Research on Value Evaluation Method of Investment Project Based on Fuzzy Composite Real Options

Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.

Selecting the Technology of Sodium Silicate Modified Poplar with the Highest Performance by Fuzzy Orthogonal Method

Sodium silicate modification can improve the overall performance of wood.The modification process has a great influence on the properties of modified wood.In this study,a new method was introduced to analyze the wood modification process,and the properties of modified wood were studied.Poplar wood was modified with sodium silicate by vacuum-pressure impregnation.After screening using single-factor experiments,an orthogonal experiment was carried out with solution concentration,impregnation time,impregnation pressure,and the cycle times as experimental factors.The modified poplar with the best properties was selected by fuzzy mathematics and characterized by SEM,FT-IR,XRD and TG.The results showed that some lignin and hemicellulose were removed from the wood due to the alkaline action of sodium silicate,and the orderly crystal area of poplar became disorderly,resulting in the reduction of crystallinity of the modified poplar wood.FT-IR analysis showed that sodium silicate was hydrolyzed to form polysilicic acid in wood,and structural analysis revealed the formation of Si-O-Si and Si-O-C,indicating that sodium silicate reacted with fibers on the wood cell wall.TG-DTG curves showed that the final residual mass of modified poplar wood increased from 25%to 67%,and the temperature of the maximum loss rate decreased from 343℃ to 276℃.The heat release and smoke release of modified poplar wood decreased obviously.This kind of material with high strength and fire resistance can be used in the outdoor building and indoor furniture.

Analysis of Landscape Vitality of Historical and Cultural Blocks Based on AHPFuzzy Comprehensive Evaluation Method:A Case Study of Daopashi Street in Anqing City

Historical and cultural blocks are witnesses of history and inheritors of culture. As one of the main spaces for outdoor interaction in historical and cultural blocks, the improvement of its vitality is of great significance for the improvement of residential environment and the better inheritance of history and culture. Taking Daopashi Street in Anqing City as an example, an evaluation model of landscape spatial vitality of historical and cultural blocks was constructed from three aspects of viewing function, store status and service facilities, and analytic hierarchy process was used to determine the index weight and vaguely evaluate the landscape spatial vitality of historical and cultural blocks. The results show that through the comparison of weight, architectural style(0.317), the practicability of service facilities(0.168) and plant landscape(0.165) had a significant impact on the landscape spatial vitality of historical and cultural blocks,and the landscape spatial vitality of historical and cultural blocks in Daopashi Street in Anqing City was at a good level.

Aggregation operators and CRITIC-VIKOR method for confidence complex q-rung orthopair normal fuzzy information and their applications

Supply chain management is an essential part of an organisation's sustainable programme.Understanding the concentration of natural environment,public,and economic influence and feasibility of your suppliers and purchasers is becoming progressively familiar as all industries are moving towards a massive sustainable potential.To handle such sort of developments in supply chain management the involvement of fuzzy settings and their generalisations is playing an important role.Keeping in mind this role,the aim of this study is to analyse the role and involvement of complex q-rung orthopair normal fuzzy(CQRONF)information in supply chain management.The major impact of this theory is to analyse the notion of confidence CQRONF weighted averaging,confidence CQRONF ordered weighted averaging,confidence CQRONF hybrid averaging,confidence CQRONF weighted geometric,confidence CQRONF ordered weighted geometric,confidence CQRONF hybrid geometric operators and try to diagnose various properties and results.Furthermore,with the help of the CRITIC and VIKOR models,we diagnosed the novel theory of the CQRONF-CRITIC-VIKOR model to check the sensitivity analysis of the initiated method.Moreover,in the availability of diagnosed operators,we constructed a multi-attribute decision-making tool for finding a beneficial sustainable supplier to handle complex dilemmas.Finally,the initiated operator's efficiency is proved by comparative analysis.

Solving Multi-Objective Linear Programming Problem by Statistical Averaging Method with the Help of Fuzzy Programming Method

A multi-objective linear programming problem is made from fuzzy linear programming problem. It is due the fact that it is used fuzzy programming method during the solution. The Multi objective linear programming problem can be converted into the single objective function by various methods as Chandra Sen’s method, weighted sum method, ranking function method, statistical averaging method. In this paper, Chandra Sen’s method and statistical averaging method both are used here for making single objective function from multi-objective function. Two multi-objective programming problems are solved to verify the result. One is numerical example and the other is real life example. Then the problems are solved by ordinary simplex method and fuzzy programming method. It can be seen that fuzzy programming method gives better optimal values than the ordinary simplex method.

Arithmetic Operations of Generalized Trapezoidal Picture Fuzzy Numbers by Vertex Method

In this article, we define the arithmetic operations of generalized trapezoidal picture fuzzy numbers by vertex method which is assembled on a combination of the (α, γ, β)-cut concept and standard interval analysis. Various related properties are explored. Finally, some computations of picture fuzzy functions over generalized picture fuzzy variables are illustrated by using our proposed technique.

