity analysis and other strengths of TSDMF are discussed by comparison with another framework.

Multi-level Fuzzy Statistics and Maximum Entropy Rule Based Comprehensive Evaluation Strategy for Development Level of Global Energy Interconnection

Global energy interconnection is the next development stage of future power grid. In order to evaluate its development level and identify the weakness spot in the developing process, a comprehensive evaluation strategy for development level of global energy interconnection is proposed in this paper. This strategy is proposed based on the fuzzy statistics method and maximum entropy rule. The effectiveness of this evaluation strategy is illustrated through calculation examples. The calculation results show that the development degree of global energy interconnection in China, United States and Germany has reached a very good level.

Analysis of C2C Website Competitiveness Based on Text Sentiment Analysis and Dynamic Fuzzy Computation

With the global step into the era of large data, online review data show an explosive growth trend, and the resulting information overload has affected the consumer’s decision making. In terms of consumers, to tap the purchase decision-making information from the vast amount of information is a must-do before the tedious process; how to find the best service from a variety of shopping sites and find satisfied products from thousands of Products and how to help companies improve themselves, has become the forefront of e-commerce research topics. In this paper, data acquisition, data filtering, theme analysis, correlation analysis, sentiment analysis and dynamic fuzzy statistics are introduced to the user-generated content (UGC) fuzzy comprehensive evaluation. Firstly, collect the data, we use the correlation analysis and the stopped words to reduce the dimensionality of the data, and generate the revised candidate sets of themes. Then, we use emotion extraction, emotion polarity judgment and comment analysis to divide the UGC into several evaluation grades; then we get the fuzzy comprehensive evaluation matrix by the fuzzy statistic method. Finally, the comprehensive evaluation model is constructed to give users product score and the C2C website ranking.

Development of fuzzy statistical method of optimal resource allocation among technical departments of an electric utility company

We formulated the approach to solving specific aspects of the task of strategic planning of sustainable development of an electric utility enterprise as a multi-criteria decision-making problem, which can be solved under conditions of fuzzy initial information. To solve this task, the method of constructing a set of feasible solutions was proposed, based on the specific functioning of an enterprise divisions. The set of feasible variants is compiled according to the Pareto method, when no element can be improved without worsening of at least one of the other elements, which makes it possible to define a compromise allocation of funding, at which the minimum possible value of the risk of an accident in the electric utility enterprise’s networks is provided. As an optimizationl criterion, we adopted the risk of an accident occurrence in an electric utility system.To solve the task of risk evaluation at solving a linear programming problem, we applied the method, which allows evaluating the risk by analytical way without carrying out probabilistic-statistical modeling. As a result, the developed method is efficient for practical application during an express evaluation of the risk at different variants of the allocation of funds among the units of electric utility enterprise without carrying out of cumbersome probabilistic-statistical modeling.

Condition Assessment Model for Subsection Vacuum Switch in Service Based on Fuzzy Synthetic Evaluation

In order to solve the problems of subsection vacuum switch repair deficiency and blind repair and to improve the accuracy of the subsection vacuum switch condition assessment we put forward a strategy based on the theory of fuzzy evaluation. Firstly, a layered evaluation index system on the base of preventive experiments, including working surroundings, operation history, maintenance records, and accessories section and so on is built. Then, the relative impairment degree is introduced to describe the relative grade of subsection vacuum switch changing from actual conditions to faults. The member functions for qualitative indices and the quantitative indices are respectively determined with helps of a fuzzy statistic method and a fuzzy distribution method. An operation condition evaluation model evaluates the state of every grade and gives a comprehensive assessment of subsection vacuum switch, is established on the base of the fuzzy synthetic judgment. Example analysis shows t the method for the safe operation of the transformer condition assessment of reliability is higher and more accurate.

A Novel Application of Fuzzy Statistical Methods in Economic Decisions Making

A Novel Application of Fuzzy Statistical Methods in Economic Decisions Making

A new integrative evaluation method for candidate reservoirs of hydrocarbon gas drive

Before implementing hydrocarbon gas drive, an applicable evaluation of reservoirs for hydrocarbon gas drive can improve the success rate and economic benefit. On the basis of a large amount of literature research, 11 factors affecting the hydrocarbon gas injection development have been screened out. These 11 factors constitute the suitability evaluation indexes of candidate reservoirs for hydrocarbon gas drive. Meantime, the classification of 11 evaluation indexes has also been set up, and fuzzy statistical method, analytic hierarchy process, and expert assessment method have been adopted to obtain the weight value of each evaluation index. Three candidate reservoirs have been taken for example; using multi-level fuzzy comprehensive evaluation to optimize the most suitable candidate reservoir, the potential size of three candidate reservoirs for hydrocarbon gas drive is provided. By comparing the evaluation results with the numerical reservoir simulation results, the evaluation method not only gives a correct evaluation for candidate reservoirs but also has a high practicability and reliability.

