Fuzzy Decision of Ground Improvement Method

With the rapid development of expressway in China, the ground improvement is becoming more and more important. The decision of the ground improvement method often depends on the experience of an engineer. This paper sets up a module of multi-level fuzzy decision of the ground improvement method in the expressway construction which is mainly to set up multi-level structure module, to get value of the affected factors at rule level and index level, to set up the character index matrix of project level and to have a total evaluation on the projects. Combined with the project of ground improvement on the Second Cincture Road in Wuhan, a case study is carried out with satisfactory results.

Research on Fuzzy Decision of Resources Selection in Job-sh op Scheduling for a One-of-a-Kind and Order-Oriented Production System

In a one-of-a-kind and order-orient ed production corporation, job shop scheduling plays an important role in the prod uction planning system and production process control. Since resource selection in job shop scheduling directly influences the qualities and due dates of produc ts and production cost, it is indispensable to take resource selection into acco unt during job shop scheduling. By analyzing the relative characteristics of res ources, an approach of fuzzy decision is proposed for resource selection. Finall y, issues in the application of the approach are discussed.

Study on Fuzzy Decision for Purchasing Spare Parts for Machinery Equipment

For purchasing spare parts for machinery products, the general principle, procedure and method are put forward in the paper. Fuzzy theory and method are applied to set up a decisive model for purchasing spare parts. By working out the kinds and quantities of spare parts, the purchase of parts is provided with scientific decision.

Method for triangular fuzzy multiple attribute decision making based on two-dimensional density operator method

Aiming at the triangular fuzzy(TF)multi-attribute decision making(MADM)problem with a preference for the distribution density of attribute(DDA),a decision making method with TF number two-dimensional density(TFTD)operator is proposed based on the density operator theory for the decision maker(DM).Firstly,a simple TF vector clustering method is proposed,which considers the feature of TF number and the geometric distance of vectors.Secondly,the least deviation sum of squares method is used in the program model to obtain the density weight vector.Then,two TFTD operators are defined,and the MADM method based on the TFTD operator is proposed.Finally,a numerical example is given to illustrate the superiority of this method,which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.

Governance of artificial intelligence applications in a business audit via a fusion fuzzy multiple rule‑based decision‑making model

A broad range of companies around the world has welcomed artificial intelligence(AI)technology in daily practices because it provides decision-makers with comprehensive and intuitive messages about their operations and assists them in formulating appropriate strategies without any hysteresis.This research identifies the essential components of AI applications under an internal audit framework and provides an appropriate direction of strategies,which relate to setting up a priority on alternatives with multiple dimensions/criteria involvement that need to further consider the interconnected and intertwined relationships among them so as to reach a suitable judgment.To obtain this goal and inspired by a model ensemble,we introduce an innovative fuzzy multiple rule-based decision making framework that integrates soft computing,fuzzy set theory,and a multi-attribute decision making algorithm.The results display that the order of priority in improvement—(A)AI application strategy,(B)AI governance,(D)the human factor,and(C)data infrastructure and data quality—is based on the magnitude of their impact.This dynamically enhances the implementation of an AI-driven internal audit framework as well as responds to the strong rise of the big data environment.Highlights Artificial intelligence(AI)promotes the sustainability development of audit tasks.A fuzzy MRDM model extracts key factors from large amounts of data.Fuzzy decision-making trial and evaluation laboratory analysis accounts for dependence and feedback among factors.An effective framework of AI-driven business audit is proposed in which“AI cognition of senior executives”is the most important criterion.

