基于区间直觉模糊 AHP 法的大坝浇筑方案选取

针对工程方案优选中的模糊问题,基于直觉模糊层次分析法,将同时考虑隶属度、非隶属度及犹豫度的区间直觉模糊数引入层次分析法,对工程方案进行优先排序。通过建立层次结构模型,根据影响因素的重要性差异确定直觉模糊判断矩阵,依据决策者权重,计算各方案判断矩阵的熵权,从而得到各方案在不同属性下的最终熵权,并依据大小排序确定最优方案。将该方法应用于工程案例,通过计算和分析证明了本方法在工程方案优选问题中有效性及可行性。     

广义Shapley区间直觉不确定语言Choquet积分在绿色住宅投资群决策中的应用

多属性群决策作为解决多方案选择性问题的一种重要方法具有十分重要的研究意义,目前的多属性群决策方法主要存在属性评价过程中信息失真、没有注意到指标间存在交互作用以及如何科学合理地获得专家及指标权重三个问题。针对以上三个问题,文章在获取属性评价信息时,由专家用区间直觉不确定语言给出方案属性值的定性判断;考虑到属性间的交互作用,利用模糊测度及GS-IVIULCA算子来计算方案的综合评价值;专家及属性权重由信息熵与Shapley函数确定;当专家及属性权重不确定时,分别建立了专家集与属性集上的最优模糊测度模型。基于此,给出了信息不确定环境下一个全新的群决策方法。最后,通过一个绿色住宅投资群决策案例进行实证分析来验证该方法的可行性和有效性。     

基于组合权重的模糊TOPSIS 法在工程项目评估中的应用

TOPSIS 广泛应用于多属性群决策的环境中,但是少有在工程项目评估中出现。利用TOPSIS 的基本原理,结合变权及反馈的思想,提出了基于组合权重的直觉模糊集TOPSIS 方法。先由专家利用直觉模糊数对决策方案进行评价;分别应用基于变权向量的思想以及包括主观权重和反馈权重在内的组合权重来确定决策者权重以及属性权重;确定综合加权直觉模糊评价矩阵的正负理想解并对Hamming 距离进行计算,从而得出评价对象中优劣方案的评价及排序。并通过工程项目评估的算例进一步说明基于组合权重的直觉模糊TOPSIS 方法的科学有效性。     

基于 Z-numbers 模糊数的改进 PROMETHEE 法

针对评价值为模糊数的工程方案优选问题,通过 Z-numbers 模糊数方法建立模糊评价矩阵,考虑了各决策主体的可靠程度,将模糊推理引入 PROMETHE 方法,对方案进行优先排序。运用 Matlab 的模糊推理系统工具箱构建模糊规则模型,计算每两对方案的差别度,采用模糊语言评价代替优先函数的选择,得到各方案在不同属性下的优先指数,并根据综合优序级别值对各备选方案进行排序,获得最优方案。最后通过一个工程案例进行计算和分析,证明了该方法对工程方案优选问题具有良好的实践价值。     

基于MYCIN与直觉模糊的桥梁拆除方案优选

为科学合理地优选桥梁拆除方案,针对已有评价方法中评价指标模糊处理过于简化以及AHP确定指标权重主观性强的问题,首次构建了包含5项一级指标和17项二级指标的桥梁拆除方案评价指标体系;在AHP确定指标权重的基础上,创新性地运用直觉模糊理论和MYCIN不确定因子,融合不确定因子证据信息和权重,根据实质不确定因子最大化原则来进行最佳桥梁拆除方案的决策优选。最后,结合沌阳大道高架桥拆除实例应用验证了该评估优选方法的可靠性,并在北翟高架桥快速拆除项目上示范应用。     

基于一类新的直觉模糊熵的直觉模糊多属性决策法

针对属性权重完全未知且属性值为直觉模糊数的多属性决策模型,提出了一个新的决策方法。该方法首先通过构造一类新的直觉模糊熵,然后利用该直觉模糊熵计算各个属性权重,进而提出了基于直觉模糊相似的TOPSIS决策法。为说明方法的有效性和实用性,给出了一个智能手机购买选择问题的例子进行说明。     

基于GM(1,1)和D-S证据理论的直觉模糊应急决策方法

针对应急决策问题,提出1种基于GM(1,1)与D-S证据理论的直觉模糊决策方法。借助记分函数和犹豫度构建以直觉模糊数为建模对象的GM(1,1)模型,并基于该模型预测下一时间段的决策信息;根据直觉模糊熵权法确定指标权重,通过指标权重与直觉模糊集本身特点,构建D-S证据理论的基本概率分配函数,并根据D-S证据理论的信息融合规则进行方案的信息融合,进而对方案进行排序;通过某特大煤矿坍塌事件进行实证研究,验证了本文提出方法的合理性与可行性。     

