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In this thesis, the methods of surrounding rock masses stability classification on the basis of the geological documentation of muck and the boring parameters of TBM are approached, especially as follows:①The geological documentation of muck and the boring parameters of TBM in the Yellow River Diversion Project.of shanxi province is summarized systematically;②Based on the geological documentation of muck and the boring parameters of TBM, that whether the common methods of surrounding rock masses stability (the methods of regular factor classification) classification are feasible, is carried on the discussion;③According to the corresponding relation of muck and the boring parameters of TBM and the surrounding rock masses stability type, the extension assessment method of tunnel surrounding rock masses stability classification is set up, also the corresponding fortran calculation procedure worked out, and not only rational result in conformity with the reality can be obtained, but also the stability situation of surrounding rock masses in front of the working range can be predicted according to the change of the dependent value in the application instance of Yellow River Diversion Project;④Combining with the application instance of Yellow River Diversion Project, extension assessment method in the application of surrounding rock masses stability classification is compared and verificated in detail by applying fuzzy synthesis method by forefathers, and a certain degree discussion and summary about the application achievement of surrounding rock masses stability classification, which is assessed by extension assessment method and fuzzy synthesis method, are carried on.

本文基于渣料和TBM掘进参数的地质编录提供的地质信息进行了围岩稳定分类方法的探讨,重点进行:①对引黄工程中渣料和TBM掘进参数的地质编录的系统整理;②基于渣料和TBM掘进参数的地质编录获得的地质信息,对常用围岩稳定分类方法是否能够进行围岩稳定分类进行了探讨;③根据渣料和TBM掘进参数与围岩稳定类型的对应关系,应用可拓理论,建立了隧洞围岩稳定分类的可拓评价方法,还编制了相应的fortran计算程序,并在引黄工程的应用实例中不仅取得了与客观实际相符的合理结果,而且根据其关联度值的变化能够预测临近掌子面前方围岩的稳定情况;④结合引黄工程的应用实例运用模糊综合评判方法对可拓评判方法在围岩稳定分类中的应用进行了详细的验证、比较,并对前人在运用可拓学和模糊数学进行岩体稳定评判的应用成果方面,进行了一定的探讨、总结。

With the found of new Rhizobium resources and development of science and technology,Rhizobium taxonomy has transfer from tradition classification to modern systematic taxonomy.

随着根瘤菌资源的不断发现和科学技术的不断发展,根瘤菌分类从以互接种族为依据的传统分类逐步过渡到了以系统发育关系为依据的现代系统分类,特别是近十几年来,生物技术应用于根瘤菌系统发育及其分类的研究进一步促进了根瘤菌资源的开发利用,使得根瘤菌的分类及其系统发育研究有了突破性进展。

Some new basic concepts are proposed in this paper, including the approximation space of generalization, rough approximation axiom, disturbance set axiom, classification principle of rough set, principle of nondeterministic even set, principle classification, bit quantum symmetric classification, of concentration, game classification, quantum logic incomparable set, bit space set, protocol relation, rough set function of protocol relation, rough classification algebra, rough simple algebra, etc., and a guess is also proposed.

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。

UDI dataset is used to verify the validation of the ABC. Experimental results show that the ABC has higher classification accuracy, with 5% average improvement, than the naive Bayes one has. Especially, for the dataset containing strong associated attributes, 37% improvement in accuracy is obtained.

应用UDI数据集对分类器进行了测试,分类结果表明,ABC算法的分类准确率明显高于朴素贝叶斯分类算法,平均提高5%,特别是对属性间有着较强依赖关系的数据集,其分类准确率提高了37%。

This dissertation brings forward and realizes the multilevel classifiable method which is based on characters coding. Above all, this method realizes the first-grade classification by extracting enough effective characters from characters and coding them, to the others which couldn't be recognized by the first-grade classification, the method will adopt the second-grade classification using template matching to recognize these characters.

本文使用了基于特征编码的多级分类识别方法,通过给字符抽取足够多的有效的特征并给特征编码实现第一级分类,对于第一级分类后仍不能区分的字符,再进入第二级分类用模板匹配的方法最终达到区分的目的,这种方法的重点在第一级分类阶段。

This dissertation brings forward and realizes the multilevel classifiable method which is based on characters coding. Above all, this method realizes the first-grade classification by extracting enough effective characters from characters and coding them, to the others which coundn t be recognized by the first-grade classification, the method will adopt the second-grade classification using template matching to recognize these characters.

