检索结果-内蒙古大学图书馆

International Conference on Natural Language Processing and Knowledge Engineering

作者： Chen, KL Zong, CQ Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100080 Peoples R China

ISBN: (纸本)0780379020

In the domain of text categorization (TC), the TF (term frequency)*IDF (inverse document frequency) weighting algorithm and TF*IWF*IWF weighting algorithm are widely used. However, the two algorithms are too biased by the term frequency and neglect the unbalance between classes. In this paper., we propose a new weighting algorithm, which is named as TF (term frequency) *IWF (inverse word frequency)*IWF (inverse word frequency)*VE (variance and expectation). The new algorithm improves the TF*IWF*IWF weighting algorithm in both TF and VE. This paper compares the new algorithm with TF*IWF*IWF algorithm respectively in theory and experiment. From the preliminary experiment, we find that the F1-Measure has been improved for 11.78%.

关键词： weighting algorithm variance text categorization

来源：评论

学校读者我要写书评

暂无评论

A New Way to Set the Maximum Weight in the weighting algorithm of UTC

A New Way to Set the Maximum Weight in the Weighting Algorit...

引用

Joint Conference of the European-Frequency-and-Time-Forum / IEEE International Frequency Control Symposium (EFTF/IFCS)

作者： Milton, J. Panfilo, G. Univ Edinburgh Sch Phys Edinburgh Midlothian Scotland BIPM Time Dept Sevres France

ISBN: (数字)9781665497183

ISBN: (纸本)9781665497183

In this paper a new way to set the maximum weight in the weighting algorithm of UTC based on the Karush-Kuhn-Tucker conditions is presented. The idea is to impend several clocks (H-masers) reaching the maximum weight if they are not good enough. This is due to the current way to fix the maximum weight and to the normalization process applied. The final scope is the improvement of long-term stability of UTC.

关键词： UTC weighting algorithm long-term stability

来源：评论

学校读者我要写书评

暂无评论

Clinical application of non-invasive prenatal diagnosis of phenylketonuria based on haplotypes via paired-end molecular tags and weighting algorithm

引用

BMC MEDICAL GENOMICS 2021年第1期14卷 294-294页

作者： Dai Peng Zhao Ganye Sun Gege Xia Yanjie Liu Ning Kong Xiangdong Zhengzhou Univ Affiliated Hosp 1 Genet & Prenatal Diag Ctr Dept Obstet & Gynecol Zhengzhou 450052 Henan Peoples R China

Background Phenylketonuria (PKU) is a metabolic disease that can cause severe and irreversible brain damage without treatment. Methods Here we developed a non-invasive prenatal diagnosis (NIPD) technique based on haplotypes via paired-end molecular tags and weighting algorithm and applied it to the NIPD of PKU to evaluate its accuracy and feasibility in the early pregnancy. A custom-designed hybridization probes containing regions in phenylalanine hydroxylase (PAH) gene and its 1 Mb flanking region were used for target sequencing on genomic and maternal plasma DNA (7-13 weeks of gestation) to construct the parental haplotypes and the proband's haplotype. Fetal haplotype was then inferred combined with the parental haplotypes and the proband's haplotype. The presence of haplotypes linked to both the maternal and paternal mutant alleles indicated affected fetuses. The fetal genotypes were further validated by invasive prenatal diagnosis in a blinded fashion. Results This technique has been successfully applied in twenty-one cases. Six fetuses were diagnosed as patients carrying both of the mutated haplotypes inherited from their parents. Eleven fetuses were carriers of one heterozygous PAH variants, six of which were paternal and five of which were maternal. Four fetuses were absence of pathogenic alleles. All results were consistent with the prenatal diagnosis through amniotic fluid. Conclusions The results showed that our new technique applied to the genotyping of fetuses with high risk for PKU achieves an accurate detection at an early stage of pregnancy with low fetal fraction in cell free DNA.

