APPLICATION OF ROUGH SET THEORY TO MAINTENANCE LEVEL DECISION-MAKING FOR AERO-ENGINE MODULES BASED ON INCREMENTAL KNOWLEDGE LEARNING

The maintenance of an aero-engine usually includes three levels,and the maintenance cost and period greatly differ depending on the different maintenance levels.To plan a reasonable maintenance budget program, airlines would like to predict the maintenance level of aero-engine before repairing in terms of performance parameters,which can provide more economic benefits.The maintenance level decision rules are mined using the historical maintenance data of a civil aero-engine based on the rough set theory,and a variety of possible models of updating rules produced by newly increased maintenance cases added to the historical maintenance case database are investigated by the means of incremental machine learning.The continuously updated rules can provide reasonable guidance suggestions for engineers and decision support for planning a maintenance budget program before repairing. The results of an example show that the decision rules become more typical and robust,and they are more accurate to predict the maintenance level of an aero-engine module as the maintenance data increase,which illustrates the feasibility of the represented method.

Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and cost-effectiveness.This paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse data.When it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,respectively.We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying properties.We present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these principles.These operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and subtlety.We highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making field.We use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted data.Additionally,we developed a novel technique by combining the IFSs with quaternion numbers.We establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making problems.Using the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately woven with the complexity ofmedical evaluation in order to thoroughly assess the relevance and efficacy of the suggested methodology.

Process Auxiliary Decision-making Based on Rough Sets and Regulation Distance Computing

Computer aided process planning（CAPP） is an important content of computer integrated manufacturing, and intelligentizing is the orientation of development of CAPP. Process planning has characters of empirical and time-consuming to finalize, and the same technical aim always can be achieved by different process schemes, so intelligentizing of process decision making always be a difficult point of CAPP and computer integrated manufacturing （CIM）. For the purpose of intelligent aided process decision making and reuse of process resource, this paper proposed a decision making method based on rough sets（RS） and regular distance computing. The main contents and methods of process planning decision making are analyzed under agile response manufacturing environment, the concept of process knowledge granule is represented, and the methods of process knowledge granule partitioning and granularity analysis are put forward. Based on the theory of RS and combined the method of process attributes importance identification, the paper brought forward a computing model for process scheme regulation distance under the same attribute conditions, and conflict resolution strategy was introduced to acquire process scheme fit for actual situation of enterprise＇s manufacturing resources, so as to realize process resources＇ conflict resolution and quick excavate and reuse of enterprises＇ existing process knowledge, to advance measures of process decision making and improve the rationality and capability of agile response of process planning.

One Direction Rough Law Generation and Its Security Transmission

By using function one direction S-rough sets （function one direction singular rough sets）, the concept of one direction rough law is proposed, where one direction rough law is the law pair { w（x）-, w（x） - } composed by w（x）- and w（x）-, ffthe attribute set {a_ , a-} of function one direction S-rough sets changes, then one direction rough law { w（x）_, w（x）- } will change, too. By employing ellipse curves, the concept of one direction rough law security is presented, the security theorem of one direction rough law is proposed and the applications are given. One direction rough law security, which is generated by the intersection and penetration between function one direction S-rough sets and ellipse curves, is a new applied research direction of function S-rough sets.

Analysis on decision-making model of plan evaluation based on grey relation projection and combination weight algorithm

In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.

Driving decision-making analysis of car-following for autonomous vehicle under complex urban environment

The decision-making under complex urban environment become one of the key issues that restricts the rapid development of the autonomous vehicles. The difficulty in making timely and accurate decisions like human beings under highly dynamic traffic environment is a major challenge for autonomous driving. Car-following has been regarded as the simplest but essential driving behavior among driving tasks and has received extensive attention from researchers around the world. This work addresses this problem and proposes a novel method RSAN(rough-set artificial neural network) to learn the decisions from excellent human drivers. A virtual urban traffic environment was built by Pre Scan and driving simulation was conducted to obtain a broad set of relevant data such as experienced drivers' behavior data and surrounding vehicles' motion data. Then, rough set was used to preprocess these data to extract the key influential factors on decision and reduce the impact of uncertain data and noise data. And the car-following decision was learned by neural network in which key factor was the input and acceleration was the output. The result shows the better convergence speed and the better decision accuracy of RSAN than ANN. Findings of this work contributes to the empirical understanding of driver's decision-making process and it provides a theoretical basis for the study of car-following decision-making under complex and dynamic environment.

