Evaluaton model for the geometry complexity of casting based on fuzzy theory

The parameters that describe the complex degree of a certain casting are of some uncertainty. Therefore, a new method based on the fuzzy theory to classify the complex degree of castings has been presented in this paper. The feasibility of fuzzy theory in describing the complex degree of castings has been discussed and the procedure of this method has been specified by analyzing the complex degrees of some typical castings. The element factors that influence the casting complexity, have been summarized, which include the wall-thickness and the number of transition surface, etc. The results show that it is reasonable and practicable to classify the complex degree of castings with the fuzzy theory.

Evaluation of Home Elevator Performance Based on Extension Fuzzy Theory

It is quite difficult as to how to choose an appropriate home elevator, because the factories manufacturing home elevator are numerous and the models of production are different. Therefore, this article combines .fuzzy math with extension theory on the basis of matter element theory, extension set theory and correlation function, constructs a classical matter element and a segmentfield matter element by classifying home elevator performance and making a performance index membership zero dimension, and establishes an extension fuzzy evaluation model of home elevator performance levels. The example in this article shows that the established method is able to evaluate actual home elevator performance.

Confidence Level of System Spares OptimizationUsing Fuzzy Theory

To obtain a higher readiness for a complex system, the common method is to store some spares. Confidence level of system spares is an important parameter to control the probability of the spares required. By introducing fuzzy theory, this paper allocates the confidence level of system spares to its subsystems, thus to achieve a rational management of system spares,

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.

Comprehensive Evaluation of Modern Enterprise Image with Theory of Fuzzy Mathematics

The multi layered indexes for modern enterprise images are summarized to overcome the shortness of single layered ones in evaluating modern enterprise images. The relevant multi layered evaluation model and algorithm are proposed. As an example, an electrical appliance enterprise in Qingdao city is evaluated with the proposed model and evaluation indexes to show the reasonability of the proposed indexes.

Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and wind.Energy resources are vital for all countries in terms of their economies and politics.As a result,selecting the optimal option for any country is critical in terms of energy investments.Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming.In the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous data.This study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp numbers.The hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective characteristics.The best-suited renewable energy alternative is discovered using the approach presented.

A BENCHMARK EXERCISE ON FUZZY SET THEORY BASED EXPERT JUDGEMENT TECHNIQUE

It is sometimes impossible to make a correct decision in a certain engineering task without the help from professional expert judgments. Even though there are different expert opinions available, however, they should be appropriately aggregated to a useful form for making an acceptable engineering decision. This paper proposed a technique which utilizes the fuzzy set theory in the aggregation of expert judgments. In the technique, two main key concepts are employed: linguistic variables and fuzzy numbers. Linguistic variables first represent the relative importance of evaluation criteria under consideration and the degree of confidence on each expert perceived by the decision maker, and then are replaced by suitable triangular fuzzy numbers for arithmetic manipulation. As a benchmark problem, the pressure increment in the containment of Sequoyah nuclear power plant due to reactor vessel breach was estimated to verify and validate the proposed technique.

Fuzzy stochastic damage mechanics(FSDM) based on fuzzy auto-adaptive control theory

In order to fully interpret and describe damage mechanics, the origin and development of fuzzy stochastic damage mechanics were introduced based on the analysis of the harmony of damage, probability, and fuzzy membership in the interval of [0,1]. In a complete normed linear space, it was proven that a generalized damage field can be simulated through β probability distribution. Three kinds of fuzzy behaviors of damage variables were formulated and explained through analysis of the generalized uncertainty of damage variables and the establishment of a fuzzy functional expression. Corresponding fuzzy mapping distributions, namely, the half-depressed distribution, swing distribution, and combined swing distribution, which can simulate varying fuzzy evolution in diverse stochastic damage situations, were set up. Furthermore, through demonstration of the generalized probabilistic characteristics of damage variables, the cumulative distribution function and probability density function of fuzzy stochastic damage variables, which show β probability distribution, were modified according to the expansion principle. The three-dimensional fuzzy stochastic damage mechanical behaviors of the Longtan rolled-concrete dam were examined with the self-developed fuzzy stochastic damage finite element program. The statistical correlation and non-normality of random field parameters were considered comprehensively in the fuzzy stochastic damage model described in this paper. The results show that an initial damage field based on the comprehensive statistical evaluation helps to avoid many difficulties in the establishment of experiments and numerical algorithms for damage mechanics analysis.

A Modified Comprehensive Evaluation System of Groundwater Pollution Based on Fuzzy Set Theory

A modified comprehensive evaluation system of groundwater pollution based on Fuzzy set theory is introduced.In this evaluation system,a five-degree membership function and a comprehensive weight function are built by combining Delphi method with double weight method.By studying a typical engineering project,the features and advantages of the modified evaluation system are analyzed by comparing to the popular simple comparison method.This indicates that the weighted average model is applicable in the situation that the content of every evaluation factor is even and the evaluation aim is to externalize the contribution of every evaluation factor in groundwater environmental quality.