A dimension reduction technique for two-mode non-convex fuzzy data

Fuzzy modeling and fuzzy statistics provide useful tools for handling empirical situations affected by vagueness and imprecision in the data. Several fuzzy statistical models and methods (e.g., fuzzy regression, fuzzy principal component analysis, fuzzy clustering) have been developed over the years. Generally the standard LR-fuzzy data representation has been used in these methods. However, several empirical contexts, such as human ratings and decision making, may show more complex fuzzy structures which cannot be successfully modeled by the LR representation. In all these cases another type of fuzzy data representation, the so-called LHIR representation, should be preferred instead. In particular, this novel representation allows to handle with fuzzy data which are characterized by non-convex membership functions. In this paper, we address the problem of summarizing large datasets characterized by two-mode non-convex fuzzy data. We introduce a novel dimension reduction technique (NCFCA) based on the framework of Component Analysis and Least squares programming. Finally, to better highlight some important characteristics of the proposed model, we apply NCFCA to three empirical datasets concerning behavioral and socio-economic issues.

Investigation of emergency automation failures influence on the power system accident risk

To improve the power system reliability, it is necessary to organize efficient management. Effective management requires an integrated approach which takes into account the probabilistic nature of failures, stochasticity of modes, possible scenarios of the accident and its consequences. Technical risk most fully covers all the factors. The paper presents the fuzzy-statistical method for assessing the accident probability and risk in the power system. The proposed method takes into account the operation of system emergency automation devices and their operable or inoperable condition. Modeling of the 14-node test circuit of the power system was performed using the developed method. Probability of dynamic stability loss on the time interval was estimated for this circuit. The results have confirmed the adequacy of the developed fuzzy-statistical method and shown the need to consider the operation and condition of system emergency automation to obtain reliable results.

Encoding words into Cloud models from interval-valued data via fuzzy statistics and membership function fitting

When constructing the model of a word by collecting interval-valued data from a group of individuals, both interpersonal and intrapersonal uncertainties coexist. Similar to the interval type-2 fuzzy set (IT2 FS) used in the enhanced interval approach (EIA), the Cloud model characterized by only three parameters can manage both uncertainties. Thus, based on the Cloud model, this paper proposes a new representation model for a word from interval-valued data. In our proposed method, firstly, the collected data intervals are preprocessed to remove the bad ones. Secondly, the fuzzy statistical method is used to compute the histogram of the surviving intervals. Then, the generated histogram is fitted by a Gaussian curve function. Finally, the fitted results are mapped into the parameters of a Cloud model to obtain the parametric model for a word. Compared with eight or nine parameters needed by an IT2 FS, only three parameters are needed to represent a Cloud model. Therefore, we develop a much more parsimonious parametric model for a word based on the Cloud model. Generally a simpler representation model with less parameters usually means less computations and memory requirements in applications. Moreover, the comparison experiments with the recent EIA show that, our proposed method can not only obtain much thinner footprints of uncertainty (FOUs) but also capture sufficient uncertainties of words.

Evaluation Model of the Supporting Plate of the Steaming Bucket Based on Fuzzy Comprehensive Evaluation

To solve evaluation problem of the structure design of the supporting plate of the steaming Bucket, a evaluation method based on fuzzy comprehensive evaluation was presented for the Supporting Plate. Membership functions for the quantitative and qualitative indicators were built by using the fuzzy statistical test method and fuzzy distribution. On the basis, the evaluation model was built based on fuzzy comprehensive evaluation, each layer of which was evaluated respectively, and suggests the evaluation results of structure analysis of the supporting plate. The instance analysis shows that the method is reasonable and effective.

Research on Fuzzy Comprehensive Evaluation of Cable-Stayed Bridges

As bridge span increases, people have growing concern on bridge safety and durability. The fuzzy comprehensive evaluation was introduced to assess complicated cable-stayed bridges. The calculate approach of fuzzy comprehensive evaluation was introduced first. Using the representation proposed by Professor Zadeh, the membership degree of the bridge technique status was described. The membership function of comprehensive evaluation for cable-stayed bridges was established by fuzzy statistics method. The application problem of model in the comprehensive evaluation for cable-stayed bridges was discussed, and the model was established in the composite calculation procedure of fuzzy sets. The fuzzy comprehensive evaluation theory was applied in the evaluation of the Sifangtai Cable-stayed Bridge as an example and the final results was basically consistent with that of the uncertain AHP method. It can be concluded that the theory can apply to the comprehensive evaluation of cable-stayed bridges.

