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- fuzzy classification model 模糊分类模型
- This paper first assort the topography of different district with the fuzzy classification, and then the expanding coefficient is gotten by the model of linear regression, so we can get more accurate information for the network planning. 本文从展线系数的特性分析入手,首先采用模糊聚类分析法进行地形分类,然后建立多元线性回归模型来确定各个区域的展线系数,有利于为路网决策提供更为准确的信息。
- Fuzzy classification systems can deal with perceptual uncertainties in classification problems. 模糊分类系统可以处理分类问题中资料的不确定性。
- Use a fuzzy classification with dynamic size feature windows to recognize and extract vacuole nucleus. 提出变尺寸特征窗口模糊分类法,对空泡状细胞核进行识别提取;
- Compared with Bayesian classification model,experimental results show SANBC has higher accuracy. 实验结果表明,与朴素贝叶斯分类模型相比,SANBC分类模型具有较高的分类正确率。
- Concrete steps of automatic fuzzy classification of text are illuminated,and algorithm of automatic fuzzy classification of text is given in detail. 文中描述了文本自动模糊分类的具体步骤，同时给出了实现文本自动模糊分类的详细算法
- Latent Semantic Index (LSI) was used to select text feature and then Boosting algorithm was proposed to integrate fuzzy classification. 首先采用潜在语义索引(LSI)对文本特征进行选择；
- The knowledge management model may subdivide for the knowledge classification model,the intelligence capital model and the social structure model. 知识管理模型可分为知识分类模型、智力资本模型和社会结构模型等三种类型。
- An example is given to illustrate that the fuzzy classification is simple in computation, flexible in application and effective in practice. 通过实例说明所建立的围岩模糊分类法是一种计算简便、应用灵活、行之有效的分类法。
- The destination of classification is to learn a classification function or classification model that can map a data item to a preassigned class. 分类的目的是学会一个分类函数或分类模型，该模型能把数据库中的数据项映射到给定类别中的某一个。
- To solve this problem, we propose a new text classification model: Latent Semantic Classification (LSC) model by extending LSI model. 针对上述问题,在扩展LSI模型的基础上,我们提出了一种新的文本分类模型:潜在语义分类模型(Latent Semantic Classification:LSC)。
- We also presents the main quality pattern of QDMS,including quality forecast model,classification model and association model. 并介绍了质量数据挖掘的主要模型及方法,包括质量预测模型、分类模型和关联模型。
- The results show that the classification model of distance discriminant analysis excellent performance, high prediction accuracy. 研究结果表明，距离判别分析模型分类性能良好，预测精度高，回判估计的误判率很低。
- ObjectiveTo build an effective and exact reorganization and classification model for the quality control of Andrographis paniculata Nees. 目的建立高效准确的穿心莲样品识别模型,为进行质量控制提供参考。
- Last allow the features overpass the classification model,which created by decision tree and Markov model,to get the nodes last classification result. 最后将得到的节点特征通过由决策树和一阶马尔可夫链结合得出的分类模型进行分类。
- BP network, fuzzy neural network and fuzzy classification are separately used for the diagnosis and analysis of several typical faults in rotating machinery in this paper, and finally their diagnosis results are contrasted. 在本文中分别运用BP网络、模糊神经网络和模糊分类系统对旋转机械中几种典型的故障进行了诊断和分析,并将它们的诊断结果进行了对比。
- Therefore,it is a puzzle to study the classification model,increase the class number and improve the detection ratio according to the classic classification algorithms. 因此，不管是分类模型的建立，还是分类类别数目的扩展和分类率的提高，难度都相当大。
- The result shows that the fuzzy classification can be nine pieces of pests that harmed seriously, such as rice leaf folder, cotton bollworm, etc.The correct recognition accuracy is over 86%. 对稻纵卷叶螟、棉铃虫等田间危害严重的9种害虫进行识别分类的识别率达86%25以上。
- The data splitting using the method maximizes the classification model accuracy and at the same time minimizes the noise percentage between the training set and the test set. 通过该方法进行数据分割，不仅提高了分类模型的分类精度，而且能够最小化训练集和测试集之间的噪声百分比。
- Last allow the features overpass the classification model, which treated by decision tree and Markov model, to get the node's last classification result. 最后将得到的节点特征通过由决策树和一阶马尔可夫链结合得出的分类模型进行分类。
