Risk analysis of extended reach wells in the Liuhua Oilfield,South China Sea,based on comprehensive fuzzy evaluation method

Drilling engineering has great uncertainty and it always involves huge investment and high risk. Risk analysis of extended reach drilling （ERD） is very important to prevent complex failures and to improve drilling efficiency. Nowadays there are few reports on how to analyze quantitatively the drilling risk for extended reach wells （ERWs）. Based on the fuzzy set theory, a comprehensive fuzzy evaluation model for analyzing risks of ERD is proposed in this paper. Well B6ERW07 is a planned 8,000-meter ERW with a high ratio of horizontal displacement （HD） to vertical depth （VD） in the Liuhua Oilfield, the South China Sea, China. On the basis of the evaluation model developed in this study, the risk for drilling Well B6ERW07 was evaluated before drilling. The evaluation result shows that the success rate of drilling this well is predicted to be 51.9%, providing important rational and scientific information for the decisionmakers.

Electric Multiple Unit Bogie Maintainability Allocation with Interval Analysis and Fuzzy Evaluation Method

Based on the failure rate and design features allocation method,considering the multiple influential factors which affect electric multiple unit( EMU) bogies,maintainability allocation on EMU bogie was presented by interval analytic hierarchy analysis and fuzzy comprehensive assessment. The maintainability allocation model was established. Weight based on the influence degree of each factor on maintenance was assigned. Fuzzy interval numbers were used to substitute real numbers and express uncertain information.The maintenance weighting factors for each subsystem were calculated by fuzzy comprehensive assessment. Then the allocation method was applied to EMU bogie. The results show that the method is feasible. The problem difficult to quantify for EMU bogie maintenance allocation is solved effectively.

Neural Network Based Multi-level Fuzzy Evaluation Model for Mechanical Kinematic Scheme

To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result,as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model,the corresponding evaluation result is outputted and the best alternative can be selected. Under this model,expert knowledge can be effectively acquired and expressed,and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.

Research on Flight Delay Based on Fuzzy Evaluation Algorithm

In recent years, since airspace restrictions and the volume of passenger traffic are increasing, the rate of flight delay is rising rapidly and the contradiction about it is outstanding. Flight delay event not only holds up passengers’ time, but also makes the airlines suffer a lot. So a scientific and reasonable guidance is necessary to reduce the delay effect. This paper firstly establishes a method to assess the degree of airport delays and get all factors which caused the flight delays quantification, and ultimately we offer a proposal to deal with the flow factor, which is the principal reason for flight delays.

AN ANALYSIS OF THE APPLICABILITY OF FUZZY CLUSTERING IN ESTABLISHING AN INDEX FOR THE EVALUATION OF METEOROLOGICAL SERVICE SATISFACTION

An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public satisfaction survey data obtained in Wafangdian,China in 2010,this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index.Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators,correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer,then one indicator could be removed,or the two indicators merged.For evaluation indicators in different sub-evaluation layers,although clustering reveals attribute correlations,these indicators may not be substituted for one another.Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.

Fuzzy Synthetic Evaluation of Water Quality of Naoli River Using Parameter Correlation Analysis

In order to improve the effectiveness of Fuzzy Synthetic Evaluation (FSE) models, a Parameter Correlation Analysis (PCA) was introduced into the FSE and a case study was carried out in the Naoli River in the Sanjiang Plain, Northeast China. The basic principle of the PCA is that the pairs of parameters which are highly correlated and linear with each other would contribute the same information to an assessment and one of them should be eliminated. The method of the PCA is that a correlation relationship among candidate parameters is examined before the FSE. If there is an apparent nonlinear or curvilinear relationship between two parameters, then both will be retained; if the correlation is significant (p<0.01), and the scatter plot suggests a linear relationship, then one of them will be deleted. However, which one will be deleted? For solving this problem, a sensitivity test was conducted and the higher sensitivity parameters remained. The results indicate that the original data should be preprocessed through the PCA for redundancy and variability. The study shows that introducing the PCA into the FSE can simplify the FSE calculation process greatly, while the results have not been changed much.