Grinding Characteristics Of Directionally Aligned SiC Whisker Wheel - Comparison With A12O3 Fiber Wheel

A unique SiC whisker wheel was invented,in which the whiskers were aligned normally to the grinding wheel surface.In this paper,grindabilities of the SiC whisker wheel are investigated and compared with those of other wheels of SiC grains,Al2O3 grains,as well as Al2O3 long and short fibres which were also aligned normally to the grinding wheel surface,respectively.The main research contents concern grinding characteristics of a directionally aligned SiC whisker wheel such as material-removal volume,wheel-wear rates,integrity of the ground surfaces,grinding ratios and grinding efficiency.Furthermore,grinding wheels of whiskers and fibres have a common disadvantage:they tend to load easily.The authors have proposed a simple method of loading-free grinding to overcome this propensity and investigate some related grinding characteristics under loading-free grinding conditions.

切向车铣18CrNiMo7-6钢V形缺口表面三维形貌研究

疲劳试样的缺口加工一直是一个亟需解决的难题。提出一种全新的切向车铣加工缺口工艺,通过理论与试验结合的方法探究了切向车铣对V形缺口表面形貌的影响规律。结果表明:在不同的工艺参数下,切向车铣V形缺口底部会呈现出不同的加工纹理方向,提出的理论公式计算出的纹理方向与工件轴线的夹角与实际结果误差很小;缺口底部三维表面粗糙度R_(a)随着铣刀转速n_(c)的升高而减小,随着工件转速n_(w)的升高而变大,随着每齿进给量f_(z)的增加先减小后增大;得到表面粗糙度最优参数组合为n_(c)=6000 r/min,n_(w)=100 r/min,f_(z)=0.0375μm,在此切削参数组合下得到的V形缺口表面粗糙度R_(a)可达到0.075μm。

基于直驱机床的航空整体叶轮加工效率优化方法研究

为解决航空叶轮在复杂五轴联动加工过程中的效率和精度控制难题,本文基于直驱机床围绕加工参数对表面粗糙度和加工时间的影响进行了深入分析。首先通过与传统机床进行加工对比,证明了直驱机床的精度与速度方面的优势;其次针对原点坐标的研究揭示了原点位置对加工效率的影响,尤其是当原点接近A、C轴中心时,加工效率显著提高;最后通过正交试验法研究了转速、每齿进给量、切宽这3个关键因素,并发现每齿进给量是影响表面粗糙度的主导因素,其次是切宽,而转速的影响较小。在保证粗糙度小于1.6μm的前提下,以转速20000 r/mim、每齿进给量0.03 mm、切宽0.6 mm的参数组合获得最优结果。基于优化的工艺参数不仅提升了加工效率,节约了43.3%的加工时间,还确保了加工质量,为航空叶轮的精密加工提供了重要的技术参考,同时为基于直驱机床的复杂零件高效加工提供实践指导和理论依据。

