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Data mining diagnosis system based on rough set theory for boilers in thermal power plants

YANG Ping

《机械工程前沿（英文）》 2006年第1卷第2期页码 162-167 doi: 10.1007/s11465-006-0017-z

摘要： Large amounts of data in the SCADA systems databases of thermal power plants have been used for monitoring, control and over-limit alarm, but not for fault diagnosis. Additional tests are often required from the technology support center of manufacturing companies to diagnose faults for large-scale equipment, although these tests are often expensive and involve some risks to equipment. Aimed at difficulties in fault diagnosis for boilers in thermal power plants, a hybrid-intelligence data-mining system based only on acquired data in SCADA systems is structured to extract hidden diagnosis information directly from the SCADA systems databases in thermal power plants. This makes it possible to eliminate additional tests for fault diagnosis. In the system, a focusing quantization algorithm is proposed to discretize all variables in the preparation set to improve resolution near the change between normal value to abnormal value. A reduction algorithm based on rough set theory is designed to find minimum reducts from all discrete variables in the preparation set to represent diagnosis rules succinctly. The diagnosis rules mining from SCADA systems database are expressed directly by variables in the database, making it easy for engineers to understand and use in industry applications. A boiler fault diagnosis system is designed and realized by the proposed approach, its running results in a thermal power plant of Guangdong Province show that the system can satisfy fault diagnosis requirement of large-scale boilers and its accuracy rangers from 91% to 98% in different months.

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基于Rough集理论的模糊神经网络构造方法

黄显明,易继锴

《中国工程科学》 2004年第6卷第4期页码 44-50

摘要：

提出了在模糊神经网络中使用Rough集理论进行网络结构设计的方法。由于Rough集理论有强大的数值分析能力，而模糊神经网络具有准确的逼近收敛能力和较高的精度，所以通过两者的结合，可以得到一种可理解性好、计算简单、收敛速度快的神经网络模型。这种网络构造方法的主要过程为：首先，利用Rough集理论对给定数据集进行规则获取；然后，根据这些规则构造模糊神经网络各层的神经元个数及相关参数初始值；最后，用BP算法迭代求出网络的各种参数，完成网络的设计

关键词：模糊神经网络 Rough集规则获取函数拟合

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The research on structural damage identification using rough set and integrated neural network

Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG

《机械工程前沿（英文）》 2013年第8卷第3期页码 305-310 doi: 10.1007/s11465-013-0259-5

摘要：

A huge amount of information and identification accuracy in large civil engineering structural damage identification has not been addressed yet. To efficiently solve this problem, a new damage identification method based on rough set and integrated neural network is first proposed. In brief, rough set was used to reduce attributes so as to decrease spatial dimensions of data and extract effective features. And then the reduced attributes will be put into the sub-neural network. The sub-neural network can give the preliminary diagnosis from different aspects of damage. The decision fusion network will give the final damage identification results. The identification examples show that this method can simplify the redundant information to reduce the neural network model, making full use of the range of information to effectively improve the accuracy of structural damage identification.

关键词： rough set integrated neural network damage identification decision making fusion

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Reduction of rough set attribute based on immune clone selection

LIANG Lin, XU Guang-hua

《机械工程前沿（英文）》 2006年第1卷第4期页码 413-417 doi: 10.1007/s11465-006-0049-4

摘要： A novel attribute reduction approach of rough set based on immune clone selection is proposed. In this method, the approximation quality and attribute set were adopted as evolution object and antibody, respectively. On the basis of the inherent distribution within the immune response, the global optimization of the antibody was realized through parallel local optimization. Moreover, the diversity of the antibody population was maintained with the affinity maturation and renewal of the antibody. Thus, the stable multi-optimal solutions can be preserved. In addition, the machinery fault data were analyzed by this method, and the attribute reduction sets were obtained further to satisfy the demand of feature selection in machinery diagnosis.