Vulnerability Assessment of Tourism Environment in the South China Sea Islands : Construction of Evaluation Model Based on Interpretation System of Formation Mechanism

Tourism vulnerability research is an important theoretical basis for sustainable research of tourism.In this study,it hopes to establish a comprehensive evaluation index system for vulnerability of tourism environment in the South China Sea Islands,to achieve the sound development of island tourism in the South China Sea.Therefore,based on the study of the geographical environment and geographical background of the South China Sea Islands,the mechanism analysis method is used to form three interpretation systems.First,interpretation system of meridional causality mechanism.4 evaluation levels and 52 indicators are screened out,and the mathematical and physical criteria for each indicator is established.Second,interpretation system of latitudinal factor relationship mechanism.The AHP is used to obtain the weights of each index,and the contribution rate of factor at each level to the vulnerability is determined.Third,sharing platform of connecting meridional and latitudinal interpretation system.Likert 5-level scale is used to make the factors belong to different orders of magnitude,and factors from different systems could be comparable.Finally,through the formulation of mathematical and chemical standards of indexes and weights of evaluation indexes,a comprehensive evaluation model for vulnerability of tourism environment in the South China Sea Islands is established.

Evaluation of Farmland Drainage Water Quality by Fuzzy–Gray Combination Method

The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.

Optimum Design for the Magnification Mechanisms Employing Fuzzy Logic-ANFIS

To achieve high work performance for compliant mechanisms of motion scope,continuous work condition,and high frequency,we propose a new hybrid algorithm that could be applied to multi-objective optimum design.In this investigation,we use the tools of finite element analysis(FEA)for a magnificationmechanism to find out the effects of design variables on the magnification ratio of the mechanism and then select an optimal mechanism that could meet design requirements.A poly-algorithm including the Grey-Taguchi method,fuzzy logic system,and adaptive neuro-fuzzy inference system(ANFIS)algorithm,was utilized mainly in this study.The FEA outcomes indicated that design variables have significantly affected on magnification ratio of the mechanism and verified by analysis of variance and analysis of the signal to noise of grey relational grade.The results are also predicted by employing the tool of ANFIS in MATLAB.In conclusion,the optimal findings obtained:Its magnification is larger than 40 times in comparison with the initial design,the maximum principal stress is 127.89MPa,and the first modal shape frequency obtained 397.45 Hz.Moreover,we found that the outcomes obtained deviation error compared with predicted results of displacement,stress,and frequency are 8.76%,3.6%,and 6.92%,respectively.

Intelligent Fault Detection of Retainer Clutch Mechanism of Tractor by ANFIS and Vibration Analysis

In this study, ANFIS, as decision support system, is applied to detect the faults of MF 285 mechanism tractor clutch. Maintenance mechanisms include normal mode, rolling element failure, seal failure and attrition-based. Experiments were carried out in three speeds: 1000, 15,000, 2000 RPM and two conditions. The sensor was mounted vertically and horizontally. Vibrating spectrum of the time domain and the frequency of vibration data were obtained. Thirty-three statistical parameters of vibration signals in frequency domain and time were chosen as the sources attribute to detect errors. Finally, the top three features as input vectors to the ANFIS were evaluated. Using statistical parameters the performance of the system was calculated with the experimental data and training of ANFIS model. The system could not provide a seal to identify the fault. Regardless of the vibration data obtained from the classification of the seal, the overall classification accuracy of the ANFIS was 99.14% in the amount of 100% of the sensor installed vertically and horizontally. The results showed that this system can be used as an intelligent diagnosis system.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

多维驱动因素联动效应对企业数字化创新的影响——基于SEM与fsQCA的实证分析

随着云计算、大数据、人工智能等数字科技蓬勃发展,数字化创新深刻影响着企业创新与运营模式。利用结构方程模型(SEM)与模糊集定性比较分析方法(fsQCA)分析技术不确定性、市场不确定性、企业家精神、组织学习、组织忘记对企业数字化创新的影响。结果发现:技术不确定性、市场不确定性、企业家精神、组织学习、组织忘记和数字化创新6个要素存在因果线性关系,并发现学习主导型、市场驱动学习型和市场主导型3条数字化创新路径,以及3条非高数字化创新路径。其中,市场驱动学习型最有可能激发数字化创新。结合结构方程模型(SEM)分析结果,比较上述6条路径发现,数字化创新的影响因素具有非对称性,3条非高数字化创新路径并不是3条高数字化创新路径的对立面。