基于机器学习的岩体结构面剪切破坏区域预测研究

剪切破坏区域是岩体结构面上下盘相对运动的主要接触区域,对抗剪强度具有重要影响。鉴于结构面剪切破坏区域与形貌特征的高度非线性关系,本文在分析结构面表面形貌特征及剪切机制的基础上,以粗糙度参数倾向、倾角、曲率、高差和孔径分布来描述结构面表面形貌特征。对结构面试样开展法向应力为1.0 MPa的直剪试验,通过图像分割技术提取剪切破坏区域,利用多种机器学习方法构建结构面剪切破坏区域预测模型,建立结构面粗糙度参数与破坏状态之间的非线性关系,并采用训练准确率和AUC(Area Under Curve)值等指标对模型预测性能进行评估。结果表明所建立的模型中集成装袋树预测性能最好,其次是K最近邻,其训练准确率最高分别可达98.02%和97.38%,AUC值最高分别可达0.78和0.74。通过敏感性分析发现孔径分布对剪切破坏区域的影响最大。本研究对有效分析结构面的剪切破坏机理和准确评价抗剪强度具有重要意义。

海量大数据定向采样有差别挖掘算法仿真

在大数据中,不同类别之间可能存在数据分布不均衡的情况,即某些类别的数据样本数量远远少于其他类别。这种情况下,传统的采样方法无法正确反映所有类别的特征和差异。为提升大数据信息的应用性,文中研究海量大数据定向采样有差别挖掘算法。以网站统一资源定位器(URL)初始化为基础,在网络上抓取网页,采集网页的超文本标记语言(HTML)数据,提取定向数据的相关链接,并将其导入URL队列。根据网络搜索策略,实施相关的数据搜索和处理。完成数据搜索后,将自动进行下一网页的URL,继续进行海量大数据定向采样。结合模糊特征匹配与检测滤波方法实现大数据定向采样过程中的抗干扰处理。采用粗糙集算法实施挖掘,利用扩展差别矩阵对大数据决策表内的值实施约简,实现海量大数据的模式分类。实验结果显示,该算法数据采集过程中的丢包率基本控制在0.2%以下,具有较高的鲁棒性。

F-rough law and the discovery of rough law

By using function one direction S-rough sets （function one direction singular rough sets）, this article presents the concepts of F-law, F-rough law, and the relation metric of rough law; by using these concepts, this article puts forward the theorem of F-law relation metric, two orders theorem of F-rough law relation metric, the attribute theorem of F-rough law band, the extremum theorem of F-rough law relation metric, the discovery principle of F-rough law and the application of F-rough law.

Frictional behavior of planar and rough granite fractures subjected to normal load oscillations of different amplitudes

The dynamic frictional behaviors of natural discontinuities(joints,fractures,faults)play an important role in geohazards assessment;however,the mechanisms of the dynamic fault weakening/strengthening are still unclear.In this paper,a dynamic shear box was used to perform direct shear tests on saw-cut(planar)and natural(rough)granite fractures,with different normal load oscillation amplitudes.Based on the recorded shear forces and normal displacements,the shear forces,apparent friction coefficients and normal displacements are found to change periodically with oscillated normal loads and are characterized by a series of time shifts.The observed changing patterns are similar for the rough and planar fractures.Compared with the test data under constant normal load(CNL),small/large normal load oscillation amplitude enhances/reduces the peak shear strength,with a critical point.The magnitude of critical normal load oscillation for the rough fractures is smaller than the planer fractures.The results imply that dynamic fault weakening/strengthening can be achieved by both normal load oscillation amplitudes and slip surface topography.The rough fractures with larger normal oscillation amplitude can easily cause frictional weakening under stress disturbance.

S-Rough communication and its characteristics

In view of certain defects of common rough communication, using the S-rough sets, this article presents a S-rough communication model. The S-rough communication model is the extension of the common rough communication model. S-rough communication has two kinds of forms： one-direction S-rough communication and two-direction S-rough communication. The mathematical structure and characteristics of the one-direction S-rough communication and the two-direction S-rough communication, the relationship theorem between the one-direction S-rough communication and the two-direction S-rough communication are also presented. The S-rough communication is a dynamic communication method, and it is a novel research direction in rough sets field.