吴江地区软土地基处理方案的优化选择

针对软基处理方案影响因素的模糊性和复杂性等特点,提出了基于模糊理论的软土地基处理方案决策模型,给出了该模型的原理、方法及具体应用步骤。通过构建软土地基处理方案模糊评判模型,考虑各个影响因素的重要程度,将各个方案的评价指标量化分析,使方案选择更加科学合理和直观可靠。     

基于直觉模糊集的膨胀土胀缩性评价

膨胀土胀缩等级的分类是治理膨胀土工作中的首要问题，为了准确评价膨胀土的胀缩性等级，以便于现场及时采取相应工程措施，减少灾害的发生，本文提出了综合考虑主、客观权重的直觉模糊集评价模型。选取液限、胀缩总率、塑性指数、天然含水率和自由膨胀率5个评价指标构成评价属性集。针对某高速公路的钻孔土样建立直觉模糊评价模型，并分析了指标权重变化对于胀缩性评价结果影响的灵敏度。研究结果表明：基于直觉模糊法的评价结果与模糊数学法、物元可拓法、变权靶心贴近度法和未知测度法的评价结果较为吻合，本文通过与4种有效模型评价结果相互印证的方式验证了直觉模糊集理论建立的评价模型应用于膨胀土胀缩性评价的合理性和可行性；针对某高速公路的局部钻孔土样的指标模糊性分析表明，自由膨胀率、塑性指数、天然含水率、胀缩总率、液限的指标权重的选取对胀缩性评价结果的敏感性依次减弱，其中自由膨胀率模糊性值最小、敏感性最强，而液限的模糊性值最大，因而随着液限权重的变化对胀缩性评价结果的影响较小。     

基于直觉模糊集的工程建设全过程咨询风险评价

文中针对工程建设全过程咨询风险评价进行了研究。首先构建了工程建设全过程咨询风险评价层次结构,将专家评价信息转化为直觉模糊集形成评价矩阵;然后利用直觉模糊熵描述专家信息的模糊程度并确定准则权重,利用Euclidean距离确定专家信息的相似度并结合犹豫度确定专家权重,利用得分函数确定各风险因素综合得分值,据此确定关键风险因素;最后通过实证分析验证了评价方法的可行性,研究成果为工程建设全过程咨询项目风险管理提供决策依据。     

基于模糊理论大跨浅埋公路隧道施工风险评估

鉴于大跨浅埋公路隧道施工风险评估的模糊属性,采用模糊数学方法定量化处理施工风险估计中的定性问题。建立了茅山隧道施工风险多层次模糊综合评价数学模型,运用模糊理论对专家给出的茅山隧道施工各项风险因素的概率等级和损失等级隶属度进行统计分析,得到了各因素的概率及损失估计结果。基于R=P×C模型考虑了风险因素发生概率及损失对风险评估的影响,得到各风险因素、基本风险事件的风险等级,确定茅山隧道施工的安全风险、环境影响风险及整体风险等级为四级,应采取有效的风险控制措施应对。研究表明,模糊理论解决了风险评估中的模糊性及量化问题,可作为评估大跨浅埋公路隧道施工阶段风险的有效模型。     

基于云模型的地铁施工地表变形风险推理分析

在地铁盾构施工地表沉降研究中,风险因素具有模糊性和随机性的特点,云模型理论可将自然语言值表示的某个定性概念转换为定量表示,把模糊问题的亦此亦彼性和隶属度的随机性统一起来。本文在建立盾构施工地表沉降事故树的基础上,运用云模型处理专家对风险因素发生概率大小分布范围划分定性与定量的转换关系,通过对云图凝聚性的修正,更加客观、准确地确定了地铁盾构施工引发地表沉降各风险因素的概率分布范围和基本事件的概率值;基于云模型和信心指数实现了定性语言值向定量数值的转换。在此基础上进行模糊事故树敏感性分析,得出盾构施工地表沉降风险的基本事件模糊重要度,由此明确影响大的基本事件,便于针对性制定施工事前地表沉降控制措施。     

基于三角模糊数的输变电工程模糊综合评价

针对输变电工程风险评价中专家主观因素所占比例较高的现状,研究了主观和客观相结合的评价方法,利用网络分析法与模糊评判法构建模糊网络风险评价模型,从而对风险实施有效控制。根据输变电工程特征,分析了影响施工安全的综合因素,建立了输变电工程风险评价指标体系,并使用两两比较判断矩阵法计算风险指标权重,再利用模糊综合评判将二级指标整合,得到项目的综合风险水平。为解决模型主观偏好的弊端,构建过程加入风险维度,用三角模糊数处理决策过程中的模糊性,对模型做进一步改善。并以某输变电工程为例,验证该方法具有可行性。     

基于模糊综合评判的地基处理方案优化

利用模糊数学的原理和方法,建立模糊综合评判模型,为优选地基处理方案提供了一种有效、实用的方法。     

A fuzzy logic approach to model delays in construction projects using translational models

The likelihood of a project delay is affected by different factors; thus, there is a pressing need to develop a method that estimates the likelihood of such a delay. In this paper, analysis of potential occurrences of delays, which are classified into procedural, enabling, and triggering causes, is performed using the fuzzy fault-tree analysis method. Subjective judgment expresses causes of delay and their respective degree of effectiveness which are analysed in this study. The fuzzy triangular model and translational models are employed in this study. The severity of the likelihood of the project delay is the result of this analysis. A model was developed to assess the likelihood of the project delay. Evaluation of the model was performed for applicability and adequacy of the model. On average, evaluation performed by independent construction engineers and fuzzy logic experts produced satisfactory results.     