基于模糊认知图的高铁企业国际声誉形成机制仿真分析

为探究高铁企业国际声誉形成机制的动态演化过程,采用一种结合了结构方程模型和模糊认知图的方法进行仿真分析。预测分析结果表明:宏观因素、企业能力和被感知的能力均与国际声誉呈正相关,与国际声誉之间的相关性大小排序为宏观因素>企业能力>被感知的能力。诊断分析结果表明:宏观因素是引起国际声誉变化的最根本原因。混合分析结果证明了以宏观因素为核心采取综合干预措施,对国际声誉的提升效果最好。基于分析结果,提出了高铁企业提升国际声誉的对策。这种混合方法模拟了因素间的动态交互作用,并在不同假设情景下进行仿真分析,揭示了高铁企业国际声誉形成机制的动态演化过程。研究结果有助于拓展国际声誉形成机制的知识体系,也可为高铁企业采取针对性策略提升国际声誉提供实践参考。

雾天桥梁可变限速值的效用评估及优化

为改善高速公路桥梁路段雾天环境的交通安全,文中考虑可变限速标志设置对驾驶行为的影响,从服从效应角度提出其量化评估方法,以期获得最优作用效能。文中以鄂东长江大桥为原型,选取该桥梁近年最低能见度(100 m)和自由流服务水平作为测试环境,设计3种限速策略,分别为对照组SⅠ(无限速策略)、实验组SⅡ(90~70 km/h限速策略)、实验组SⅢ(90~70~50 km/h逐级限速策略);依托驾驶模拟器,实现不同限速条件的雾天桥梁场景微观驾驶行为数据的细粒度感知,采用重复测量方差分析方法从驾驶人响应的快速性、稳定性及准确性剖析可变限速标志的作用机理及驾驶人特征表现,并通过模糊综合评价方法评估不同限速策略的有效性。研究结果表明:雾天桥梁可变限速标志能够使驾驶人更早地采取减速措施,车辆在雾区行驶过程的稳定性更好;在雾天能见度100 m情况下,90~70~50 km/h逐级限速策略的稳态频数更大,空间稳定性更好,且速度超调量和跟随比更小,响应准确性更高。模糊综合评估结果显示,90~70~50 km/h逐级限速策略作为最优方案,能够有效地提升雾区驾驶行为的调节适应能力,降低驾驶风险,提高车辆运行的稳定性。本研究成果为雾天桥梁可变限速标志的优化设置提供了解决方案,可为雾天桥梁的主动安全防控提供有效支撑。

虚拟大学颠覆性创新:一个量化评估框架的构建

针对虚拟大学是否具有颠覆性创新潜质这一问题,目前学术界虽然存在截然不同的两种观点,但所采纳研究方法却较为一致,即均以理论思辨方法展开探讨,鲜见针对虚拟大学案例展开量化评估。究其原因,在于目前学术界尚缺乏可用于虚拟大学颠覆性创新的评估框架。据此,尝试设计了一套评估框架,该框架首先基于扎根理论分析法、借助NVivo软件编码建构了六大评估维度,包括教学服务、使用相对成本、开放性、组织独立性、大学市场运作机制及质量;继而,运用层次分析法和模糊综合评价法,针对六大维度所包含各项特征指标予以量化赋分以确定各部分权重。将所构建框架应用于四所有代表性的虚拟大学(学院),评估结果较为准确地反映了四所虚拟大学(学院)的发展现状和办学水平。所构建这一评估框架,无论对于志在争夺高等教育市场份额的虚拟大学,还是对于决意维系和增强自身竞争力并顺应教育数字化改革趋势的传统大学,均具有较强的理论和实践参考价值。