关键词： inherent distribution maturation evolution diversity antibody

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基于粗糙集的企业技术创新能力更新方法研究

苗成林,冯俊文

《中国工程科学》 2011年第13卷第9期页码 109-112

摘要：

随着时间、环境的不断变化及企业技术创新能力的进一步要求，现有的技术创新能力已逐渐不能满足企业技术创新的要求，因此技术创新能力更新成为企业在新的要求下的一种能力行为。文章基于粗集理论研究了新要求下的企业技术创新能力更新方法，确定技术创新能力更新次序以达到更新费用最低，随后分析算法并通过实例证明其有效性。

关键词：技术创新能力更新粗糙集

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广义近似空间与粗糙分类代数

刘永红

《中国工程科学》 2006年第8卷第3期页码 39-48

摘要：

提出了广义近似空间、粗近似公理、干扰集公理、粗糙集的分类原则、粗选原则、不确定偶集原则、精选原则、对策分类、量子逻辑分类、bit量子对称分类、不可比集、bit空间集、协议关系、粗糙集函数、粗糙分类代数和粗糙单代数等基本概念，并提出了一个猜想；展示了一些新观点；基于协议关系构造了粗糙商代数和粗糙子代数，给出了回避-归并算法及算例。

关键词：广义近似空间粗糙集粗糙分类代数协议关系粗糙单代数粗糙商代数粗糙子代数

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基于粗神经网络的企业财务危机预警方法

柳炳祥,盛昭翰

《中国工程科学》 2002年第4卷第8期页码 58-62

摘要：

分析了评价财务危机的指标体系和财务危机等级的划分，论述了粗神经网络的结构和基本原理，叙述了基于粗神经网络的财务危机预警方法，并给出了一个基于粗神经网络的财务危机的预警实例。实验结果表明，该方法应用于财务危机预警中是有效的，为财务危机预警提供了一条新的研究思路和方法。

关键词：财务危机指标体系粗集神经网络预警

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不完备模糊信息系统

杨习贝,杨静宇,吴陈,傅凡

《中国工程科学》 2006年第8卷第7期页码 47-53

摘要：

以不完备模糊信息系统为研究对象，建立了其中的模糊相容关系及模糊粗糙上、下近似集。在此基础上，探讨了论域上的模糊覆盖问题并提出了覆盖的3种运算形式；定义了2种新的模糊粗糙熵以讨论不完备模糊信息系统中的不确定性因素，证明了不确定因素的变化与度量强度之间的重要关系；建立了一种度量部分模糊知识依赖的新方法，获得了一些新的定理结果证明。

关键词：不完备模糊信息系统模糊相容关系模糊粗糙集模糊覆盖模糊粗糙熵模糊知识依赖

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Smart optical-fiber structure monitoring based on granular computing

Guan LU, Dakai LIANG,

《机械工程前沿（英文）》 2009年第4卷第4期页码 462-465 doi: 10.1007/s11465-009-0073-2

摘要： Using an optic fiber self-diagnosing system in health monitoring has become an important direction of smart materials and structure research. The buried optic fiber sensor can be used to test the parameters of the composite material. The granular computing method can reach the requirement of damage detection by analyzing digital signals and character signals of the smart structure at the same time. The paper investigates an optic fiber smart layer and presents a method for realizing optic fiber smart structure monitoring and damage detection by using granular computing. After the analysis, it is presumed that optic fiber smart structure monitoring based on granular computation can identify the damage from complex signals.

关键词： smart material and structure GrC optical fiber sensor rough set clustering algorithm

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一种模糊Rough决策方法

罗党

《中国工程科学》 2004年第6卷第12期页码 32-36

摘要：

利用模糊集理论和粗糙集理论在处理不确定性和不精确性问题方面侧重点的差异性，构造一种组合决策模型。该模型从问题领域内的部分不精确信息出发利用模糊聚类方法构造一个决策信息系统，利用粗糙集理论关于决策规则的约简方法从决策信息系统中提取（挖掘）决策规则，使之适用于问题的整个领域。

