Dynamic Analysis of Customer Demand Based on Intuitionistic Fuzzy Number in Product Planning

To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.

Application of entropy-based fuzzy matter-element analysis in seepage monitoring of RCC dam

Taking account of the fuzzy results of the seepage monitoring analysis of roller compacted concrete(RCC)dam and uncertainties of the individual indicator evaluation,the fuzzy matter-element model of seepage monitoring of RCC dam analysis has been established with the use of the fuzzy matter-element analysis theory and the concept of euclid approach degree.The use of entropy theory can calculate the weighting factor through the disorder utility values of the information reflected by the data itself,which can effectively avoid the problems of weight distribution and uncertainties of subjective judgments of the seepage monitoring analysis of roller compacted concrete dam.And further the example shows that the analysis of entropy-based fuzzy matter-element analysis model of the seepage monitoring of roller compacted concrete dam is in accordance with the actual situation,which verifies the effectiveness of the method.

Fuzzy cluster analysis of water mass in the western Taiwan Strait in spring 2019

The classification of the springtime water mass has an important influence on the hydrography,regional climate change and fishery in the Taiwan Strait.Based on 58 stations of CTD profiling data collected in the western and southwestern Taiwan Strait during the spring cruise of 2019,we analyze the spatial distributions of temperature(T)and salinity(S)in the investigation area.Then by using the fuzzy cluster method combined with the T-S similarity number,we classify the investigation area into 5 water masses:the Minzhe Coastal Water(MZCW),the Taiwan Strait Mixed Water(TSMW),the South China Sea Surface Water(SCSSW),the South China Sea Subsurface Water(SCSUW)and the Kuroshio Branch Water(KBW).The MZCW appears in the near surface layer along the western coast of Taiwan Strait,showing low-salinity(<32.0)tongues near the Minjiang River Estuary and the Xiamen Bay mouth.The TSMW covers most upper layer of the investigation area.The SCSSW is mainly distributed in the upper layer of the southwestern Taiwan Strait,beneath which is the SCSUW.The KBW is a high temperature(core value of 26.36℃)and high salinity(core value of 34.62)water mass located southeast of the Taiwan Bank and partially in the central Taiwan Strait.

Integrated classification method of tight sandstone reservoir based on principal component analysise simulated annealing genetic algorithmefuzzy cluster means

In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tight sandstone reservoirs which lack the prior information and core experiments.A variety of evaluation parameters were selected,including lithology characteristic parameters,poro-permeability quality characteristic parameters,engineering quality characteristic parameters,and pore structure characteristic parameters.The PCA was used to reduce the dimension of the evaluation pa-rameters,and the low-dimensional data was used as input.The unsupervised reservoir classification of tight sandstone reservoir was carried out by the SAGA-FCM,the characteristics of reservoir at different categories were analyzed and compared with the lithological profiles.The analysis results of numerical simulation and actual logging data show that:1)compared with FCM algorithm,SAGA-FCM has stronger stability and higher accuracy;2)the proposed method can cluster the reservoir flexibly and effectively according to the degree of membership;3)the results of reservoir integrated classification match well with the lithologic profle,which demonstrates the reliability of the classification method.

New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory

The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method.It also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow implication.Thismethodology can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic zone.The Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara differentiability.According to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in detail.The illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are known.Based on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.

Evaluation on Urban Land Ecological Security Based on the PSR Model and Matter-Element Analysis: A Case Study of Zhuhai, Guangdong, China

As one of the Special Economic Zones since the reform and opening up, Zhuhai has developed during the past 30 years. Its economic development, industrial structure and ecological environment have undergone great changes. Research on changes in Zhuhai’s land ecological security is of great significance. Using relevant data from 2007-2012, this study established a land ecological security assessment system based on the PSR conceptual framework model. The system contained 18 indicators from 3 aspects according to the concrete features of Zhuhai. Then we used the matterelement analysis and the improved entropy weight to analyze and evaluate the land ecological security of Zhuhai. The results showed that: from 2007 to 2012, the levels of the land ecological security of Zhuhai were “secure”, and the value increased year by year;as the land ecological security response value increased, Zhuhai was capable of solving land ecosystem problems. However, it should be noted that the structure of land ecosystem in Zhuhai has not formed and that rapid expansion of construction land has caused the shortage of cultivated land and other issues. Measures should be taken to control the construction area, improve land intensive utilization and improve the land ecological security.

Evaluation of the Strategic Tolerance Human Resource Management Based on Matter-Element Analysis Method

The main features and connotation of the tolerance human resource management based on strategy are analyzed and summarized. The theory and method of systematic engineering is used to build the evaluation index systems for the tolerance human resource management. On the basis of it, by using the theory of matter-element analysis, the matter-element models are formulated for the evaluation of the tolerance human resource management. Regarding annual tolerance human resource management as the object of matter-dement, the tolerance human resource ：management for two years are analyzed and evaluated through using the matter. element models proposed. A ease study is carried out and the satisfactory results are obtained. A new scientific methed is provided for the evaluation of human resource management based on strategy.