多项目并行施工危险源管理研究

鉴于现行危险源评价中针对多项目并行施工危险源的评价方法较少。结合多项目的特点,运用模糊数学理论、马尔科夫理论和可靠性理论,建立了基于可靠性分析的模糊马尔科夫模型,为总项目部进行危险源控制提供了理论依据,减少了其对危险源进行盲目控制,从而也起到节约成本的作用。将此模型运用于某小区建设危险源评价中,计算结果表明,下一时段第一与第四项目部的深基坑护壁强度不够所产生危险的概率比较大,应对基坑进行加固,第二与第三项目部危险源所产生的危险等级概率在可接受范围内,与工程实施中的反馈信息基本一致。     

A fuzzy logic approach to model delays in construction projects using rotational fuzzy fault tree models

Delays in construction projects are inevitable and, as a result, claims and disputes arise. Different causes of delay can come into play and therefore the need to identify and classify different causes of project delay arises. Different factors that contribute to project delay affect the likelihood of project delay in different degree of effectiveness. Fuzzy fault tree analysis (FTA) is suggested by this research to estimate the likelihood of project delay. Likelihood of delay membership function is further quantified using the weighted average defuzzification method. Two fuzzy logic models are implemented into the fuzzy FTA, using Visual Basic software: the models discussed in this research are Baldwin's rotational model and the Angular model. Comparison between the two fuzzy logic models has been carried out. Validation of the fuzzy FTA computer model is performed. Validation of the model was performed for adequacy and applicability of the model. On average, the validation performed by independent construction engineers and fuzzy logic experts produced satisfactory results. The computer software suggested by this study is an attempt to assess the likelihood of the project delay, which helps reduce delays in construction projects that can cause time loss.     

Selection of slab formwork system using fuzzy logic

Formwork plays an important role in building construction. The selection of an appropriate formwork system can reduce project cost, improve quality and speed up the construction process. Although the selection of an appropriate formwork system requires years of experience in formwork design, few experienced personnel may be available, especially in small/medium size contracting companies. With the lack of such experts, the costly outsourcing option becomes essential otherwise the selection of a particular formwork system might not be appropriate. A structured approach is developed to help decision makers in small/medium Egyptian construction companies to select the appropriate horizontal formwork system(s) for their projects. This can be achieved by recognizing the project governing factors affecting the selection process. Based on these factors, a knowledge base is developed to facilitate the process. A fuzzy logic system is used to automate the process and overcome ambiguity and uncertainty in the selection process. The system is shown to be useful and accurate in its application to a real-life case. A survey of formwork experts reveals its ease of use. Further research will expand the system to consider vertical formwork selection to ensure full compatibility.     

A fuzzy logic approach to the selection of cranes

This paper presents a fuzzy logic approach to select the best crane type in a construction project from the main crane types, namely, mobile, tower and derrick cranes. Each factor of the project is classified as being dynamic or static according to whether the factor does or does not depend on the particular project. Linguistic information about the suitability of each crane type with respect to each factor of the project is translated into either fuzzy sets (for static factors) or fuzzy if–then rules (for dynamic factors). The fuzzy rules are then aggregated into a fuzzy relation between the space of factor property and the space of crane efficiency. In a particular project the experts describe the property as well as the relative importance of each factor. The rules are then fired using the max–min extension principle, and the resulting efficiencies are aggregated with their importance weights. The process identifies the best crane as the one with the highest expected overall efficiency.     

Application of fuzzy analytic hierarchy process model on determination of optimized pile-type

Pile-type selection is a very important stage of foundation design, and there are many field factors influencing the decision of pile-type selection. Since there is a limitation of traditional “major factors method” to satisfy the requirement of modern foundation construction, this study presents an efficient approach, in which analytic hierarchy process (AHP) is employed. AHP is a multiple criteria decision-making tool that has been applied in many fields related to the decision-making, e.g., in the field of economics, marketing, sociology, etc. However, it is rarely reported that AHP is applied in the field of civil engineering for decision making. In this study, AHP combined with fuzzy synthetic evaluation method is employed to select the type of pile used as the foundation of a residential building in Fuzhou, Fujian Province, China. The results show that fuzzy AHP approach is an easy and efficient way for pile-type selection.