建筑供应链视角下区块链技术应用影响因素分析:基于Fuzzy-DEMATEL-ISM模型

为促进区块链技术赋能建筑供应链数字化转型,从建筑供应链视角探究区块链技术应用影响因素的相互关系与作用方式。基于模糊决策实验室与解释结构模型先后界定因素属性特征、相互作用关系,划分层次结构,并从因素的中心度(M)、原因度(R),层次结构维度进行分析。结果表明:政策导向与法律体系、技术兼容性、技术功能特性、技术运营成本、企业规模等作为原因因素,对区块链技术应用具有驱动作用;竞争者行为、节点企业使用意愿、行业技术认知、专业基础设施、核心人才与技术能力、供应链结构模式等因素作为结果因素,可反映区块链实际应用情况;在建筑供应链的区块链技术应用过程中以改善结果因素为导向的促进策略更为有效。研究结论可为促进区块链在建筑行业中的应用提供策略参考。

Simulation of Haloxylon Ammodendron Stand Basic Diameter Structure Based on Fuzzy Distribution Function

Based on the investigation data of 12 Haloxylon ammodendron plots in the south edge of Gurbantunggut Desert, Fuzzy distribution was introduced into the study of Haloxylon ammodendron base diameter structure fitting according to the consistency between the characteristics of Fuzzy distribution function and the distribution series of cumulative percentage of stand base diameter, and the fitting precision and effect of Fuzzy distribution function were discussed. The root mean square error RMSE and determination coefficient R2 values showed that Fuzzy-Γ1, Fuzzy-Γ2, Fuzzy-Γ3, Fuzzy-Γ4 had good fitting performance, among which Fuzzy-Γ1 had relatively high fitting precision, and its parameters were closely related to stand age and density, Fuzzy-Γ2 distribution function was the second, and Fuzzy-Γ4 distribution function had the worst fitting effect. By introducing a parameter c from the similarity of four distribution function formulas, a generalized Fuzzy distribution function Fuzzy-Γ5 is obtained. This function shows the highest fitting accuracy. Most of the values of parameter c are near 1 or 2, which shows that the diameter distribution is mainly approximate to Fuzzy-Γ1 and Fuzzy-Γ2.

New Approaches to the Prognosis and Diagnosis of Breast Cancer Using Fuzzy Expert Systems

Breast cancer remains a significant global health challenge, necessitating effective early detection and prognosis to enhance patient outcomes. Current diagnostic methods, including mammography and MRI, suffer from limitations such as uncertainty and imprecise data, leading to late-stage diagnoses. To address this, various expert systems have been developed, but many rely on type-1 fuzzy logic and lack mobile-based applications for data collection and feedback to healthcare practitioners. This research investigates the development of an Enhanced Mobile-based Fuzzy Expert system (EMFES) for breast cancer pre-growth prognosis. The study explores the use of type-2 fuzzy logic to enhance accuracy and model uncertainty effectively. Additionally, it evaluates the advantages of employing the python programming language over java for implementation and considers specific risk factors for data collection. The research aims to dynamically generate fuzzy rules, adapting to evolving breast cancer research and patient data. Key research questions focus on the comparative effectiveness of type-2 fuzzy logic, the handling of uncertainty and imprecise data, the integration of mobile-based features, the choice of programming language, and the creation of dynamic fuzzy rules. Furthermore, the study examines the differences between the Mamdani Inference System and the Sugeno Fuzzy Inference method and explores challenges and opportunities in deploying the EMFES on mobile devices. The research identifies a critical gap in existing breast cancer diagnostic systems, emphasizing the need for a comprehensive, mobile-enabled, and adaptable solution by developing an EMFES that leverages Type-2 fuzzy logic, the Sugeno Inference Algorithm, Python Programming, and dynamic fuzzy rule generation. This study seeks to enhance early breast cancer detection and ultimately reduce breast cancer-related mortality.