Both-branch fuzzy decision and decision encryptionauthentication

This paper is on fuzzy decision theory and information security theory which are mutually independent and engrafted. This paper presents both-branch fuzzy decision and problems on decision encryption-authentication, puts forward two kinds of both-branch fuzzy decision on X: both-branch fuzzy decision on X having bounded domains X = X+∩X- ={x0}, both-branch fuzzy decision on X havingoverlapping domains X* = X+∩X- = {x_1~*,x_2~*,…,x_1~*}. It presents single branch separate-separate out theoremof both-branch fuzzy decision on X, single branch superposition theorem of both-branch fuzzy decision, exclusive-decompose principle of both-branch fuzzy decision. This paper presents encryption-authentication theorem of decision by engrafting information security theory and technique with both-branch fuzzy decision, and provides encryption-decryption and signature-authentication of both-branch fuzzy decision.

A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps

In the aluminum reduction process, aluminum uoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic ef ciency. Making the decision on the amount of AlF3 addi- tion (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into con- sideration a variety of interrelated functions;in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is dif cult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have dif culty covering these complex causalities. In this work, a data and knowl- edge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy deci- sion trees, which are used to amend the initial structure provided by experts. The state transition algo- rithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA.

Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

Tri-Intersectional Model of Leadership by Values:A Fuzzy Multi-Criteria Decision Making Open Technology Assessment System

Purpose-Nowadays successful organizations need to be masters at leadership by values to play in a constantly changing and transforming environment.But how can leaders and organizations effectively convene strategic and culture development based on values?This paper presents the Tri-Intersectional Model of Leadership by Values(TMLV)in which leaders and organizations can integrate a sustainable strategy,as well as a culture and value-based management system that simultaneously leverages human,financial,and social resources.With its three essential axes of values(economic-pragmatic,emotional-development,and ethical-social)at their intersection points,it allows leaders to focus on the strategy linkages:innovation-intersection between the economic-pragmatic values axis and the emotional-development values axis-allows them to develop sustainable innovations;survival-intersection between the economic-pragmatic values axis and the ethical-social values axis-enhances their organization’s survival;finally,sensibility-intersection between the economic-pragmatic values axis and the ethical-social values axis-makes them more humane and more socially-responsible.The application of the TMLV,using the Fuzzy Multi-Criteria Decision Making Open Technology Assessment System,can be a great inspiration for stimulating and working with values in organizations,as well as allowing leaders to develop a values-based,high-involvement,and performance-oriented culture.Methodology/Approach-This research considers empirical data analysis of the 37 case studies of the EU-InnovatE project(http//www.euinnovate.com)-a pioneering initiative to align innovation values to integrate the end user into the process of innovation and entrepreneurship related to a sustainable lifestyle and the green economy in Europe-using a fuzzy multiple-criteria decision making method and open technologies system,such as server-side PHP language,MariaDB Database,fork of MYSQL Database Management System,and JavaScript libraries to perform operation directly on the user’s browser.Findings-The application of the TMLV model,considering empirical analysis of the extracted values from the case studies,using the Fuzzy Multi-Criteria Decision Making Open Technology Assessment System,can be a great inspiration for stimulating and working with values in João organizations,as well as allowing leaders to develop suitable strategies and interventions for shaping a sustainable high-performance culture.Research implications-This research can be a starting point for further research to assess the effectiveness of the leadership model based on a decision-making open technology system in any given organization,as well as to invite researchers who have positive passion about working with values to participate in the improvement of this tool.Originality/value-The Tri-Intersectional Model of Leadership by Values using the Fuzzy Multi-Criteria Decision Making Open Technology Assessment System is presented as an evolution in leadership models that may be used to fuel innovation,survival,and a sensibility strategic focus that is necessary to optimize human and organizational performance and deliver effective solutions to the massive array of human,financial,and social problems we face today.

Fuzzy Consistent Relation and Decision Making

This paper presents a kind of fuzzy consistent relation, discusses its main properties - center-division transitivity, describes its combined operation. At the same time, introduce the applications of fuzzy consistent relation in decision making.

