On Multi-Granulation Rough Sets with Its Applications

Recently,much interest has been given tomulti-granulation rough sets (MGRS), and various types ofMGRSmodelshave been developed from different viewpoints. In this paper, we introduce two techniques for the classificationof MGRS. Firstly, we generate multi-topologies from multi-relations defined in the universe. Hence, a novelapproximation space is established by leveraging the underlying topological structure. The characteristics of thenewly proposed approximation space are discussed.We introduce an algorithmfor the reduction ofmulti-relations.Secondly, a new approach for the classification ofMGRS based on neighborhood concepts is introduced. Finally, areal-life application from medical records is introduced via our approach to the classification of MGRS.

Cost Sensitive Multi-Granulation Preference Relation Rough Set for Ordinal Decision System

The preference analysis is a class of important issues in multi-criteria ordinal decision making.The rough set is an effective approach to handle preference analysis.In order to solve the multi-criteria preference analysis problems,this paper improves the preference relation rough set model and expands it to multi-granulation cases.Cost is also an important issue in the field of decision analysis.Taking the cost into consideration,we also expand the model to the cost sensitive multi-granulation preference relation rough set.Some theorems are represented,and the granule structure selection based on approximation quality is investigated.The experimental results show that the multi-granulation preference rough set approach with the consideration of cost has a better performance in granule structure selection than that without cost consideration.

Dualities in Covering Rough Operations

Rough set theory is a technique of granular computing. In this paper, we study a type of generalized rough sets based on covering. There are several literatures[1,40-43] exploring covering-based rough sets. Our focus of this paper is on the dualities in rough operations.

Study on covering rough sets with topological methods

The authors study the covering rough sets by topological methods. They combine the covering rough sets and topological spaces by means of defining some new types of spaces called covering rough topological (CRT) spaces based on neighbourhoods or complementary neighbourhoods. As the separation axioms play a fundamental role in general topology, they introduce all these axioms into covering rough set theories and thoroughly study the equivalent conditions for every separation axiom in several CRT spaces. They also investigate the relationships between the separation axioms in these special spaces and reveal these relationships through diagrams in different CRT spaces.

Covering-Based Soft Rough Sets

Covering-based rough sets process data organized by a covering of the universe. A soft set is a parameterized family of subsets of the universe. Both theories can deal with the uncertainties of data. Soft sets have not any restrictions on the approximate description of the object,and they might form a covering of the universe. From this viewpoint,we establish a connection between these two theories. Specifically,we propose a complementary parameter for this purpose. With this parameter,the soft covering approximation space is established and the two theories are bridged. Furthermore,we study some relations between the covering and the soft covering approximation space and obtain some significant results. Finally,we define a notion of combine parameter which can help us to simplify the set of parameters and reduce the storage requirement of a soft covering approximation space.

Properties and Relations of Several Operators Based on Covering Rough Sets

The coveting rough sets theory is a generalization of traditional rough set theory, and can also describe information with incompleteness and fuzziness in information systems. In this paper, we first provide the definitions of several upper and lower covering approximation operators on the covering approximation space. Then, we study the properties of these operators. Finally, we propose the mutual relations between approximation operators and similar relations of the operator （ I ） based on the covering rough sets.

Numerical Characterizations of Covering Rough Sets Based on Evidence Theory

Covering rough sets are improvements of traditional rough sets by considering cover of universe instead of partition.In this paper,we develop several measures based on evidence theory to characterize covering rough sets.First,we present belief and plausibility functions in covering information systems and study their properties.With these measures we characterize lower and upper approximation operators and attribute reductions in covering information systems and decision systems respectively.With these discussions we propose a basic framework of numerical characterizations of covering rough sets.