基于Fuzzy DEMATEL-ISM的高技术船舶产业链韧性影响因素研究

为明晰高技术船舶产业链韧性提升的关键,基于文献分析并采用专家访谈法,从预测能力、抵抗能力、恢复能力3个维度,确定高技术船舶产业链韧性的14个影响因素,运用Fuzzy DEMATEL确定其重要程度和因果属性,识别关键影响因素,并利用ISM划分影响因素的层次结构,表征各影响因素的致因属性和层次关系,并从韧性能力的角度分析其对产业链韧性的影响。结果表明,专业化产业集群、上下游产业协同、知识储备、技术创新能力和产业链结构是高技术船舶产业链韧性的关键影响因素,其中知识储备和产业链结构是本质致因,抵抗能力对产业链韧性起最直接作用。

DYNAMIC CHARACTERISTIC ANALYSIS OF FUZZY-STOCHASTIC TRUSS STRUCTURES BASED ON FUZZY FACTOR METHOD AND RANDOM FACTOR METHOD

A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented. Considering the fuzzy randomness of the structural physical parameters and geometric dimensions simultaneously, the structural stiffness and mass matrices axe constructed based on the fuzzy factor method and random factor method; from the Rayleigh＇s quotient of structural vibration, the structural fuzzy random dynamic characteristic is obtained by means of the interval arithmetic; the fuzzy numeric characteristics of dynamic characteristic axe then derived by using the random variable＇s moment function method and algebra synthesis method. Two examples axe used to illustrate the validity and rationality of the method given. The advantage of this method is that the effect of the fuzzy randomness of one of the structural parameters on the fuzzy randomness of the dynamic characteristic can be reflected expediently and objectively.

The Fuzzy Grey Relational Analysis of the Factors Influencing Farm Produce Logistics

The farm produce logistics plays an important role in promoting the agricultural production and prosperity of the rural economy,so grasping the main factors influencing the development of farm produce logistics,is of important significance to accelerating the development of farm produce logistics. The values of identification coefficient in the grey relational analysis are taken based on the experience,so the accuracy of the results is affected. This article uses the improved fuzzy grey relational analysis to analyze the main factors influencing farm produce logistics. The results show that the number of storage companies has a great impact on the development of farm produce logistics,followed by the farm produce processing machinery capacity,rural transport infrastructure,farm produce market conditions and government financial support for agriculture,while the total number of Internet users in rural areas has an limited impact on the development of farm produce logistics.

Optimal fuzzy PID controller with adjustable factors based on flexible polyhedron search algorithm

A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.

Multi-factor high-order intuitionistic fuzzy timeseries forecasting model

Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.

Success Factors of Biotechnology Industry Based on Triangular Fuzzy Number

Based on the theory of competitive advantage and value chain, this paper establishes the indicator system, and develop the strategic framework using the fuzzy Delphi method. Then the triangular fuzzy number model is established using Fuzzy Analytic Hierarchy Process, and the key factors influencing biotechnology industry are extracted. The results show that in terms of weight, the key factors influencing the success of biotechnology industry are sequenced as follows: "open innovation capacity", "quality and cost control ability", "advanced customer-oriented product manufacturing capacity", "technology R & D personnel's capacity", "brand image building capacity", "logistics and sales capacity", "grasping the market demand trends". The manufacturers and government decision-making body can use this as the basis, to promote the development of the biotechnology industry.

Model Predictive Yaw Control Using Fuzzy-Deduced Weighting Factor for Large-Scale Wind Turbines

Yaw control system plays an important role in helping large-scale horizontal wind turbines capture the wind energy.To track the stochastic and fast-changing wind direction,the nacelle is rotated by the yaw control system.Therein,a difficulty consists in the variation speed of the wind direction much faster than the rotation speed of the nacelle.To deal with this difficulty,model predictive control has been recently proposed in the literature,in which the previewed wind direction is employed into the predictive model,and the estimated captured energy and yaw actuator usage are two contradictive objectives.Since the performance of the model predictive control strat-egy relies largely on the weighting factor that is designed to balance the two objectives,the weighting factor should be carefully selected.In this study,a fuzzy-deduced scheme is proposed to derive the weighting factor of the mod-el predictive yaw control.For the proposed fuzzy-deduced strategy,the variation degree and the increment of the wind direction during the predictive horizon are used as the inputs,and the weighting factor is the output,which is dynamically adjusted.The proposed model predictive yaw control is demonstrated by some simulations using real wind data and its performance is compared with the conventional model predictive control with thefixed weighting factor.Comparison results confirm the outweighing performance of the proposed control strategy over the conventional one.