Integrated Evaluation of Air Traffic Controller Workload Based on Matter-Element Analysis

A model for evaluating the controller workload was presented based on matter-element analysis, particularly from a mansystem engineering perspective. On the basis of a questionnaire survey, 18 kinds of indexes which influence the controller workload were determined. By establishing the classical field and node field of the controller workload, the correlation function of the controller workload grade was obtained; then the correlation degree and estimated grade of controller workload were given. A case study verifies the feasibility of the proposed evaluation method.

Expert Anti-Evaluation Model Based on Matter-Element Analysis in Fund Project Peer-Review System

The article analyses several key issues which restrict the effectiveness of fund project peer review work. It analyses the evaluating theory and matter-element theory to access the expert anti-evaluation model, and also studies the expert anti-evaluation index system to support the anti-evaluation method. The practical basis is the true score data of the experts which is collected from the actual anti-evaluation in Liaoning province science and technology fund project peer review system. With the practical experience of the actual project, we prove that the expert index system anti-evaluation model and expert anti-evaluation method can improve the fund project peer review work and play a positive role for the peer review work and also make the review work more scientific and more rational.

ESTIMATION METHOD FOR AIRCRAFT SIMILARITY BASED ON FUZZY THEORY AND GREY INCIDENCE ANALYSIS

An estimation method for aircraft similarity based on fuzzy theory and grey incidence analysis is presented. This estimation method is made up of the triangular fuzzy transforming model of linguistic variables and the method of grey incidence analysis. Nine feature attributes of aircraft are selected to estimate the similarity between the new aircraft and the existing aircraft. A new aircraft X and other six existing aircrafts are taken as examples. Analyses show that similarity estimation results obtained from the method are in accordance with practice.

FUZZY WITHIN-CLASS MATRIX PRINCIPAL COMPONENT ANALYSIS AND ITS APPLICATION TO FACE RECOGNITION

Matrix principal component analysis （MatPCA）, as an effective feature extraction method, can deal with the matrix pattern and the vector pattern. However, like PCA, MatPCA does not use the class information of samples. As a result, the extracted features cannot provide enough useful information for distinguishing pat- tern from one another, and further resulting in degradation of classification performance. To fullly use class in- formation of samples, a novel method, called the fuzzy within-class MatPCA （F-WMatPCA）is proposed. F-WMatPCA utilizes the fuzzy K-nearest neighbor method（FKNN） to fuzzify the class membership degrees of a training sample and then performs fuzzy MatPCA within these patterns having the same class label. Due to more class information is used in feature extraction, F-WMatPCA can intuitively improve the classification perfor- mance. Experimental results in face databases and some benchmark datasets show that F-WMatPCA is effective and competitive than MatPCA. The experimental analysis on face image databases indicates that F-WMatPCA im- proves the recognition accuracy and is more stable and robust in performing classification than the existing method of fuzzy-based F-Fisherfaces.

Stability analysis for affine fuzzy system based on fuzzy Lyapunov functions

An analysis method based on the fuzzy Lyapunov functions is presented to analyze the stability of the continuous affine fuzzy systems. First, a method is introduced to deal with the consequent part of the fuzzy local model. Thus, the stability analysis method of the homogeneous fuzzy system can be used for reference. Stability conditions are derived in terms of linear matrix inequalities based on the fuzzy Lyapunov functions and the modified common Lyapunov functions, respectively. The results demonstrate that the stability result based on the fuzzy Lyapunov functions is less conservative than that based on the modified common Lyapunov functions via numerical examples. Compared with the method which does not expand the consequent part, the proposed method is simpler but its feasible region is reduced. Finally, in order to expand the application of the fuzzy Lyapunov functions, the piecewise fuzzy Lyapunov function is proposed, which can be used to analyze the stability for triangular or trapezoidal membership functions and obtain the stability conditions. A numerical example validates the effectiveness of the proposed approach.

基于Fuzzy Matter-Element模型的电力上市公司财务核心竞争能力评价

鉴于电力上市公司财务核心竞争能力评价的复杂性以及单项指标评价结果的不相容性,本文在模糊物元分析的基础上,将熵权的理论方法与海明贴近度的概念相结合,建立了电力上市公司财务核心竞争能力评价的模糊物元模型。把不同电力企业作为物元的事物,以它们的各项评价指标及相应的模糊量值构造模糊物元,通过计算与理想模糊物元之间的海明贴近度,实现对上市电力公司财务核心竞争能力的综合评价。

基于VWM-GRA的新型Fuzzy-FMEA复杂装备风险评估方法

失效模式和影响分析(Failure Mode and Effect Analysis,FMEA)是一种识别和预防复杂装备潜在故障模式的风险评估方法,然而,现有FMEA方法采用等权重和精确数表征不确定情形下的风险因素评估信息,导致风险优先数(Risk Priority Number,RPN)难以准确评估复杂装备故障模式的风险优先级。针对这一难题,文中提出了一种基于变权方法-灰色关联分析(Variable Weight Method-Grey Relation Analysis,VWM-GRA)的新型Fuzzy-FMEA复杂装备风险评估方法。在风险因素权重分配方面,在模糊熵值法的基础上,考虑风险评估信息对风险因素权重的影响,构建风险因素变权综合模型以动态调整风险因素权重值,据此确定风险因素的客观变权重;在风险优先数排序方面,在模糊语言变量表征风险因素评估信息的基础上,考虑风险因素评估信息不确定性量化对故障模式排序精度的影响,构建故障模式模糊灰色关联分析模型,以获取评估信息数据序列间的相对关联度,据此评估故障模式的风险优先级。最后,通过航空发动机主轴轴承的故障模式风险实例,分析验证文中方法的有效性。案例分析表明:该方法能够有效解决不确定情形下准确评估复杂装备故障模式风险优先级的难题。