GEAR POSITION DECISION METHOD OF AUTOMATED MECHANICAL TRANSMISSION BASED ON FUZZY INFERENCE

A gear position decision method used in automated mechanical transmission is introduced. The algorithm of the mechod is composed of a driving environment and driver's intention estimator, the shift schedules suit for each typical driving environment and driver's intention situation, and an inference ligic to determine the most proper gear position for the present situation. The estimator identifies the driving environment and driver's intention features which are divided into some typical models. Based on the identified results, the algorithm works out the best gear position. It just simulates the course of driver's making gear position decision when driving a automobile with manual transmission. The test results show that the automated mechanical transmission with the method gives less unnecessary shifting and more proper gear position than common shift schedules.

A Fuzzy Sequential Optimization Method for the Antenna Structures with Multiple Objectives

This paper presents a fuzzy sequential optimization method for the antenna structures with multiple objectives (structural displacement, weight, cost, nature frequency characteristic) based on fuzzy sets. This has led to a set of new concepts which are discussed here. The paper establishes a sequential optimization model, in which the cost function is constructed, the membership function of single objective is defined as extended quadratic function, the membership function in decision making is constructed with linearly weighted and power product weighted models and the objectives are classed. In addition, the paper presents two methods, namely the linear extended method and the secondary constrained sequential optimization method, by which effective satisfactory design can be found. A computer program is given, optimization computing of the truss- type and antenna structures are described. It is shown that the method is practical and effective.

Ranking Method for Complementary Judgment Matrixes with Fuzzy Numbers Based on Hausdorff Metric Distance

A method for ranking complementary judgment matrixes with traspezoidal fuzzy numbers based on Hausdorff metric distance and fuzzy compromise decision approach is proposed. With regard to fuzzy number complementary judgment matrixes given by a decider group whose members have various weights, the expert＇s information was aggregated first by means of simple weight average（SWA） method and Bonissone calculational method. Hence a matrix including all the experts＇ preference information was got. Then the matrix＇ column members were added up and the fuzzy evaluation values of the alternatives were got. Lastly, the Hausdorff metric distance and fuzzy compromise decision approach were used to rank the fuzzy evaluation values and then the ranking values of all the alternatives were got. Because exact numbers and triangular fuzzy numbers could all be transformed into trapezoidal fuzzy numbers, the method developed can rank complementary judgment matrixes with trapezoidal fuzzy numbers, triangular fuzzy numbers and exact numbers as well. An illustrative example is also given to verify the developed method and to demonstrate its feasibility and practicality.

Fuzzy distances based FMAGDM compromise ratio method and application

An extended compromise ratio method（CRM） based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes are expressed with values of linguistic variables parameterized using triangular fuzzy numbers.A compromise solution is determined by introducing the ranking index based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible simultaneously.This proposed method is compared with other existing methods to show its feasibility and effectiveness and illustrated with an example of the military route selection problem as one of the possible applications.

Research and Application of Maintenance Decision Method of Complex Equipment in Nuclear Power Plant

The determination of maintenance mode of complex equipment in nuclear power plant is an essential work for reliability analysis and maintenance decision. Currently, the main decision method of maintenance mode is reliability centered maintenance( RCM) logic decision-making process, but the process is a qualitative analysis process. Based on a comprehensive analysis of factors affecting equipment reliability and maintenance work, it adopts a fuzzy synthesis decision method to establish a maintenance decision model,which uses the maximum subordination principle and expert assessment method to determine the maintenance mode of complex equipment. Combined with a concrete example of generators in nuclear power plant,a description of maintenance decision method was proposed in the application of complex equipment. The research shows that the method is feasible and reliable.