Credibility Measure and Assessment Method of Equipment Severity to Voltage Sag

In order to accurately describe the equipment’ severity caused by voltage sag, the credibility measure which meets the conditions of non-additive is proposed based on their physical properties of responses. This assessment measure can avoid the deficiencies that classical probability measure needs a large number of samples and the non-duality of fuzzy measure. The membership functions of sensitive equipment voltage tolerance capability that corresponding to the characteristic quantities in the status uncertain area was determined by fuzzy statistical method and polynomial fitting method. Then the joint credibility distribution function was deduced based on uncertainty theory. Hence, the assessment model of severity of equipment failure is constructed. Based on practical samples, the PCs were simulated using the proposed method. Comparing the simulation results with methods using classical probability measure and possibility measure prove that the proposed method is proper and credible and can reflect practical condition more objectively.

Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation

A secondary fuzzy comprehensive evaluation system is constructed to evaluate the risk of floor water invasion in coal mines. Four first-grade indices and 13 second-grade indices are determined based on the principles of scientificity, rationality, operability and representative by using fuzzy mathematics theory. Each index is quantitatively graded according to five risk grades using fuzzy statistical method and expert evaluation method, and the membership degree of every index is constructed. The weight of every index is rationally distributed by analytic hierarchy process (AHP). Evaluations of engineering practice are carried through with hydrogeological data of six mining faces in China. The satisfying evaluation results are consistent with engineering practice.

Credibility Measure and Its Assessment of Customer Equipment Failure Probability Due to Voltage Sag

In order to accurately describe the equipment’ severity caused by voltage sag, the credibility measure which meets the conditions of non-additive is proposed based on their physical properties of responses. This assessment measure can avoid the deficiencies that classical probability measure needs a large number of samples and the non-duality of fuzzy measure. The membership functions of sensitive equipment voltage tolerance capability that corresponding to the characteristic quantities in the status uncertain area was determined by fuzzy statistical method and polynomial fitting method. Then the joint credibility distribution function was deduced based on uncertainty theory. Hence, the assessment model of severity of equipment failure is constructed. Based on practical samples, the PCs were simulated using the proposed method. Comparing the simulation results with methods using classical probability measure and possibility measure prove that the proposed method is proper and credible and can reflect practical condition more objectively.

Green Building Economic Model and Empirical Evaluation

Based on the analysis of the economic evaluation of green building, taking references of 《Evaluation standards of green building》 (GB / T 50378-2006), indicators reflecting the economy of green building are selected through expert scoring method and fuzzy statistics method .Furthermore, a comprehensive evaluation model is established based on principle of fuzzy mathematics through the application of AHP aiming at determining the index weight. All above is to provide a wider perspective for the economic evaluation of green building.

Assessment System about the Ecosystem Water Based on AHP-FPP

According to characteristics about the ecosystem water，the ecosystem water level assessment index system is structured. We put forward Fuzzy Statistics method to quantify the qualitative indexes in the system, using Analytic Hierarchy Process(AHP) to determine the weight of each hierarchy in the system, adopting Fuzzy Preference Process(FPP) to assess the ecosystem water level. The final conclusion of the example indicates that fuzzy comprehension assessment method can reflect utilization water characteristic in different areas and make reasonable comprehension assessment, also show that the method is practical.

Calculating the reliability of shafts with probability and possibility variables in the limiting-state model

A new approach is proposed in calculating the reliability of shafts in any mechanical systems. In this approach, the basic parameters in the mathematical model of the limiting state are a combination of random and fuzzy variables, when probabilistic and statistical methods cannot be used for reliability calculation.

Merging fuzzy statistical data with imprecise prior information

Solving complex decision problems requires the usage of information from different sources. Usually this information is uncertain and statistical or probabilistic methods are needed for its processing. However, in many cases a decision maker faces not only uncertainty of a random nature but also imprecision in the description of input data that is rather of linguistic nature. Therefore, there is a need to merge uncertainties of both types into one mathematical model. In the paper we present methodology of merging information from imprecisely reported statistical data and imprecisely formulated fuzzy prior information. Moreover, we also consider the case of imprecisely defined loss functions. The proposed methodology may be considered as the application of fuzzy statistical methods for the decision making in the systems analysis.

Interpreting patterns and analysis of acute leukemia gene expression data by multivariate fuzzy statistical analysis

DNA microarray technologies, which monitor simultaneously, the expression pattern of thousands of individual genes in different biological systems have resulted in a tremendous increase of the amount of available gene expression data and have provided new insights into gene expression during development, within disease processes, and across species. However, microarray gene expression data are characterized by very high dimensionality (genes), relatively small numbers of samples (observations), irrelevant features, as well as collinear and multivariate characteristics. These features complicate the interpretation and analysis of microarray data, and the complexity of such data means that its analysis entails a high computational cost. This situation motivated the researchers to develop a new method for analyzing microarray data. In this paper, we propose a simple gene selection and multivariate fuzzy statistical analysis methods. The proposed method was applied to microarray data from leukemia patients; specifically, it was used to interpret the gene expression pattern and analyze the leukemia subtype whose expression profiles correlated with four cases of acute leukemia gene expression.