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挖掘变化知识的可拓数据挖掘研究

陈文伟

《中国工程科学》 2006年第8卷第11期页码 70-73

摘要：

规范了可拓信息与可拓知识基本概念，即在信息和知识的概念上扩充了变化的信息和变化的知识。明确了可拓数据挖掘概念以及可拓推理新概念。证明了可拓数据挖掘两个定理和可拓推理公式。提出的从挖掘静态知识的数据挖掘扩展到挖掘变化知识的可拓数据挖掘，为数据挖掘开辟了新的研究方向，并通过实例进行了说明。

关键词：可拓信息可拓知识可拓数据挖掘可拓推理

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Methodological considerations for redesigning sustainable cropping systems: the value of data-mininglarge and detailed farm data sets at the cropping system level

Nicolas MUNIER-JOLAIN, Martin LECHENET

《农业科学与工程前沿（英文）》 2020年第7卷第1期页码 21-27 doi: 10.15302/J-FASE-2019292

摘要：

Redesigning cropping and farming systems to enhance their sustainability is mainly addressed in scientific studies using experimental and modeling approaches. Large data sets collected from real farms allow for the development of innovative methods to produce generic knowledge. Data mining methods allow for the diversity of systems to be considered holistically and can take into account the diversity of production contexts to produce site-specific results. Based on the very few known studies using such methods to analyze the crop management strategies affecting pesticide use and their effect on farm performance, we advocate further investment in the development of large data sets that can support future research programs on farming system design.

关键词： data mining holistic Integrated Pest Management economics DEPHY network.

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Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient

《医学前沿（英文）》页码 596-609 doi: 10.1007/s11684-021-0868-z

摘要： Sialic acid binding Ig-like lectin 10 (Siglec10) is a member of innate immune checkpoints that inhibits the activation of immune cells through the interaction with its ligand CD24 on tumor cells. Here, by analyzing public databases containing 64 517 patients of 33 cancer types, we found that the expression of Siglec10 was altered in 18 types of cancers and was associated with the clinical outcomes of 11 cancer types. In particular, Siglec10 was upregulated in patients with kidney renal clear cell carcinoma (KIRC) and was inversely associated with the prognosis of the patients. In 131 KIRC patients of our settings, Siglec10 was elevated in the tumor tissues of 83 (63.4%) patients compared with that in their counterpart normal kidney tissues. Moreover, higher level of Siglec10 was associated with advanced disease (stages III and IV) and worse prognosis. Silencing of CD24 in KIRC cells significantly increased the number of Siglec10-expressing macrophages phagocytosing KIRC cells. In addition, luciferase activity assays suggested that Siglec10 was a potential target of the transcription factors c-FOS and GATA1, which were identified by data mining. These results demonstrate that Siglec10 may have important oncogenic functions in KIRC, and represents a novel target for the development of immunotherapies.

关键词： innate immune checkpoint Siglec10 kidney renal clear cell carcinoma

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基于复杂类型数据的发现特征子空间模型(DFSSM)的研究

杨炳儒,唐菁

《中国工程科学》 2003年第5卷第1期页码 56-61

摘要：

探讨围绕知识发现领域中较为宏观、较为重大的问题。首先，根据复杂类型数据（包括Web数据、多媒体数据、空间数据、时间序列数据等）所具有的非线性动力学性质和特征，采用模式（定义为Hilbert空间中的矢量）来定量地表征复杂类型数据的多变性及具有的不确定状态和行为，并用模式的变化来刻画其整体知识发现过程的发展和演变规律；其次，以知识发现系统内在机理的研究为基础，构造了复杂类型数据知识发现系统的总体结构模型——发现特征子空间模型DFSSM；最后，用基于Web的文本挖掘系统和基于图像信息（气象云图）的知识发现系统作为实例进行了验证，结果表明DFSSM方法对于非结构化的文本数据及图像数据类型的知识发现过程具有指导性作用。因此，该结构模型具有较好的实用性与普适性，有望拓展到其他复杂类型数据的知识发现过程中。

关键词：复杂类型数据数据挖掘文本挖掘

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A building-based data capture and data mining technique for air quality assessment

Ni SHENG, U Wa TANG

《环境科学与工程前沿（英文）》 2011年第5卷第4期页码 543-551 doi: 10.1007/s11783-011-0369-4

摘要： Recently, a building-based air quality model system which can predict air quality in front of individual buildings along both sides of a road has been developed. Using the Macau Peninsula as a case study, this paper shows the advantages of building-based model system in data capture and data mining. Compared with the traditional grid-based model systems with input/output spatial resolutions of 1–2 km, the building-based approach can extract the street configuration and traffic data building by building and therefore, can capture the complex spatial variation of traffic emission, urban geometry, and air pollution. The non-homogeneous distribution of air pollution in the Macau Peninsula was modeled in a high-spatial resolution of 319 receptors·km . The spatial relationship among air quality, traffic flow, and urban geometry in the historic urban area is investigated. The study shows that the building-based approach may open an innovative methodology in data mining of urban spatial data for environmental assessment. The results are particularly useful to urban planners when they need to consider the influences of urban form on street environment.