Calculation of impact factor of vibrator oscillation in offset printing based on fuzzy controller and genetic algorithm

In the inking system of an offset printing press,a vibrator roller distributes ink not only in the circumferential direction but also in the axial direction.In the control process,if ink amount is determined only by the dot area coverage without considering the impact of vibrator roller's oscillation,the printing colour quality will be reduced.This paper describes a method of calculating the impact factor of vibrator roller' s oscillation.First,the oscillation performance is analyzed and sample data of impact factor is got.Then,a fuzzy controller used for the calculation of the impact factor is designed,and genetic algorithm is used to optimize membership functions and obtain the fuzzy control rules automatically.This fuzzy controller can be used to calculate impact factors for any printing condition,and the impact factors can be used for ink amount control in printing process and it is important for higher printing colour quality and lowering ink and paper waste.

Type 2 Possibility Factor Rotation in No-Data Problem

Uemura [1] discovered a mapping formula that transforms and maps the state of nature into fuzzy events with a membership function that expresses the degree of attribution. In decision theory in no-data problems, sequential Bayesian inference is an example of this mapping formula, and Hori et al. [2] made the mapping formula multidimensional, introduced the concept of time, to Markov (decision) processes in fuzzy events under ergodic conditions, and derived stochastic differential equations in fuzzy events, although in reverse. In this paper, we focus on type 2 fuzzy. First, assuming that Type 2 Fuzzy Events are transformed and mapped onto the state of nature by a quadratic mapping formula that simultaneously considers longitudinal and transverse ambiguity, the joint stochastic differential equation representing these two ambiguities can be applied to possibility principal factor analysis if the weights of the equations are orthogonal. This indicates that the type 2 fuzzy is a two-dimensional possibility multivariate error model with longitudinal and transverse directions. Also, when the weights are oblique, it is a general possibility oblique factor analysis. Therefore, an example of type 2 fuzzy system theory is the possibility factor analysis. Furthermore, we show the initial and stopping condition on possibility factor rotation, on the base of possibility theory.

Accurate Reactive Power Controller and Power Factor Correction Using Fuzzy Logic

This paper presents the use of fuzzy logic technique to control the reactive power of load and hence improve the source power factor. A shunt compensator is proposed, which consists of a voltage controlled reactor by full-wave thyristor bridge in parallel with a capacitor. The proposed voltage control technique composed of two independent fuzzy controllers, primary and secondary. The PFC （primary fuzzy controller） is designed based on linearization method to introduce to the network the nearest value of reactive power （VAR） required to correct the power factor. The SFC （secondary fuzzy controller） is designed to achieve accurate compensation for the required VAR to achieve the pre-set power factor value. Simulations for 15 different practical study cases are presented to evaluate the performance of the controller, and the results show how the designed controller is fast and accurate. Harmonics analyses are carried out up to the 13th harmonic to determine the requirement of harmonics filter.

Study on Two-Tier EV Charging Station Recommendation Strategy under Multi-Factor Influence

This article aims to address the clustering effect caused by unorganized charging of electric vehicles by adopting a two-tier recommendation method.The electric vehicles(EVs)are classified into high-level alerts and general alerts based on their state of charge(SOC).EVs with high-level alerts have the most urgent charging needs,so the distance to charging stations is set as the highest priority for recommendations.For users with general alerts,a comprehensive EV charging station recommendation model is proposed,taking into account factors such as charging price,charging time,charging station preference,and distance to the charging station.Using real data from EV charging stations and ride-hailing vehicles in Xiamen City,Fujian Province,simulation analyses are conducted using Python for different periods of the day.The research results show that the stability of the multi-factor recommendation model in terms of service density variance,coverage rate,price cost,and distance cost outperform single-factor models.This indicates that our composite multi-factor recommendation model has significant practical value in resolving the clustering phenomenon caused by unorganized EV charging,optimizing the EV charging service system,and improving user satisfaction.