盖板件高效铣削表面粗糙度预测与工艺参数优化

为了保证7075铝合金盖板件铣削表面质量和提高铣削加工效率,进行工艺参数优化,通过响应曲面法(RSM)构建铣削加工表面粗糙度预测模型,分析铣削工艺参数对表面粗糙度的影响规律。基于表面粗糙度预测模型建立高效铣削工艺参数优化目标方程,采用改进的粒子群算法(PSO)对目标方程进行优化,运用优化后的工艺参数对某盖板件进行铣削加工。试验结果表明:采用优化后的工艺参数进行盖板件铣削加工可以满足表面粗糙度要求,验证了预测模型的准确性和改进PSO方法的可行性。

南水北调中线总干渠冰盖糙率观测分析

冰盖糙率是确定渠道冰期输水水位和流量关系的基础参数,一直是明渠冰工程研究的重点之一。鉴于当前大型混凝土渠道冰盖糙率研究成果相当匮乏,以南水北调中线总干渠石家庄以北唯一无输水建筑物的唐河节制闸—放水河节制闸渠段为研究区域,依据全线通水以来唯一生成全渠段封冻冰盖的2016年1—2月逐日水位和流量实测数据,采用伯努利能量方程和谢才-曼宁公式推求渠道糙率,定性定量分析封冻前后渠道糙率变化特征。结果表明:①研究渠段畅流期渠道糙率n b为0.0167,封冻期冰盖综合糙率n c为0.0146,冰盖下表面糙率n i为0.0118。②由于水力磨蚀作用,封冻期冰盖糙率随时间呈波动减小的趋势。③渠道一旦生成封冻冰盖,输水能力大幅降低,仅占渠道设计流量的66.7%。该研究给出了大型混凝土渠道封冻冰盖糙率和输水能力降低的确切数值,以期为冰期输水调度和类似工程设计提供科学依据。

基于集覆盖理论的覆盖信息系统属性约简方法

针对覆盖信息系统属性约简问题,提出基于集覆盖理论的覆盖信息系统属性约简方法。首先,构造覆盖信息系统的相关矩阵,通过相关矩阵诱导出覆盖信息系统的集覆盖模型,并探讨了覆盖信息系统与其诱导的集覆盖模型之间的联系,发现集覆盖模型的一个极小覆盖恰是原覆盖信息系统的一个属性约简集,从而可以将求解覆盖信息系统的属性约简问题转化为求解对应集覆盖模型的极小集覆盖问题。其次,利用集覆盖启发式算法(set covering heuristic algorithm,SCHA)在解决集覆盖问题上具有更高的精度和更好的性能,给出了基于SCHA的覆盖信息系统属性约简的求解步骤及算法。最后,通过实例验证了所提方法的可行性和有效性。

基于Rough集的交叉覆盖算法设计

This paer gives an artificial network(RCSN)combining rough set theory and covering design algorithm,which reduces condition attribute using rough set theory and designs the structure of neural network with covering de-sign algorithm. An instance shows this kind of network has the advantages of fast computation and high accuracy ;themethod also can cut down the occupying of memory and the cost of data collecting.

基于Rough集和构造性学习神经网络的经济预警模型

在深入分析人工神经网络(ANN)与粗集(Rough set)理论方法的基础上,将Rough集、构造性神经网络与宏观经济预警研究相结合,尝试建立起基于Rough集-覆盖算法的构造性神经网络宏观经济预警方法体系;结合安徽省经济数据,对该模型预警实证分析。理论和实践证明,基于Rough集-覆盖算法的构造性神经网络预警模型是有效的、可行的,且具有较高的精度,从而为动态经济预警提供一条新的途经。

覆盖广义Rough集中的隶属关系

对覆盖广义Rough集中的隶属关系、隶属函数进行了定义,并利用隶属函数定义了集合的Rough包含与Rough相等,得到一些与Paw lak的Rough集不同的性质。

强化工艺对盖板玻璃表面粗糙度影响研究

盖板玻璃表面粗糙度对其覆膜工艺有一定影响。本文研究了不同成型工艺及不同厂家单强盖板玻璃强化前后表面粗糙度的变化,溢流法为样1和样2,浮法为样3,用粗糙度仪对样品强化前后进行测试,并分析其Ra、Rz典型值及离散程度和≥0.01μm的峰谷数变化。三款样品强化前后Ra和Rz典型值变化不大,主要在其最小数量级波动;强化前/后≥0.01μm的峰谷总数量差值均≤7。综上表明强化工艺对盖板玻璃表面粗糙度无明显影响。

广东区域通风廊道识别初探

以广东省为例,通过绘制空气动力学粗糙长度,从动力学角度初步识别出通风潜力;利用数值模拟输出的冬夏季平均水平风场,结合近地面温度和粗糙长度加权后得到通风指数,发现城际尺度风道分布受季节热力差异影响,冬季通风能力显著优于夏季。将通风评价结果划分为4个等级,从广东全域尺度分冬、夏两季识别了潜在风道。

覆盖Rough集及其隶属函数

从覆盖的角度重新定义了Rough集,并用一种新的、从邻域的角度重新定义了隶属函数,得到了与Pawlak与Rough集隶属函数的一些不同的性质,而且隶属函数的意义也与Pawlak的Rough集隶属函数的意义有所不同.