匝道合流交通场景下自动驾驶汽车安全性测试评价方法

针对高速匝道交通场景提出了一种基于自然驾驶数据的自动驾驶汽车安全性评价方法。通过分析合流区冲突特征,建立碰撞时间(Time to Collision,TTC)模型、后侵占时间(Post Encroachment Time,PET)模型、最小安全换道距离(Minimum Safe Spacing,MSS)交通冲突指标计算模型来确定安全性评价指标,利用模糊聚类自然驾驶指标数据确定指标阈值范围,搭建自动驾驶汽车仿真测试试验,应用层间相关性的重要性准则权重分配方法和灰色关联评分模型,计算得到不同控制算法下自动驾驶汽车安全性的综合评价得分。结果表明,被试车辆驾驶行为与理想驾驶行为在各安全性指标的关联度分布明显,计算总体关联度,得分可以直观说明不同自动驾驶系统的综合安全性能。

农村女性劳动力人力资本差异下的辽宁省农户福利测度分析

研究不同女性人力资本水平下的农户福利状况,对我国构建和谐社会具有重要意义。利用调研数据,通过聚类分析方法将受访农村女性劳动力分为高、中、低人力资本三类,采用模糊评价法进行农户福利水平测度,得出农村女性劳动力整体人力资本水平较低,女性劳动力人力资本与农户福利水平呈现同向变动关系等结论。提出提升农村女性受教育水平、改善农村医疗卫生状况、提高女性健康资本等政策建议。

钢桥疲劳裂纹扩展行为研究及可靠度更新分析

疲劳断裂失效一直是导致钢结构桥梁发生破坏的重要原因之一。为了更好地利用断裂力学对此失效行为进行研究,开展桥梁钢板件标准疲劳裂纹扩展试验。利用金属磁记忆无损检测技术监测疲劳裂纹扩展行为,分析疲劳裂纹扩展过程中磁信号的变化情况。从理论及试验两方面探讨疲劳裂纹扩展长度磁信号量化方法,确定磁特征参数与裂纹扩展长度之间定量关系式。随后将所提关系应用于疲劳裂纹扩展剩余寿命预测确定性研究,并通过试验结果对其进行验证。最后考虑疲劳裂纹扩展的随机性及损伤信息更新的必要性,进一步开展疲劳可靠度评估研究。研究结果表明:磁信号梯度最大值可以较好地对裂纹扩展长度进行量化表征,剩余寿命预测结果与试验结果误差均在20%以内,基于磁信号的可靠性评估方法可以配合我们更好地制定桥梁维修及养护策略。

首都都市圈高速铁路通勤服务满意度评价及对策

为了解当前都市圈高速铁路通勤服务满意程度和探讨未来高速铁路通勤发展的优化方向,构建包含候车与乘坐服务、票务管理、时间效率、接驳换乘体验4个方面的高铁通勤满意度评价体系,运用因子分析-模糊综合评价法对首都都市圈高铁通勤满意度进行实证分析,得到候车乘坐服务的总体满意度较高,票务管理的总体满意度最低。揭示当前票制票价单一、接驳换乘效率低等重要影响因素,提出采用时点划分动态定价、优化通勤常客备案制度等方式优化首都都市圈高速铁路通勤服务,为提高全国都市圈高速铁路通勤运营服务质量提供了依据和建议。

基于模糊DEMATEL-超效率DEA的可再生能源发电技术综合效益评估方法

“双碳”目标下,各类可再生能源发电技术发展迅速,综合权衡不同可再生能源发电方案的综合效益对可再生能源的优化设计具有重要意义。综合考虑经济效益、环境效益、能源效益和社会效益4个层面,提出了一种基于模糊决策试验和评价实验(decision making trial and evaluation laboratory,DEMATEL)与超效率数据包络分析(data envelopment analysis,DEA)模型的可再生能源发电技术综合效益评估方法。该方法分为投入-产出指标体系构建和综合评估2个阶段。首先,利用三角直觉模糊数处理模糊评价信息,将其与DEMATEL相结合量化各指标之间相互影响关系,基于指标间逻辑分析结果建立投入-产出评估指标体系。然后,基于超效率DEA模型对各可再生能源发电方案进行评估排序,结合投入冗余和产出不足分析结果给出各方案的针对性改善建议,以期为进一步选择和确定可再生能源产业发展战略提供参考。最后以某省10类可再生能源发电单元为研究对象,基于所提研究方法进行综合评估和分析,并与多准则妥协解排序法和熵权法进行对比分析,验证了所提方法的有效性。