基于Fuzzy-DEMATEL-ISM的四川省报废汽车回收率影响因素分析

报废汽车回收率对汽车回收拆解利用产业发展至关重要。对四川省报废汽车回收率影响因素做了相关研究,结合四川省报废汽车回收产业发展现状,从经济层面、政策层面、技术层面、思想层面和其他层面5个维度提出了12个影响因素,并收集了专家问卷,借助Fuzzy-DEMATEL法定量分析了各因素的影响程度;结合ISM法分析了报废汽车回收率关键影响因素的层级关系,识别出收车成本、回收利润、车主收入水平、环保意识、法律意识5个直接影响因素,非法回收处罚力度、补贴政策、零部件再利用政策3个本质影响因素。针对影响因素分析结果,提出了相应建议措施,为四川省报废汽车回收率的提升提供参考。

APPLICATION OF FUZZY CONTROL METHOD WITH SELF-TUNING FACTOR IN JIGGER'S DISCHARGING

Adopting the strategy of fuzzy control with self tuning factor within whole universe of discourse, a kind of fuzzy control method for jigger discharging is put forward. This method has many advantages over the conventional PID controller in terms of response speed, stability and robustness. It is effective to restrain the jig bed from over thick or empty, and the stability of the bed is markedly improved. The good results are obtained in factory tests.

一种随机变论域Fuzzy控制器在医疗头盔中的实现

目前的自适应模糊控制方法在实际问题中难以达到良好的效果。针对这一问题,提出一种随机变论域Fuzzy控制器。首先,基于原有的伸缩因子设计一种简单、精准的随机伸缩因子,并通过仿真对比验证其性能;接着,以实际前后圈梁伸缩的长度与理想状态下前后圈梁伸缩的长度期望值的误差和误差的变化作为输入变量,引起旋钮转速变化的多少作为输出变量,设计随机变论域Fuzzy控制器;最后,使用仿真实验对比响应曲线图分析得到,设计的模糊控制器性能明显提升,并且整个控制过程中超调小、稳定性高、响应时间有明显的缩短,实现了医疗头盔的治疗效果。

基于遗传算法的汽车主动悬架变论域模糊PID控制

针对1/4车主动悬架系统,提出一种基于遗传算法(genetic algorithm,GA)的变论域模糊比例-积分-微分(proportional-integral-differential,PID)控制方法.在建立主动悬架系统模型的基础上,引入变论域思想设计模糊PID控制器.为进一步改善控制器减振效果,采用GA来优化变论域中伸缩因子描述函数的参数.结果表明:相比PID、模糊PID与未优化的变论域模糊PID等控制方法,基于GA的变论域模糊PID控制方法在降低车身垂向加速度、改善乘坐舒适性方面具有优越性;所提控制方法对簧载质量和车辆行驶速度不确定性具备较强的鲁棒性.

哪些因素决定了科技龙头企业竞争力?——基于fs QCA的组态效应研究

竞争力是事关科技龙头企业生存和发展的关键问题。当前经济新的下行压力进一步增大,哪些因素决定了科技龙头企业竞争力,这是在理论和实践的双重探索中形成的一个重要时代课题。因为科技龙头企业竞争力影响因素以及因素之间关系十分复杂,所以组态视角和模糊集定性比较分析可作为相对合适的研究方法,深入分析科技龙头企业竞争力的决定因素。单个要素并不构成科技龙头企业竞争力产生的必要条件,科技龙头企业可从3种路径获得较强竞争力,具有适当规模在提升竞争力方面发挥着重要作用。科技龙头企业可以根据实际情况,充分发挥自身有利条件,通过不同的方式实现企业竞争力提升。引入组态视角探究哪些因素决定了科技龙头企业竞争力,有助于深化对科技龙头企业竞争力背后多重因素间复杂互动本质的理性认识,对科技龙头企业提升竞争力具有重要的理论价值与实践意义。