关键词： traffic air pollution spatial distribution high resolution geographic information system

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Shear stress distribution prediction in symmetric compound channels using data mining and machine learning

Zohreh SHEIKH KHOZANI, Khabat KHOSRAVI, Mohammadamin TORABI, Amir MOSAVI, Bahram REZAEI, Timon RABCZUK

《结构与土木工程前沿（英文）》 2020年第14卷第5期页码 1097-1109 doi: 10.1007/s11709-020-0634-3

摘要： Shear stress distribution prediction in open channels is of utmost importance in hydraulic structural engineering as it directly affects the design of stable channels. In this study, at first, a series of experimental tests were conducted to assess the shear stress distribution in prismatic compound channels. The shear stress values around the whole wetted perimeter were measured in the compound channel with different floodplain widths also in different flow depths in subcritical and supercritical conditions. A set of, data mining and machine learning algorithms including Random Forest (RF), M5P, Random Committee, KStar and Additive Regression implemented on attained data to predict the shear stress distribution in the compound channel. Results indicated among these five models; RF method indicated the most precise results with the highest value of 0.9. Finally, the most powerful data mining method which studied in this research compared with two well-known analytical models of Shiono and Knight method (SKM) and Shannon method to acquire the proposed model functioning in predicting the shear stress distribution. The results showed that the RF model has the best prediction performance compared to SKM and Shannon models.

关键词： compound channel machine learning SKM model shear stress distribution data mining models

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Study of operation optimization based on data mining technique in power plants

LI Jianqiang, LIU Jizhen, GU Junjie, NIU Chenglin

《能源前沿（英文）》 2007年第1卷第4期页码 457-462 doi: 10.1007/s11708-007-0067-1

摘要： The determination of operation optimization value is very important for economic analysis and operation optimization in power plants. The operation optimization value determined by traditional methods usually cannot reflect the ac

关键词： traditional optimization determination economic analysis important

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A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

《工程管理前沿（英文）》 2020年第7卷第1期页码 27-46 doi: 10.1007/s42524-020-0092-6

摘要： The era of big data brings unprecedented opportunities and challenges to management research. As one of the important functions of management decision-making, evaluation has been given more functions and application space. Exploring the applicable evaluation methods in the big data environment has become an important subject of research. The purpose of this paper is to provide an overview and discussion of systematic evaluation and improvement in the big data environment. We first review the evaluation methods based on the main analytic techniques of big data such as data mining, statistical methods, optimization and simulation, and deep learning. Focused on the characteristics of big data (association feature, data loss, data noise, and visualization), the relevant evaluation methods are given. Furthermore, we explore the systematic improvement studies and application fields. Finally, we analyze the new application areas of evaluation methods and give the future directions of evaluation method research in a big data environment from six aspects. We hope our research could provide meaningful insights for subsequent research.

关键词： big data evaluation methods systematic improvement big data analytic techniques data mining

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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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可拓学在数据挖掘中的应用初探

李立希,李铧汶,杨春燕

《中国工程科学》 2004年第6卷第7期页码 53-59

摘要：

可拓学在数据挖掘中的应用是多方面的，其特点是挖掘“不行变行”的规律。可拓方法丰富了数据挖掘的内容，为多值型关联规则的建立提供了新的工具。提出的可拓数据挖掘模式，有利于利用现存数据更好地为决策服务。

关键词：可拓学可拓集合可拓方法数据挖掘

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关联规则挖掘算法综述

毕建欣,张岐山

《中国工程科学》 2005年第7卷第4期页码 88-94

摘要：

介绍了关联规则挖掘算法的基本原理，并按照挖掘中涉及到的变量数目（维数）、数据的抽象层次和处理变量的类别（布尔型和数值型），依次对关联规则挖掘算法的研究进行综述，并对一些典型的算法进行分析和比较，最后展望了关联规则挖掘算法的研究方向。

关键词：数据挖掘关联规则算法综述

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用于介观模拟电子束选区熔化的数据挖掘技术 Article

钱亚, 闫文韬, 林峰

《工程（英文）》 2019年第5卷第4期页码 746-754 doi: 10.1016/j.eng.2019.06.006

摘要：

在电子束选区熔化技术（EBSM）工艺中，制造部件的性质受到每一道熔道沉积质量的影响。然而，熔道的形成受到各种物理现象和工艺参数的支配，这些参数之间的相关性十分复杂，难以通过实验得出。近来，介观建模技术已成为模拟电子束（EB）熔化过程以及揭示特定熔道形貌的形成机制的手段。尽管如此，人们对工艺参数与熔道特征之间的相关性尚未有定量的理解。本文从介观模拟的结果出发，研究了熔道的形态特征，同时引入了熔道宽度和高度等关键性描述指标，以便从数值上评估沉积质量。本文还定量研究了各种工艺参数的影响，从而导出了工艺条件和熔道特征之间的相关性。最后，本文提出了一种由介观建模和数据挖掘技术组成的仿真驱动优化框架，并讨论了框架的潜力和局限性。