关键词： Phenylketonuria Non-invasive prenatal diagnosis Haplotype weighting algorithm Paired-end molecular tags

来源：评论

学校读者我要写书评

暂无评论

A NEW weighting algorithm FOR LINEAR CLASSIFIER

A NEW WEIGHTING ALGORITHM FOR LINEAR CLASSIFIER

引用

2003 International Conference on Natural Language Processing and Knowledge Engineering

作者： Keli Chen Chengqing Zong National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)0780379020

In the domain of text categorization(TC),the TF (term frequency)*IDF(inverse document frequency) weighting algorithm and TF*IWF*IWF weighting algorithm are widely ***,the two algorithms are too biased by the term frequency and neglect the unbalance between *** this paper, we propose a new weighting algorithm,which is named as TF(term frequency) *IWF(inverse word frequency) *IWF(inverse word frequency)*VE (variance and expectation).The new algorithm improves the TF*IWF*IWF weighting algorithm in both TF and *** paper compares the new algorithm with TF*IWF*IWF algorithm respectively in theory and *** the preliminary experiment,we find that the F1 -Measure has been improved for 11.78%.

关键词： weighting algorithm Variance Text categorization

来源：评论

学校读者我要写书评

暂无评论

Determination of the coordinates of the center of a Gaussian beam by means of a matrix photodetector using a weighting method

引用

MEASUREMENT TECHNIQUES 2003年第12期46卷 1133-1137页

作者： Savchenko, EV Razumov, LA Rinkevicius, BS

A weighting algorithm to determine the coordinates of the center of a Gaussian laser beam projected onto a matrix photodetector is considered. The influence of the internal noise of the photodetector the maximum brightness of the signal at the beam maximum, and the beam radius on the precision of the algorithm is investigated. Recommendations on image processing are presented.

关键词： weighting algorithm optical measurements Gaussian beam charge-coupled devices

来源：评论

学校读者我要写书评

暂无评论

Weighted spatial based geometric scheme as an efficient algorithm for analyzing single-trial EEGS to improve cue-based BCI classification

引用

NEURAL NETWORKS 2017年 92卷 69-76页

作者： Alimardani, Fatemeh Boostani, Reza Blankertz, Benjamin Shiraz Univ Dept Comp Sci & Engn Shiraz Iran Inst Adv Studies Basic Sci Gavazang Zanjan Iran Tech Univ Berlin Neurotechnol Grp Berlin Germany Sch Elect & Comp Engn Dept Comp Sci & Engn & Informat Technol Zand AvePOB 71348-51154 Shiraz Iran Berlin Brain Comp Interfact BBCI Project Berlin Germany

There is a growing interest in analyzing the geometrical behavior of electroencephalogram (EEG) covariance matrix in the context of brain computer interface (BCI). The bottleneck of the current Riemannian framework is the bias of the mean vector of EEG signals to the noisy trials, which deteriorates the covariance matrix in the manifold space. This study presents a spatial weighting scheme to reduce the effect of noisy trials on the mean vector. To assess the proposed method, dataset Ha from BCI competition IV, containing the EEG trials of 9 subjects performing four mental tasks, was utilized. The performance of the proposed method is compared to the classical Riemannian method along with Common Spatial Pattern (CSP) on the dataset. The results show that when considering just two imagery classes, the proposed method performs on par with CSP method, whereas in the multi class scenario, the proposed algorithm outperforms the CSP approach on seven out of nine subjects. Incidentally, the proposed method obtains better accuracy for the majority of subjects compared to the classical Riemannian method. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Riemannian geometry Cue-based Brain computer interface weighting algorithm Covariance matrix

来源：评论

学校读者我要写书评

暂无评论

RBF Networks-Based Weighted Multi-Model Adaptive Control for a Category of Nonlinear Systems With Jumping Parameters

引用

IEEE ACCESS 2019年 7卷 84929-84937页

作者： Li, Qing Yang, Yuhang Zhang, Yuzhen Liu, Yukun Zhang, Weicun Cui, Jiarui Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

This paper studies the tracking control problem for nonlinear system with largely jumping parameters. To deal with the large uncertainties of system parameters, an RBF networks-based weighted multi-model adaptive control (WMMAC) strategy is designed, in which the model set can be constructed to cover and approximate the variation range of the plant parameters. Correspondingly, the RBF network controller set generates the appropriate global control signals when parameters jumping, and better transient performance is obtained. Different from existing neural network learning methods, two novel learning rules based on the difference value between the current value of an objective function and its optimal value for the RBF networks are developed to achieve a fast convergence rate. The stability of the overall closed-loop system is validated by the virtual equivalent system (VES) theory, and favorable performance of the proposed control strategy is demonstrated by the numerical simulations.