本文提出并实现了基于特征编码的多级分类识别方法,通过给字符抽取足够多的有效的特征并给特征编码实现第一级分类,对于第一级分类后仍不能区分的字符,再进入第二级分类用模板匹配的方法最终达到区分的目的,这种方法的重点在第一级分类阶段。

As the method of summary classific ation does not fit with automatic summarization classification,automatic summar ization is classified using different standards in the paper. The classification is based on the features of automatic summarization.

目前 ,文摘的分类方法不适用于自动文摘的分类,因此,本文试着从多角度对自动文摘系统进行了分类,这样的分类根据自动文摘的特点进行的划分,是对自动文摘分类的一种总结,可以作为构造自动文摘系统和思考自动文摘发展方向的参考和借鉴。

This paper expatiated the characters about different kinds of Remote Sensing data and application ranges ,then analysed synthetically current primary image classification methods.On this base, the paper summarized routine statistic methods, artificial intelligence classificational methods , basing on factual condition to classify and else new methods,etc.Land use/cover ; remote sensing

本文阐述了不同类型遥感资料的性质及应用范围,并在综合分析研究当前主要的遥感图像分类方法基础上,对常规的统计分类方法、人工智能分类方法、针对实际情况的分类方法及其它较新的分类方法进行了综述。

Firstly, the paper, combining the characteristic of synchronous pulse bursts and inhibition with the modified PCNN model, presents a way of finding the foveation points in the images adaptively and effectively, and simulates the human vision system. Secondly, PCNN is extended to PCNNs, based on the properties of information couple and transmission, an algorithm that is used to fuse images of the same target got by several sensors to an image is presented to simulate the human vision system. Thirdly, combining the properties of synchronous pulse bursts, capture, and transmission and competition of waves, the paper presents two ways of classification, one is an algorithm based on the properties of neuron to capture and inhibit to classify the data taking on any complex unlinear distribution robustly, the other is based on the restricted distance and modified of the former to remove the influence of inferior samples in classification; Finally, based on the accumulative difference pictures, and the forming and transmission of PCNN wave, selecting and controlling the direction of autowave by connecting the neighbouring neurons selectively, the paper presents a way to simulate the tracks of moving object and detect the moving direction.

首先结合PCNN的同步脉冲发放和侧抑制特性,提出了基于改进型PCNN的图像凹点检测算法,该算法是一种自适应而有效的图像凹点检测方法,并且较好地仿真了人类视觉系统;然后,结合信息传递和信息耦合特性,将PCNN扩展成PCNNs,提出了一种基于PCNNs的图像融合算法,能够将多个传感器获取的同一目标的图像信息融合到一幅图像中,有效模拟了人类视觉系统;另外,结合PCNN的同步脉冲发放特性、捕获特性和波的传播竞争特性,开拓地将PCNN用于模式分类中,提出了基于耦合神经元点火捕获/抑制特性的分类方法和改进的约束距离下的PCNN分类方法,前者可实现对样本空间中任意复杂分布训练样本的稳健非线性分类,而后者能够消除训练样本中刺点对分类的影响;最后,结合累积差分图像思想、PCNN波的形成与传播特性,通过各神经元之间连接取向来选择与控制自动波的流向,将PCNN用于运动视觉分析中的运动轨迹模拟及运动方向检测。

The objective of this course is to introduce taxonomic characters and phylogeny during each orders of Class Insecta. Lectures include the history, catalogue, nomenclature, identification, description, type specimen, external morphological characters of 32 orders, systematic, phylogeny and theory of entomo-taxonomy.

本课程主要介绍昆虫纲各目的分类特徵及分类系统;课程内容包括昆虫分类学之发展史、分类阶层、昆虫命名、昆虫鉴定、特徵描述、模式标本、32目各目之外表形态构造及其诊断鉴定特徵、分类系统及分类学说等。

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Lugalbanda was a god and shepherd king of Uruk where he was worshipped for over a thousand years.

Lugalbanda 是神和被崇拜了一千年多 Uruk古埃及喜克索王朝国王。

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