2) 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
3) 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。
4) 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。
5) basic training
基本训练
1.
Considering the lack of practical and uniform basic contents for surgical resident training,the paper proposes five basic training strategies and discusses their role in training surgical residents.
针对目前外科住院医师缺少实用统一的基本训练内容,提出并探讨五项基本训练在临床实践中的应用价值。
2.
Firstly,the fundamental phenomenological outlook of Husserl is interpreted as the basic training of phenomenology.
第一,把胡塞尔对现象学的基本考察诠释为现象学的基本训练;第二,把其主要步骤归结为:悬置自然立场———体验意识的本质性质———从自然世界中分离出意识———关闭自然世界———取消精神实在———进入纯粹意识并确立现象学立场;第三,分析这种训练所具有的多方面重要意义,并指出其不彻底性以及如何加以彻底化。
3.
The thesis states in detail the basic training methods of listening in music from these five sections: scale exercises and singing mode, monosyllabic structure singing and tone of perception, intervals and chords of perception, rhythm of perception and melody of perception.
文章从音阶练习和模唱、单音构唱和单音听辨、音程与和弦的听辨、节奏的听辨、旋律的听辨等五个部分详细介绍了音乐中听力的基本训练方法。
6) 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：本质映射
本质映射
essential mappng
本质映射[.皮刘间..月，甩;ey叫eeTaea一oe oTo6一a-狱e朋el 把拓扑空间x映成闭单形r”的连续映射f，使得在集合f一’(于·\尹)的所有点上和f相同的任何连续映射关:x~于”都是映成整个于·的映射.例如，把于”映成自身的恒等映射是本质映射.【补注】本质映射用来刻画正规空间的夜盖维数(见维数(山庄猫沁n)).正规空间(nom词sPa以治)的概盖维数)n的充要条件是:存在一个把该空间映成”维闭单形尹的本质映射.
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条