Big Data Audit of Banks Based on Fuzzy Set Theory to Evaluate Risk Level

The arrival of big data era has brought new opportunities and challenges to the development of various industries in China.The explosive growth of commercial bank data has brought great pressure on internal audit.The key audit of key products limited to key business areas can no longer meet the needs.It is difficult to find abnormal and exceptional risks only by sampling analysis and static analysis.Exploring the organic integration and business processing methods between big data and bank internal audit,Internal audit work can protect the stable and sustainable development of banks under the new situation.Therefore,based on fuzzy set theory,this paper determines the membership degree of audit data through membership function,and judges the risk level of audit data,and builds a risk level evaluation system.The main features of this paper are as follows.First,it analyzes the necessity of transformation of the bank auditing in the big data environment.The second is to combine the determination of the membership function in the fuzzy set theory with the bank audit analysis,and use the model to calculate the corresponding parameters,thus establishing a risk level assessment system.The third is to propose audit risk assessment recommendations,hoping to help bank audit risk management in the big data environment.There are some shortcomings in this paper.First,the amount of data acquired is not large enough.Second,due to the lack of author’knowledge,there are still some deficiencies in the analysis of audit risk of commercial banks.

Evaluation of the maintenance window scheme using fuzzy soft set theory

The maintenance window scheme(MWS) is one of the most important railway transportation organizational plans and plays an important role in ensuring railway operational safety. However, MWS setting is a very complicated process, and most countries currently do so with the help of a computer-aided decision system. In general, a decision system can generate multiple alternatives for MWS within an acceptable time. Therefore, how to choose the best option from the alternatives is a vital decision. This paper presents a novel framework for MWS evaluation based on the Chinese railway system. Specifically, the requirements of each department related to MWS setting are analysed, and we construct an evaluation indicator system for MWS based on the preferences of different departments. Then, we apply the fuzzy soft set theory to MWS evaluation, a method that not only effectively deals with evaluation of uncertain information, but also gives flexibility for experts to input their subjective judgment.Additionally, using the ‘‘AND’’ operation of soft set theory allows combing evaluation information from multiple evaluators to give comprehensive results. Finally, a case study illustrates the proposed framework, showing that the proposed evaluation indicator system and evaluation method are effective and practical.

Rough Set Theory over Fuzzy Lattices

Rough set theory, proposed by Pawlak in 1982, is a tool for dealing with uncertainty and vagueness aspects of knowledge model. The main idea of rough sets corresponds to the lower and upper approximations based on equivalence relations. This paper studies the rough set and its extension. In our talk, we present a linear algebra approach to rough set and its extension, give an equivalent definition of the lower and upper approximations of rough set based on the characteristic function of sets, and then we explain the lower and upper approximations as the colinear map and linear map of sets, respectively. Finally, we define the rough sets over fuzzy lattices, which cover the rough set and fuzzy rough set,and the independent axiomatic systems are constructed to characterize the lower and upper approximations of rough set over fuzzy lattices,respectively,based on inner and outer products. The axiomatic systems unify the axiomization of Pawlak’s rough sets and fuzzy rough sets.

An evaluation method of contribution rate based on fuzzy Bayesian networks for equipment system-of-systems architecture

The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.

Research on the Algorithm of Avionic Device Fault Diagnosis Based on Fuzzy Expert System

Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.

Spherical Fuzzy WASPAS-based Entropy Objective Weighting for International Payment Method Selection

In international trade,exporters prefer to receive payments as quickly as possible,and importers want to make payments as late as possible.In this respect,the payment field,an essential condition for trade transactions,also represents the positions of exporters and importers conflict.In addition,there are many cases in which various variables must be considered rather than only one specific variable representatively affecting payment,particularly in the case of import-export Small and Medium-Sized Enterprises(SMEs)from emerging countries.A selection of proper payment methods can be categorized as a Multi-Criteria Decision-Making(MCDM)issue.Therefore,this study aims to propose a novel and efficient Spherical Fuzzy Weighted Aggregated Sum Product Assessment based Entropy Objective Weighting method(SF-EW and WASPAS-SF)to evaluate international payment methods with uncertain information.First,SF-EW model is applied to determine the relative weights of critical factors.Second,international payment method alternatives are prioritized by the WASPAS-SF approach.Five essential factors for four international payment methods are proposed based on experts’opinions and the existing literature.A real-world case study from Vietnamese import-export SMEs is presented to validate the applicability of the proposed framework.The results indicated that“Characteristics of payment method(PA)”had the most significant impact on international payment method selection.In comparison,“Letters of Credit(L/C)”was the most reliable payment method with the highest ranking available to international traders.Furthermore,a sensitivity analysis was performed to examine the validity and robustness of the proposed decision support model.Consequently,this study could contribute to international payment services and in the context of globalization and international trade.

Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain.Open Banking(OB)is one of the most important milestones since the beginning of financial technology innovation and service supply chain.As these are activities provided by traditional banks,non-bank financial institutions also provide financial service with access to consumer banking,transactional and other financial data to develop financial applications and services tailored to their customers.The development of financial technology,“Open banking”,promotes financial services to begin this transformation.However,evaluating and selecting open banking business partners from multiple perspectives for banks are underexplored.Thus,the authors in this research proposed a hybrid multicriteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process(SF-AHP)model and a Multi-Attributive Ideal-Real Comparative Analysis(MAIRCA)model with supports from seasoned domain experts.The contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business partners.The model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.

Fuzzy Multi-Criteria Decision Making for Solar Power Plant Location Selection

Vietnam is one of Southeast Asian countries with a rapid GDP growth rate,ranging from 6.5%to 7%annually,leading to an average increase in energy demand of 11%per year.This demand creates many new opportunities in the energy industry,especially renewable energy,to ensure sustainable development in the future for the country with applications of solar energy growing at the present,and other opportunities to expand in the future.In Vietnam,thanks to favorable weather,climate,terrain characteristics and many preferential support policies,there are many great opportunities in the field of solar energy exploitation and application.Location selection is an important problem in all renewable energy projects.Therefore,the author proposed a fuzzy Multi-criteria Decision-Making Model(MCDM)model for solar power plant location selection in this study,and as a result,location 5 is the optimal solution.The contribution of this study is to propose a MCDM for solar power plant location selection in Vietnam under fuzzy environmental conditions.

Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain

Fertilizer industry in Vietnam and globally have entered the saturation phase.With the growth rate slowing down,this poses challenges for the development impetus of the fertilizer industry in the next period.In fact,over the past few decades,Vietnam’s crop industry has abused excessive investment in chemical fertilizers,with organic fertilizers are rarely used or not at all,limiting crop productivity,increasing pests and diseases.To develop sustainable agriculture,Vietnam’s crop industry must limit the use of chemical fertilizers,increase the use of environmentally friendly organic and natural mineral fertilizers to produce clean agricultural products which is safe.Therefore,it is necessary to consider and choose the right supplier to ensure the goal of sustainable development.Spherical Fuzzy Analytic Hierarchy Process(SF-AHP),and the combinative distance-based assessment(CODAS)are new Multicriteria Decision Making(MCDM)method which can be used to solve supplier selection problem.This paper uses an effective solution based on a combined the concept of triple bottom line(TBL),SF-AHP and CODAS approach to help agriculture companies that need to select the best fertilizer supplier.This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs,but also develop sustainable agriculture.

Fuzzy MCDM Model for Selection of Infectious Waste Management Contractors

Healthcare supply chains are under pressure to drive down costs because of digital business,shifting customer needs and new competition.Medical waste generated from medical facilities includes medical activities and daily-life activities of patients and their family members.According to statistics of the Department of Health EnvironmentalManagement,Vietnam currently has more than 13,500 medical facilities,including hospitals from central to provincial and district levels and private hospitals and medical facilities.Preventive medicine generates about 590 tons of medical waste/day and is estimated to be about 800 tons/day.Medical waste includes ordinary medical waste and hazardous medical waste;in which ordinary medical waste accounts for about 80%–90%,only about 10%–20%is hazardous medical waste including infectious waste and non-infectious hazardous waste.This is an environmental and occupational health issue that needs attention in developing countries like Vietnam.Handling large amounts of medical waste to ensure environmental and personal hygiene,doing so inefficiently creates potential hazards to the environment and increases operating costs.However,hospitals lack objective criteria and methods to evaluate and select the most optimal infectious medical waste,relying instead on their own subjective assessment and prior experience.Therefore,the author proposed a fuzzy multicriteria decision making(MCDM)model including Fuzzy Analytic hierarchy process(FAHP)and the Weighted Aggregated Sum-Product Assessment(WASPAS)for infectious medical waste contractors’selection in this research.The proposed Fuzzy MCDM method is in-tended to provide a more efficient,accurate method in the selection of infectious medical waste contractors than subjective assessment methods,thus reduce potential risks to hospitals.The results of this study can be applied to evaluate and select contractors in other industries.

Fuzzy Multi-criteria Decision Making for Decision Support in Port Capacity Upgrade

In many port capacity upgrade projects,choosing a supplier of equipment is a complicated decision,project managers must consider many criteria to choose a supplier to ensure the project is completed on time,optimal in terms of benefit and cost.Therefore,selecting the equipment supplier in this project is a multi-criteria decision-making process.The multicriteria decision-making(MCDM)model is applied in many fields to select the optimal solution,but there are very few studies using the MCDM model to support project managers in evaluating and selecting optimal solutions in port capacity upgrade project.In this research,the authors combine Fuzzy Analytic Network Process model and Weighted Aggregated Sum Product Assessment concepts to develop a decision support system in port capacity upgrade project.The scientific and practical contribution of this study is to successfully propose a decision support model in a fuzzy environment.The results of the study will be a useful guideline to assist decision makers in port capacity upgrading projects in Taiwan as well as in other countries around the world.