完备格上的广义Rough集模型

基于way-below关系和弱way-below关系,在具有逆合对应的完备格上建立了广义Rough上下近似算子,研究了它们的基本性质,并说明本文提出的广义Rough集模型是Pawlak标准粗糙集的推广.同时,在De Morgan代数上建立了广义Rough上下近似算子,给出了相应的基本性质.

适用于明渠流及冰盖流的统一泥沙起动流速计算方法初探

冰盖是北方高寒地区河流冬季常见的一种自然现象。冰盖的出现改变了河流的运动状态,由原来的明渠流变为覆盖流。受冰盖糙率影响,垂线流速分布相应变化,进而影响河床泥沙输移。为进一步探讨冰期河床泥沙输移演变规律,基于Einstein假定,采用滚动起动模型,考虑冰盖下糙率变化、黏性淤积物干重度、相对暴露度对泥沙起动的影响,从理论上推导出了适用于冰盖流的泥沙起动流速公式,并与已有试验数据对比,相对误差集中在1%~10%之间;同时,探讨了本文公式对于明渠泥沙起动的适用性,即当冰盖糙率为0时,可视为明渠流泥沙起动流速计算公式,与实验数据对比,相对误差范围为0%~0.86%,亦可满足计算精度要求。

冬小麦覆被农田地表多层非均质混合电磁散射模型研究

冬小麦种植区域分布广泛,为监测与评估其生长信息和生长环境,本文通过引入三相混合介质模型表征植被层,引入高斯随机粗糙面表征农田粗糙地表,构建了一种冬小麦覆被农田地表的多层非均质混合电磁散射模型。首先分别对比本文提出的多层非均质混合模型与水云模型、Oh模型在冬小麦拔节期及孕穗期的后向散射系数预测结果,对本模型的有效性进行分析和验证;随后,通过分析该模型等效介电常数,并求解其电磁散射及辐射传输方程,获取植被生长信息、植被含水率及土壤粗糙度等因素对覆被农田地表等效介电常数和雷达后向散射系数的影响规律。结果表明,本文提出的多层非均质混合模型与水云模型及Oh模型预测结果有较好的一致性,同时与双弥散模型获得的小麦层等效介电常数R2分别为0.9817、0.9922、0.9863、0.9711,同样具有较好的一致性;此外,本文提出的模型对拔节期、孕穗期小麦含水率的预测结果与实际测量值的均方根误差分别为0.88%、4.65%,该模型能够较好地模拟覆被农田地表电磁散射特征,为后续无人机微波反演冬小麦生长及土壤水分信息提供坚实理论基础。

模拟草被覆盖下坡面水流阻力特性试验研究

探究植被覆盖下的坡面流阻力特性对土壤侵蚀模型的建立有着重要意义。通过3个坡度、7个流量和10个草被覆盖度下的定床冲刷实验,系统分析坡面薄层水流的流型流态与阻力特性。实验结果表明,坡面水流流态受到草被覆盖度与坡度的综合影响,主要分布在层流区及过渡流区。通过等效粗糙度和坡面水流流动阻力规律,推导出等效阻力系数f_(e)的计算公式,公式表明草被覆盖度是影响水流阻力的重要因素,f_(e)值随覆盖度增加而整体增大,实验结果显示当覆盖度在0%~37.68%的范围内时,等效阻力系数始终小于1.5;而当覆盖度在56.52%~94.2%的范围内时,f_(e)由0.697~3.042增长至2.440~14.393。淹没度及雷诺数对等效阻力系数的影响与覆盖度密切相关,覆盖度低于18.84%时,等效阻力系数随淹没度与雷诺数的增加而呈减小趋势;而当覆盖度高于65.94%时,等效阻力系数随淹没度与雷诺数的增加而以较大的速率上升。研究结果以期为水土流失综合治理提供理论支撑。