Upper and Lower Bounds of the α-Universal Triple I Method for Unified Interval Implications

Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.

A mango biological fingerprint anti-counterfeiting method based on Fuzzy C-means clustering

The anti-counterfeiting of agricultural products plays an important role in protecting the rights and interests of consumers and maintaining the healthy development of the food market.Traditional anti-counterfeiting technology mainly relies on anti-counterfeiting features of packaging or labeling,which has the risk of being copied and reused.Biological fingerprint anti-counterfeiting is a method of anti-counterfeiting that takes the biological fingerprint of agricultural products as the anti-counterfeiting feature.This paper aims to take the distribution of lenticels on the surface of mango as a biological fingerprint,and propose a mango biological fingerprint anti-counterfeiting method.As the mango ripens,the peel color of mango will change significantly,which will affect the accuracy of anti-counterfeiting identification.In this paper,the images of ripe mangoes are classified by Fuzzy C-means clustering,and appropriate image enhancement technology is used to highlight the features.The results show that the mango biological fingerprint anti-counterfeiting method based on Fuzzy C-means clustering has good accuracy and robustness,and effectively reduces the impact of peel color change on anti-counterfeiting identification during mango ripening.These results support that it is feasible to use the lenticels distribution of mango as a biological fingerprint.In this paper,a computer vision anti-counterfeiting method based on lenticels distribution is proposed.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Exploring Taiwan’s China Landscape Painting Aesthetic Preferences Through Evaluation Grid Method and the Continuous Fuzzy Kano Model

The primary objective of this study is to apply the Evaluation Grid Method(EGM)and the continuous fuzzy Kano quality model to explore the cognitive preferences of Taiwan China residents regarding the beauty of Taiwan’s China landscape paintings.The aim is to contribute to the development of social and cultural art and promote the widespread appeal of art products.Through a literature review,consultations with aesthetic experts,and the application of Miryoku Engineering’s EGM,this paper consolidates the factors that contribute to the attractiveness of painting art products among Taiwan China residents,taking into account various aesthetic qualities.Simultaneously,the paper introduces the use of the triangular fuzzy golden ratio scale semantics,specifically the equal-ratio aesthetic scale semantics,as a replacement for the traditional subjective consciousness model.Departing from the traditional discrete Kano model that employs the mode as the standard for evaluating quality,this study applies triangular fuzzy numbers to the continuous Kano quality model to analyze the diverse preferences and evaluation standards of the public.The hope is that this research methodology will not only deepen Taiwan China residents’understanding and aesthetic literacy of painting art but also serve as a reference for the popularization of art products.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

基于AHP-Fuzzy-TOPSIS帕鲁特金矿不同中段开采方法对比优化选择

随着井下开采不断向大埋深作业,通风、安全、排水等作业环境日益复杂,不同采矿方法的选择对矿山的可持续发展显得尤为重要。本文以帕鲁特金矿的开采技术条件为基础,针对4种采矿方法(崩落法、上向分层充填采矿法、分段空场嗣后充填法、梯段空场干式充填法),选取包括生产能力、采切比、损失率、贫化率、作业成本(含充填)、通风条件、生产组织和安全条件8个评价指标,运用AHP-Fuzzy-TOPSIS(层次分析-模糊数学-逼近理想解的排序法)分析模型,计算了2292 m、2050 m和1930 m三个较有代表性的中段的贴合度,并对结果进行了分析,与矿山实际生产情况贴合,验证了该方法的可行性。研究成果为下一步1930 m中段采矿方法的选择提供了理论依据,同时为其他矿井在不同生产阶段最优采矿方法选择提供了一定的借鉴意义。

基于模糊数学(Fuzzy)法的中国水稻土肥力质量近30年的时空变化特征

基于农业农村部在我国主要稻区的长期定位监测数据(1988—2017年),采用模糊数学(Fuzzy)法对水稻土肥力质量进行评价,并结合地统计学和机器学习,阐明我国水稻土肥力质量时空变化特征及其影响因素。近30 a来全国稻区土壤肥力质量呈显著上升趋势(P<0.05),从前期(1988—1999年)至中期(2000—2009年)和从中期至近期(2010—2017年),全国稻田土壤肥力指数(SFI)分别平均增加了6.9%和17.7%。各稻区SFI阶段性变化特征存在差异,西南和长江中游稻区呈前慢后快的显著上升趋势(P<0.05),华南和长江三角洲(长三角)稻区呈前快后稳的上升趋势,东北稻区呈前降后升的变化趋势。近期全国稻田SFI呈现北高南低、东高西低的分布特征,SFI超过全国平均值(0.61)的区域占50.2%。与中期相比较,近期全国稻区SFI总体呈上升趋势,SFI增加的区域占69.3%。各稻区在前期和中期(东北稻区的中期除外)均表现为土壤有机质和全氮影响SFI变化的相对重要性占比(19.4%~60.3%)远大于其他指标(0.1%~13.3%)。至近期,所有稻区各指标影响SFI变化的相对重要性占比差距缩小(7.4%~26.8%),土壤有效磷和速效钾及土壤pH(东北稻区pH除外)等指标的相对重要性增加,其中长江中游稻区土壤有效磷含量的相对重要性增至最大,但各稻区仍均以土壤全氮和有机质含量的相对重要性较大。综上,应综合考虑不同阶段和不同稻区土壤肥力质量时空差异特征及其关键肥力指标相对重要性的变化,针对性地优化施肥措施,防治水稻土酸化,以改善和提高水稻土肥力质量。

Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment

Considering the difficulty of fuzzy synthetic evaluation method in calculation of the multiple factors and ignorance of the relationship among evaluating objects, a new weight evaluation process using entropy method was introduced. This improved method for determination of weight of the evaluating indicators was applied in water quality assessment of the Three Gorges reservoir area. The results showed that this method was favorable for fuzzy synthetic evaluation when there were more than one evaluating objects. One calculation was enough for calculating every monitoring point. Compared with the original evaluation method, the method predigested the fuzzy synthetic evaluation process greatly and the evaluation results are more reasonable.

SYSTEMATIC METHOD TO GENERATE NEW IDEAS IN FUZZY FRONT END USING TRIZ

The obstacle for idea generation in fuzzy front end （FFE） is difficult to apply knowledge in different fields for designers. Theory of inventive problem solving TRIZ and computer-aided innovation systems （CAIs） which are TRIZ-base software systems with a knowledge base provide a framework for knowledge application in different fields. The major methods in TRIZ are selected, which have four types. The problems to be solved for each method are summarized and mapping from the problems to the methods is given. Systematic method with eight paths to integrate the methods and problems is formed. A case study shows the idea generation in FFE using the integrated method step by step.

Fully implicational methods for approximate reasoning based on interval-valued fuzzy sets

The aim of this paper is to discuss the approximate rea- soning problems with interval-valued fuzzy environments based on the fully implicational idea. First, this paper constructs a class of interval-valued fuzzy implications by means of a type of impli- cations and a parameter on the unit interval, then uses them to establish fully implicational reasoning methods for interval-valued fuzzy modus ponens （IFMP） and interval-valued fuzzy modus tel- lens （IFMT） problems. At the same time the reversibility properties of these methods are analyzed and the reversible conditions are given. It is shown that the existing unified forms of α-triple I （the abbreviation of triple implications） methods for FMP and FMT can be seen as the particular cases of our methods for IFMP and IFMT.

A METHOD OF SOLVING THE FUZZY FINITE ELEMENT EQUATIONS IN MONOSOURCE FUZZY NUMBERS

For same cases the rules of monosource fuzzy numbers con be used into the solution of fuzzy stochastic finite element equations in engineering. This method can reduce the computing quantity of the solution. It can be proved that the amount of the solution is nearly as much as that with the general stochastic finite element method (SFEM). In addition, a new method to appreciate the structural fuzzy failure probability is presented for the needs of the modem engineering design.

Fuzzy finite difference method for heat conduction analysis with uncertain parameters

A new numerical technique named as fuzzy finite difference method is proposed to solve the heat conduction problems with fuzzy uncertainties in both the phys- ical parameters and initial/boundary conditions. In virtue of the level-cut method, the difference discrete equations with fuzzy parameters are equivalently transformed into groups of interval equations. New stability analysis theory suited to fuzzy difference schemes is developed. Based on the parameter perturbation method, the interval ranges of the uncertain temperature field can be approximately predicted. Subsequently, fuzzy solutions to the original difference equations are obtained by the fuzzy resolution theorem. Two numerical examples are given to demonstrate the feasibility and efficiency of the presented method for solving both steady-state and transient heat conduction problems.

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.

Improvements to the fuzzy mathematics comprehensive quantitative method for evaluating fault sealing

Fuzzy mathematics is an important means to quantitatively evaluate the properties of fault sealing in petroleum reservoirs.To accurately study fault sealing,the comprehensive quantitative evaluation method of fuzzy mathematics is improved based on a previous study.First,the single-factor membership degree is determined using the dynamic clustering method,then a single-factor evaluation matrix is constructed using a continuous grading function,and finally,the probability distribution of the evaluation grade in a fuzzy evaluation matrix is analyzed.In this study,taking the F1 fault located in the northeastern Chepaizi Bulge as an example,the sealing properties of faults in different strata are quantitatively evaluated using both an improved and an un-improved comprehensive fuzzy mathematics quantitative evaluation method.Based on current oil and gas distribution,it is found that our evaluation results before and after improvement are significantly different.For faults in＂best＂and＂poorest＂intervals,our evaluation results are consistent with oil and gas distribution.However,for the faults in＂good＂or＂poor＂intervals,our evaluation is not completelyconsistent with oil and gas distribution.The improved evaluation results reflect the overall and local sealing properties of target zones and embody the nonuniformity of fault sealing,indicating the improved method is more suitable for evaluating fault sealing under complicated conditions.