1) training sample quality
训练样本质量
1.
The rough set theory was used to study training sample quality,define relative concept and establish fault feature extraction algorithm for Artificial Neural Network fault diagnosis model.
从人工神经网络故障诊断模型的特点出发 ,利用粗糙集理论解决该模型应用中的主要问题 ,包括进行训练样本质量研究 ,定义相关概念 ,给出故障特征提取算法等 ,提出了粗糙集 神经网络智能混合系统模型 ,分析了该模型的实现步骤 ,结合具体实例验证了上述理论的正确性·利用SAS软件进行了数值仿真·结果表明 ,提出的理论较好地解决了神经网络结构、训练样本的大小、样本质量等对人工神经网络的精度及泛化能力有直接影响的问题 ,减少了训练所需的计算量和时间 ,提高了模型的正确率
2) training sample
训练样本
1.
With the Kohonen network clustering in neural network employed, the degree of relationship of the universal joint axle of the rolling mill was input to Kohonen network as the training sample, studied and clustered by the network to generate different clustering centers according to the different depth and different degree of relationship among the cracks.
利用神经网络中的Kohonen网络聚类的特点 ,把轧钢机万向接轴裂纹故障不同的关联度作为Kohonen网络的训练样本输入到Kohonen网络 ,并由网络进行学习和聚类 。
2.
Exact agricultural crops identification and planting area measure depend on not only classifiers but also training samples imported into classifiers.
准确的遥感农作物类型识别和种植面积统计,不仅仅取决于不同分类方法的选择,同时还要看输入分类器用以学习的训练样本数据,训练样本对分类精度的影响比分类技术本身对测量精度的影响还要大。
3.
Typical fault characteristics are selected as training samples and GA is used to optimize the structure and original weight distribution of BP networks.
提出了一种用故障的典型特征作为训练样本、遗传算法与BP网络相结合的模拟电路故障诊断新方法。
3) training samples
训练样本
1.
Studies on the purification of training samples in supervised classification by mode filtering;
利用众数滤波对监督分类训练样本纯化的研究
2.
A purified algorithm for training samples based on local automatic searching and spectral matching technique is presented.
提出了一种基于局部自动搜索和光谱匹配技术的监督分类训练样本的纯化方法。
3.
In this paper, using orthogonal experiment method, taking three layers feed forward neural network as a example, problem of choosing training samples, weights and bias, training parameter of neural network is analyzed and studied.
运用正交试验法,以三层前向型神经网络为例,对神经网络的训练样本、权值和阀值、训练参数的选择进行分析和研究。
4) Sample training
样本训练
1.
In this paper, relevant parameters influencing sample training precision are explored when the mixtures of experts networks is applied to boiler fault diagnosis,and the relationahip between the square sum of studying error and some parameters,such as rule numbers、studying rate、cycle numbers、weighted exponent,are presented.
探讨了将混合专家网络应用于锅炉故障诊断时,影响样本训练精度的有关参数,得出了规则数、学习率、循环次数、加权指数等参数与样本训练学习误差平方和之间的关
2.
The statistical learning theory based on sample training was applied to analyze the difference and relativity of images figures,and then the common figures and distinct figures of each sort image were catched to form the identification and classification model.
利用基于样本训练的统计学习原理,在分析各类图像样本特征上的差异和相关性的基础上,提取图像共同特征和显著特征参数集合,并加入人为启发式思想,结合先验知识的指导和计算机特征分析结果来制订特征提取规则,应用Dempster-Shafer(DS)理论的思想融合提取的多个特征,形成启发式分类模型。
补充资料:蚕茧质量监督检查和国家生丝质量检验
蚕茧质量监督检查和国家生丝质量检验
cocoon quality supervision inspection and national silk quality inspection
检验局承担并组织有关检验机构对全国已核发生产准产证的缘丝、绢纺企业的生丝、绢丝质量进行抽查检验(两年共四期),以考核生产企业生丝质量水平。中国桑蚕鲜茧评茧计价方法主要有3种:①鲜上光茧干壳量仪器评定(简称仪评)计价;②“组合售茧、嫌丝计价,’(简称“组、缎”)评茧方法;③茧层率评茧计价。国家质量技术监督局于19望)年6月7日下发了《关于加强茧丝质t监督工作的通知》,要求加强桑蚕鲜茧收购期间的质量监督执法检查;重点做好鲜茧收购过程中“四率”(仪器配备率、仪器完好率、仪评率和仪评相符率)的检查工作。各级专业纤维检验机构应充分发挥职能作用,加强蚕茧质量监督管理;加强对茧站仪评计价工作指导;加强对蚕茧收购计t器具的检定工作;充分运用法律手段,在蚕茧收购期间开展执法检查活动,对违法行为坚决予以查处。 在国家生丝质t检验方面,1998年国家经贸委等4部门联合发布了(缀丝绢纺准产证制度实施办法》,规定缎丝、绢纺企业准产的基本条件。经国家茧丝绸协调小组审议,并报国务院领导批准,“国家生丝质量检验”项目列人(国家茧丝绷发展风险基金》第二批发展项目。该项目由中国纤维检验局承担并组织依法设t或依法授权的具有生丝、绢丝检验能力的纤检局(所)、生丝质检站对全国已核发生产准产证的缀丝、绢丝企业的生丝、绢丝质量进行检验。(吕善模),ngconjian zhilia叩Jiondu iianCha he gUOJia she叩51 zh1旧nyan蚕茧质一监督检查和国家生丝质t检验coon甲ality su伴币sion inspection and natsilk卿ality ins衅tion)专业纤维检验机构蚕鲜茧收购期间,对茧站收购鲜茧进行质量监督和检验的全过程。国家生丝质量检验是指由中国CO-nal桑查维
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