关键词： Multi-model adaptive control RBF network control learning rule weighting algorithm virtual equivalent system

来源：评论

学校读者我要写书评

暂无评论

Weighted Multiple Neural Network Boundary Control for a Flexible Manipulator With Uncertain Parameters

引用

IEEE ACCESS 2019年 7卷 57633-57641页

作者： Zhang, Yuzhen Li, Qing Zhang, Weicun Liu, Yukun Xue, Zhuoer Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

This paper addresses the angle tracking and vibration suppression for a flexible manipulator with uncertain parameters. Based on the partial differential equation (PDE) model, a unified framework of weighted multiple neural network boundary control (WMNNBC) is proposed to deal with the jumping parameters, in which neural networks are designed as the local boundary controllers to suppress vibrations. A novel proportion-derivative-like machine learning algorithm is developed to guarantee the learning convergence. Besides, the weighting algorithm is used to fuse multiple local neural network controllers to generate the appropriate global control signals with the variations of plant parameters. The stability of the overall closed-loop system is proved by the virtual equivalent system (VES) theory. The simulations are implemented to illustrate the feasibility and control performance of the proposed WMNNBC strategy.

关键词： Neural network control flexible manipulator machine learning weighting algorithm virtual equivalent system

来源：评论

学校读者我要写书评

暂无评论

Parallel hybridization of series (PHOS) models for time series forecasting

引用

SOFT COMPUTING 2021年第1期25卷 659-672页

作者： Hajirahimi, Zahra Khashei, Mehdi Isfahan Univ Technol IUT Dept Ind & Syst Engn Esfahan Iran

Literature indicates that many efforts have been conducted toward the development of forecasting models with a high degree of accuracy. Combining different models is known as a powerful alternative to access more reliable and more accurate results than single models. Given the great importance of hybridization theory, various hybrid models have been proposed in the literature of time series forecasting. Series hybrid approaches are one of the most well study and the most widely used hybridization models, in which components are sequentially applied. However, according to the modeling essence of this hybrid structure, the performance of the series hybrid models is directly dependent on the order of using components and modeling sequence. Besides, selecting the best modeling order that can yield the best performance in all situations is a problematic theoretical as well as practical task. Thus, the main purpose of this paper is to eliminate the drawback of series models, regarding modeling order selection using a parallel hybridization schema, which is addressed for the first time. The core principle of the proposed parallel hybridization of series (PHOS) models is to improve the series hybrid model's forecasting accuracy by integrating two hybrid structures in contrast to existing hybrid models, which emphasize only the combination of individual models. The proposed model decomposes the original time series into two linear and nonlinear parts and uses the autoregressive integrated moving average (ARIMA) and multilayer perceptron neural network (MLP) models to model underlying patterns, incorporating two series models including ARIMA-MLP and MLP-ARIMA. Finally, the series models are integrated as components of the parallel hybridization scheme. Moreover, an ordinary least square algorithm is developed to determine the optimal weights of these two components. Three benchmark data sets, including the closing of the DAX index, the closing of the Nikkei 225 index (N225),

关键词： Series hybrid models Parallel hybridization Multilayer perceptrons (MLPs) Autoregressive integrated moving average (ARIMA) Time series forecasting weighting algorithm

来源：评论

学校读者我要写书评

暂无评论

The Maximum Weight in UTC: Proposal for a New Approach

引用

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL 2023年第4期70卷 336-343页

作者： Milton, James Panfilo, Gianna Univ Edinburgh Sch Phys Edinburgh EH8 9YL Scotland BIPM F-92310 Sevres France

The goal of this work is the improvement of the long-term stability of Coordinated Universal Time (UTC). To achieve this purpose a comprehensive analysis of the atomic clocks participating in the calculation of UTC is presented. We focus our analysis on the hydrogen masers, the only clocks reaching the maximum weight in UTC. We observed that the present weighting algorithm fails to assign the maximum weight to H-masers with the best stability (predictability) only and too many clocks reach the maximum weight. To improve the process, we present a new way to generalize the maximum weight in the weighting algorithm of UTC based on the Karush-Kuhn-Tucker (K-K-T) conditions. The method succeeds in improving the longterm stability of UTC.

关键词： Clocks Cesium Prediction algorithms Stability criteria Atomic clocks Time-frequency analysis Uncertainty Coordinated Universal Time (UTC) long-term stability weighting algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：