关键词：模糊聚类粗糙集决策表决策规则

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一种基于粗糙集的模糊信息融合方法及应用

陈双叶,张微敬

《中国工程科学》 2006年第8卷第12期页码 75-79

摘要：

将粗糙集理论和模糊逻辑技术结合起来，提出了一种基于粗糙集数据处理的模糊信息融合方法。运用粗糙集的基本理论和简约计算方法，从大量原始数据中发现精简的、概略化的规则，结合模糊逻辑推理建立一致粗糙模糊模型，并提出了对模型进行扩充与完备化的概念。脉动真空灭菌温度控制过程的仿真试验研究结果表明了所提方法的有效性和可行性。

关键词：信息融合粗糙集模糊逻辑粗糙模糊模型

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区间值信息系统中基于信息熵的属性约简 Article

Jian-hua DAI,Hu HU,Guo-jie ZHENG,Qing-hua HU,Hui-feng HAN,Hong SHI

《信息与电子工程前沿（英文）》 2016年第17卷第9期页码 919-928 doi: 10.1631/FITEE.1500447

摘要：概要：区间值数据用来表示包含观察值的不确定性。区间值信息系统的处理有助于拓展粗糙集理论的应用范畴。属性约简是区间值数据分析的一个关键问题。现有针对传统单值数据的方法不适用于区间值数据。目前，关注区间值数据约简的研究还相对较少。本文从信息论的角度提出了一个区间值数据的属性约简框架，定义了区间值信息系统中的熵、条件熵以及联合熵等概念，继而构造了属性约简算法。实验结果表明所构造的方法是有效的。

关键词：粗糙集理论；区间值数据；属性约简；熵

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基于粗集方法的智能专家系统

曾黄麟

《中国工程科学》 2001年第3卷第2期页码 47-51

摘要：

文章主要介绍基于粗集方法的智能专家系统的基本构成、知识表达方式及学习推理方法。提出了利用不可分辨性或根据算法相容性进行知识简化，导出决策规则的方法，通过研究导师的知识与学习者的知识之间的依赖程度，找出每一概念的有用特征，进行知识简化和系统简化，导出决策规则的学习推理方法。

关键词：粗集方法智能专家系统不可分辨性知识简化决策规则

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Level set band method: A combination of density-based and level set methods for the topology optimization

Peng WEI, Wenwen WANG, Yang YANG, Michael Yu WANG

《机械工程前沿（英文）》 2020年第15卷第3期页码 390-405 doi: 10.1007/s11465-020-0588-0

摘要： The level set method (LSM), which is transplanted from the computer graphics field, has been successfully introduced into the structural topology optimization field for about two decades, but it still has not been widely applied to practical engineering problems as density-based methods do. One of the reasons is that it acts as a boundary evolution algorithm, which is not as flexible as density-based methods at controlling topology changes. In this study, a level set band method is proposed to overcome this drawback in handling topology changes in the level set framework. This scheme is proposed to improve the continuity of objective and constraint functions by incorporating one parameter, namely, level set band, to seamlessly combine LSM and density-based method to utilize their advantages. The proposed method demonstrates a flexible topology change by applying a certain size of the level set band and can converge to a clear boundary representation methodology. The method is easy to implement for improving existing LSMs and does not require the introduction of penalization or filtering factors that are prone to numerical issues. Several 2D and 3D numerical examples of compliance minimization problems are studied to illustrate the effects of the proposed method.

关键词： level set method topology optimization density-based method level set band

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Maximum independent set in planning freight railway transportation

Gainanov Damir N., Mladenovic NENAD, Rasskazova V. A.

《工程管理前沿（英文）》 2018年第5卷第4期页码 499-506 doi: 10.15302/J-FEM-2018031

摘要：

This work is devoted to the problem of planning of freight railway transportation. We define a special conflict graph on the basis of a set of acceptable train routes. The investigation aims to solve the classical combinatorial optimization problem in relation to the maximum independent set of vertices in undirected graphs. The level representation of the graph and its tree are introduced. With use of these constructions, the lower and upper bounds for the number of vertices in the maximum independent set are obtained.

关键词： independent set algorithm planning of transportation two-sided estimate