Generalized dominance-based rough set approach to security evaluation with imprecise information

The model of grey multi-attribute group decision-making （MAGDM） is studied, in which the attribute values are grey numbers. Based on the generalized dominance-based rough set approach （G-DR- SA）, a synthetic security evaluation method is presented. With-the grey MAGDM security evaluation model as its foundation, the extension of technique for order performance by similarity to ideal solution （TOPSIS） integrates the evaluation of each decision-maker （DM） into a group＇s consensus and obtains the expected evaluation results of information system. Via the quality of sorting （QoS） of G-DRSA, the inherent information hidden in data is uncovered, and the security attribute weight and DMs＇ weight are rationally obtained. Taking the computer networks in a certain university as objects, the example illustrates that this method can effectively remove the bottleneck of the grey MAGDM model and has practical significance in the synthetic security evaluation.

Synthetic security assessment based on variable consistency dominance-based rough set approach

Security assessment can help understand the security conditions of an information system and yield results highly conducive to the solution of security problems in it. Taking the computer networks in a certain university as samples, this paper, with the information system security assessment model as its foundation, proposes a multi-attribute group decision-making （MAGDM） security assessment method based on a variable consistency dominance-based rough set approach （VC-DRSA）. This assessment method combines VC-DRSA with the analytic hierarchy process （AHP）, uncovers the inherent information hidden in data via the quality of sorting （QoS）, and makes a synthetic security assessment of the information system after determining the security attribute weight. The sample findings show that this method can effectively remove the bottleneck of MAGDM, thus assuming practical significance in information system security assessment.

Rough law generation and its separation-recognition

By using function S-rough sets（function singular rough sets）, this paper gives rough law generation and the theorem of rough law generation.Based on these results above, the paper proposes rough law separation, the theorem of rough law separation, the compound generation theorem of rough law bands, and the principle of rough law bands.In the end, an application of rough law separation in recognizing the risk law of profit is presented.

Rough law energy and measurement of ■-decomposition rough law

By employing function one-direction S-rough sets and rough law generation method based on function S-rough sets, ^-f-decomposition law and ^-F-decomposition rough law are proposed, and the measurement of rough law variation in the process of rough law ^-F-decomposition is researched. The concepts of law energy and attdbute ^-f-interference degree are presented, which make the variation of rough law become measurable. ^-f-decomposition law energy characteristic theorem, ^-f- decomposition law energy inequality theorem, ^-F-decomposition rough law energy characteristic theorem, and ^-f-decomposition law energy mean value theorem are presented.

Process analysis of direct laser melting to fabricate layered hybrid beads

The successful fabrication of layered hybrid beads by DLM process is limited by dissimilar melting ranges of different powders.For the application of DLM process into manufacturing industries,target mechanical properties of final product must be achieved.Process analysis was performed for the DLM fabrication of layered hybrid beads by using stainless steel (SS 316L) and titanium powders.For the analysis of fabrication characteristics,single hybrid bead was formed using SS316L powder onto the base plate and then Ti powder was melted onto the previous melted layer.In addition,multi-layer hybrid beads were fabricated for the analysis of the layering effects between them.From these studies,the effects of the processing parameters,such as laser power,scan rate and scan line spacing on surface morphology were characterized and optimum processing conditions for the DLM fabrication of layered hybrid beads were developed.

Reliable approach for bistatic scattering of three-dimensional targets from underlying rough surface based on parabolic equation

A parabolic equation （PE） based method for analyzing composite scattering under an electromagnetic wave incidence at low grazing angle, which composes of three-dimensional （3-D） electrically large targets and rough surface, is presented and discussed. A superior high-order PE version is used to improve the accuracy at wider paraxial angles, and along with the alternating direction implicit （ADI） differential technique, the computational efficiency is further improved. The formula of bistatic normalized radar cross section is derived by definition and near-far field transformation. Numerical examples are given to show the validity and accuracy of the proposed approach, in which the results are compared with those of Kirchhoff approximation （KA） and moment of method （MoM）. Furthermore, the bistatic scattering properties of composite model in which the 3-D PEC targets on or above the two-dimensional Gaussian rough surfaces under the tapered wave incidence are analyzed.