Internet of Things Enabled Intelligent Energy Management and Control System for Heavy Equipment Industrial Park and Fuzzy Assessment of Its Schemes

In order to solve the problems of poor informationflow,low energy utilization rate and energy consumption data reuse in the heavy equipment industrial park,the Internet of Things(IoT)technology is applied to construct the intelligent energy management and control system(IEMCS).The application architecture and function module planning are analyzed and designed.Furthermore,the IEMCS scheme is not unique due to the fuzziness of customer demand and the understanding deviation of designer to customer demand in the design stage.Scheme assessment is of great significance for the normal subsequent implementation of the system.A fuzzy assessment method for IEMCS scheme alternatives is proposed to achieve scheme selection.Fuzzy group decision using triangular fuzzy number to express the vague assessment of experts is adopted to determine the index value.TOPSIS is modified by replacing Euclidean distance with contact vector distance in IEMCS scheme alternative assessment.An experiment with eight IEMCS scheme alternatives in a heavy equipment industrial park is given for the validation.The experiment result shows that eight IEMCS scheme alternatives can be assessed.Through the comparisons with other methods,the reliability of the results obtained by the proposed method is discussed.

Application of Intuitionistic Z-Numbers in Supplier Selection

Intuitionistic fuzzy numbers incorporate the membership and non-membership degrees.In contrast,Z-numbers consist of restriction components,with the existence of a reliability component describing the degree of certainty for the restriction.The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers,namely intuitionistic Z-numbers(IZN).The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are charac-terized by the membership and non-membership functions,exhibiting the degree of the hesitancy of decision-makers.This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.A decision-making model is proposed using the trapezoidal intuitionistic fuzzy power ordered weighted average as the aggregation function and the ranking function to rank the alternatives.The proposed model is then implemented in a supplier selection problem.The obtained ranking is compared to the existing models based on Z-numbers.The results show that the ranking order is slightly different from the existing models.Sensitivity analysis is performed to validate the obtained ranking.The sensitivity analysis result shows that the best supplier is obtained using the proposed model with 80%to 100%consistency despite the drastic change of criteria weights.Intuitionistic Z-numbers play a very important role in describing the uncertainty in the decision makers’opinions in solving decision-making problems.

Research on the Construction of Evaluation Model for the Development of Biopharmaceutical Park in China

Objective To study the influencing factors on the development of biopharmaceutical park,and to construct an evaluation model of the influencing factors for biopharmaceutical park in China.Methods By analyzing various factors affecting biopharmaceutical parks,an evaluation index system of biopharmaceutical parks and an evaluation model of influencing factors of biopharmaceutical park development based on fuzzy group decision making were established.Results and Conclusion Factors such as research and development(R&D)funding investment,incentive for transformation of scientific and technological achievements,and industrial clusters have a greater impact on the development of biopharmaceutical industrial parks in China.Local governments should increase the investment in R&D funding.Besides,they should pay attention to the incentive of transformation of scientific and technological achievements to improve the innovation ability of enterprises.Meanwhile,they should promote the clustering of high-tech enterprises to comprehensively enhance the healthy development of biopharmaceutical parks in China.

Study on an Configuration Framework for Product Family

In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuration method based on constraints and fuzzy decision for product family. The configuration method is evolved from constraint based product configuration. It employs fuzzy optimum selection in the reasoning process, which can select similar components when customers’ requirements can not be met precisely. In the configurator, product family is represented with GBOM(Generic Bill Of Material) and ACL(Article Characteristic List). Every node of GBOM has an ACL to list all instances of a component family. Constraints are attached to every node, which involves variable definition and constraints definition. In the reasoning process, constraint satisfaction and fuzzy optimum selection interact to search optimum solution. A prototype is developted to demonstrate how to run the configurator. The paper ends with a discussion of advantages, future work of the configuration method.

Soft Computing Based Procurement Planning of Time-variable Demand in Manufacturing Systems

Procurement planning with discrete time varying demand is an important problem in Enterprise Resource Planning （ERP）. It can be described using the non-analytic mathematical programming model proposed in this paper. To solve the model we propose to use a fuzzy decision embedded genetic algorithm. The algorithm adopts an order strategy selection to simplify the original real optimization problem into binary ones. Then, a fuzzy decision quantification method is used to quantify experience from planning experts. Thus, decision rules can easily be embedded in the computation of genetic operations. This approach is applied to purchase planning problem in a practical machine tool works, where satisfactory results have been achieved.