关键词：电子束选区熔化介观模型数据挖掘

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基于灰色系统理论的时序数据挖掘技术

刘斌,刘思峰,党耀国

《中国工程科学》 2003年第5卷第9期页码 32-35

摘要：

阐述了嵌入知识的数据挖掘思想和数据挖掘技术现状，结合灰色系统理论首次提出了时序数据挖掘的灰色系统方法集（GDMS），并以灰色系统中的GM（1,1）模型为例，介绍了其具体算法。应用此算法对上海市2002～2005年的上网户数进行了预测。

关键词：灰色系统嵌入知识 GDMS 预测

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数字采矿技术在岩爆风险评估中的应用

Sousa Luis Ribeiro e,Miranda Tiago,Sousa Rita Leal e,Tinoco Joaquim

《工程（英文）》 2017年第3卷第4期页码 552-558 doi: 10.1016/J.ENG.2017.04.002

摘要：

目前在世界范围内的很多地下矿山，岩爆已经成为一个与矿山采矿生产密切相关的重要现象。深入理解这类现象，不仅有助于岩爆管理，而且还有可能节约采矿成本，减少人身伤亡事故。其中，实验室实验是深入研究岩爆机理的一个重要途径。在本文作者前期的研究中，已经建立了实验室岩爆实验数据库。与此同时，借助于数字采矿技术，也建立了岩爆最大应力和岩爆风险指数的预测模型。为实现基于矿山地质条件和矿山井巷建筑结构特性对岩爆类型即岩爆强度等级的准确预测，本文的重点是，基于对岩爆实例的分析来建立岩爆影响矩阵，明确岩爆现象的诱发因子，并厘清这些影响因子之间的相互关系。运用人工神经网络（ANN）和初始贝叶斯分类器等数字矿山技术，对矿山岩爆数据库进行了更深入的研究。最后给出了研究得出的各项结论。

关键词：岩爆数字采矿贝叶斯网络原位数据库

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免疫进化机制及其在时序模式挖掘中的应用研究

杨炳儒,秦奕青,宋泽锋

《中国工程科学》 2008年第10卷第4期页码 84-89

摘要：

针对目前动态数据挖掘中存在的问题，提出基于数据增量的动态挖掘进程概念；在动态挖掘进程和生物免疫进化过程的相似性基础上，提出了知识发现中的免疫进化机制的基本内涵；给出了基于免疫进化机制的时序模式挖掘算法及其实验分析，以验证理论的正确性和有效性。

关键词：动态数据挖掘免疫算法动态挖掘进程免疫进化机制时序模式挖掘

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标题作者时间类型操作

挖掘变化知识的可拓数据挖掘研究

陈文伟

期刊论文

Methodological considerations for redesigning sustainable cropping systems: the value of data-mininglarge and detailed farm data sets at the cropping system level

Nicolas MUNIER-JOLAIN, Martin LECHENET

期刊论文

Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient

期刊论文

基于复杂类型数据的发现特征子空间模型(DFSSM)的研究

杨炳儒,唐菁

期刊论文

A building-based data capture and data mining technique for air quality assessment

Ni SHENG, U Wa TANG

期刊论文

Shear stress distribution prediction in symmetric compound channels using data mining and machine learning

Zohreh SHEIKH KHOZANI, Khabat KHOSRAVI, Mohammadamin TORABI, Amir MOSAVI, Bahram REZAEI, Timon RABCZUK

期刊论文

Study of operation optimization based on data mining technique in power plants

LI Jianqiang, LIU Jizhen, GU Junjie, NIU Chenglin

期刊论文

A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

期刊论文

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

YANG Ping

期刊论文

可拓学在数据挖掘中的应用初探

李立希,李铧汶,杨春燕

期刊论文

关联规则挖掘算法综述

毕建欣,张岐山

期刊论文

用于介观模拟电子束选区熔化的数据挖掘技术

钱亚, 闫文韬, 林峰

期刊论文

基于灰色系统理论的时序数据挖掘技术

刘斌,刘思峰,党耀国

期刊论文

数字采矿技术在岩爆风险评估中的应用

Sousa Luis Ribeiro e,Miranda Tiago,Sousa Rita Leal e,Tinoco Joaquim

期刊论文

免疫进化机制及其在时序模式挖掘中的应用研究

杨炳儒,秦奕青,宋泽锋

期刊论文

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