Assessment of gas and dust explosion in coal mines by means of fuzzy fault tree analysis

During the past decade, coal dust and gas explosions have been the most two serious types of disasters in China, threatening the lives of miners and causing significant losses in terms of national property. In this paper, an evaluation model of coal dust and gas explosions was constructed based on a fuzzy fault tree by taking the Xingli Coal Mine as a research site to identify the risk factors of coal dust and gas explosions.Furthermore, the hazards associated with such explosions were evaluated for this particular coal mine.After completing an on-site investigation, the fuzzy probabilities of basic events were obtained through expert scoring, and these expert opinions were then aggregated as trapezoidal fuzzy numbers to calculate the degrees of importance of all basic events. Finally, these degrees of importance were sorted. According to the resulting order, the basic events with higher probabilities were determined to identify key hazards in the daily safety management of this particular coal mine. Moreover, effective measures for preventing gas and coal dust explosions were derived. The fuzzy fault tree analysis method is of high significance in the analysis of accidental coal mine explosions and provides theoretical guidance for improving the efficiency of coal mine safety management in a scientific and feasible manner.

Fuzzy data envelopment analysis approach based on sample decision making units

The conventional data envelopment analysis （DEA） measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs typically have some levels of fuzziness. To analyze a decision making unit （DMU） with fuzzy input/output data, previous studies provided the fuzzy DEA model and proposed an associated evaluating approach. Nonetheless, numerous deficiencies must still be improved, including the α- cut approaches, types of fuzzy numbers, and ranking techniques. Moreover, a fuzzy sample DMU still cannot be evaluated for the Fuzzy DEA model. Therefore, this paper proposes a fuzzy DEA model based on sample decision making unit （FSDEA）. Five eval- uation approaches and the related algorithm and ranking methods are provided to test the fuzzy sample DMU of the FSDEA model. A numerical experiment is used to demonstrate and compare the results with those obtained using alternative approaches.

A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model

An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.

Risk analysis of extended reach wells in the Liuhua Oilfield,South China Sea,based on comprehensive fuzzy evaluation method

Drilling engineering has great uncertainty and it always involves huge investment and high risk. Risk analysis of extended reach drilling （ERD） is very important to prevent complex failures and to improve drilling efficiency. Nowadays there are few reports on how to analyze quantitatively the drilling risk for extended reach wells （ERWs）. Based on the fuzzy set theory, a comprehensive fuzzy evaluation model for analyzing risks of ERD is proposed in this paper. Well B6ERW07 is a planned 8,000-meter ERW with a high ratio of horizontal displacement （HD） to vertical depth （VD） in the Liuhua Oilfield, the South China Sea, China. On the basis of the evaluation model developed in this study, the risk for drilling Well B6ERW07 was evaluated before drilling. The evaluation result shows that the success rate of drilling this well is predicted to be 51.9%, providing important rational and scientific information for the decisionmakers.

Fuzzy Risk Analysis of Harbour Engineering Investment by Hierarchy System Approach

The present risk analysis model of engineering investment is built by fuzzy hierarchy approach under the assumption of maximizing the revenues of the project during its whole life cycle of operation. It can reasonably be expressed by a system evaluation analysis. As a matter of fact, the system, aimed by its system goal can be modelled by a set of factors, constitutively structured by certain links between them, to form a factorial network chart, which represents the essentials of the system behaviours, the nodes of which represent the factors concerned. The weight distribution between factors located at the same level can be determined by the eigen-value problem of a 'pair comparison' relation matrix. The weight distribution of factors at each level is successively manipulated until the fuzzy synthetic risk assessment. As an example of risk analysis of engineering investment, a harbour construction project is presented for illustration.

Evaluation model of venture investment based on fuzzy matter-element method of combined weight

An evaluation model of an international venture investment project on the basis of fuzzy matter-element and combined weight methods is introduced. First, the compound fuzzy matter-element of optimal subordinate degree is constructed on the principle of the bigger-more-optimal or the less-more-optimal depending on the actual evaluation indicators, and combined with standard fuzzy matter-element to form a difference-square fuzzy matter-element. Secondly, a combined weight is calculated by both information entropy and the expert grading method. Finally, the compound fuzzy matter-element of Euclidian approach degree by M(·,+)method is constituted and used to classify venture investment projects. Based on the model above, six venture investment projects in a company are evaluated, and the results show that the projects are all good, which is demonstrated by the good income of the projects. Therefore, the coincidence of evaluation results and actual operation status indicates that the model is of great value in practical application.