An Adaptive Domain Partitioning Technique for Meshfree-Type Methods by Kamal Shanazari

“…A set of adaptive nodes is first generated using the dimension reduction and equidistributing along the coordinate directions with respect to arc-length monitor. …”
Get full text

Interpretability of Composite Indicators Based on Principal Components by Kris Boudt, Marco d’Errico, Hong Anh Luu, Rebecca Pietrelli

“…Principal component approaches are often used in the construction of composite indicators to summarize the information of input variables. The gain of dimension reduction comes at the cost of difficulties in interpretation, inaccurate targeting, and possible conflicts with the theoretical framework when the signs in the loading are not aligned with the expected direction of impact. …”
Get full text

Projections in Moduli Spaces of the Kleinian Groups by Hala Alaqad, Jianhua Gong, Gaven Martin

“…This gives a necessary condition in a simpler space to determine the discreteness of f,g. The dimension reduction here is realised by a projection of principal characters of the two-generator Kleinian groups. …”
Get full text

Research on CSI feedback of RIS-assisted massive MIMO system based on manifold learning by QIAN Mujun, YU Shunchi, LIU Chen, SONG Yunchao, LU Feng

“…Then, the framework combined the manifold learning to train two set of dictionaries to achieve dimension reduction and reconstruction of incremental CSI. …”
Get full text

Research on parallel coordinate visualization technology based on principal component analysis and K-means clustering by Guo-jun MA, Shui-bo WANG, Qing-qi PEI, Yang ZHAN

“…In order to solve the problem that parallel coordinate visualization graphic lines are intensive,overlap and rules of data is not easy to be obtained which caused by high dimension and immense amount of multidimensional data.Parallel coordinate visualization method based on principal component analysis and K-means clustering was proposed.In this method,the principal component analysis method was used to reduce the dimensionality of the multidimensional data firstly.Secondly,the data of the dimension reduction was clustered by K-means.Finally,the data of the clustering were visualized by parallel coordinate visualization.The PCAKP visualization method is tested with the data published by the Bureau of Statistics as the test data,and compared with the traditional parallel coordinate visualization graph,the validity and effectiveness of the PCAKP visualization method are verified.…”
Get full text

Retinopathy Diabetic Recognition and Detection Using Novel Intelligent Algorithms by Liaquat Ali Rahoo

“…The proposed approach consists of four levels: pre-processing for noise removal and standardization of the input dataset, image segmentation using Spiking Neural Network (SNN) based on edge detection, dimension reduction and feature selection using percolation theory, and the final step of combining SNN and percolation theory for retinopathy area detection. …”
Get full text

Incremental Matrix-Based Subspace Method for Matrix-Based Feature Extraction by Zhaoyang Zhang, Shijie Sun, Wei Wang

“…The extracted matrix-based feature is useful to both dimension reduction and spatial statistics analysis for an image. …”
Get full text

Research on text sentiment classification based on improved feature selection method by Mingxin LIU, Jing CHEN, Qiyuan WANG

“…An improved information gain feature selection method based on sentiment dictionary was proposed.Firstly,aiming at the existing problems of information gain feature selection,such as paying attention to the frequency of feature word and ignoring the balance of corpus,an improved method was proposed.Secondly,considering the influence of sentiment words in text classification,a feature selection method IGSC (information gain combining sentiment classification) based on sentiment dictionary was proposed for text classification.By matching the text emotion words and combining the weight of emotion words,the feature dimension reduction was realized and the problem of text data sparseness affecting classification performance was solved.Finally,according to the proposed feature selection method of travel review data set for experimental verification and analysis,the experimental results show that the improved text sentiment classification feature selection method has been improved in terms of classification accuracy,recall and F value,and classification has better stability.…”
Get full text

Split-and-Combine Singular Value Decomposition for Large-Scale Matrix by Jengnan Tzeng

“…It is widely applied in many modern techniques, for example, high- dimensional data visualization, dimension reduction, data mining, latent semantic analysis, and so forth. …”
Get full text

Application of step area algorithm in IDC traffic billing by Shizong LI, Zhihai CHEN, Yongming YAN

“…IDC customers reduce costs through traffic scheduling, which leads to waste of resources and increase of operation and maintenance costs of operators.Area billing could effectively improve this problem.It made a comparison between area billing and 95% peak rate billing method, and innovatively tried the step area algorithm.By connecting the difference between 95% peak rate value and average value and 95% peak rate billing and area billing price, the data dimension reduction was carried out, and the two-dimensional scatter diagram was obtained by programming exhaustive calculation, and the relationship between them was analyzed to explore the possibility of area billing.The experimental results show that the area of pricing could guide the customer does not adopt the way of traffic scheduling to reduce costs, in addition ladder area of billing way can meet the current traffic situation in the certain degree differ with 95 billing way smaller, the flow demand rises customers reduce costs, operators can get the corresponding profits at the same time, achieve a win-win situation.…”
Get full text

Ear Recognition Based on Gabor Features and KFDA by Li Yuan, Zhichun Mu

“…Kernel Fisher Discriminant Analysis (KFDA) is then applied for dimension reduction of the high-dimensional Gabor features. …”
Get full text

A Group Feature Screening Procedure Based on Pearson Chi-Square Statistic for Biology Data with Categorical Response by Hanji He, Jianfeng He, Guangming Deng

“…In the application of lung cancer diagnosis, the proposed method for imbalanced data categorization is impressive, and the dimension reduction using linear discriminant is still good.…”
Get full text

Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis by Zhigao Zeng, Zhiqiang Wen, Shengqiu Yi, Sanyou Zeng, Yanhui Zhu, Qiang Liu, Qi Tong

“…Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. …”
Get full text

Fault early warning model of 4G base station out of service based on centralized monitoring data resources by Yang WANG, Yi MAN, Zhipeng CHEN

“…4G wireless base station equipment is an important link which has direct impact on information communication network customer service quality,and 4G wireless base stations out of service fault will directly block users' normal communication.Aiming at these problems,based on the centralized monitoring warning message data resources through association rule mining and time trace deduction analysis,4G base stations out of service fault short-term warning was achieved.Based on centralized monitoring equipment performance data resources,by the classification of network elements (data cleaning,feature selection,network elements clustering),index dimension reduction (grouped by cluster,principal component analysis),principal component expression and out of service fault correlation analysis,performance indicators selection and threshold analysis,4G base stations out of service fault long-term warning was achieved.The test can accurately predict the 27.8% of 4G base station equipment out of service fault next month.…”
Get full text

Reduction of Multidimensional Image Characteristics Based on Improved KICA by Jia Dongyao, Ai Yanke, Zou Shengxiong

“…The domestic and overseas studies of redundant multifeatures and noise in dimension reduction are insufficient, and the efficiency and accuracy are low. …”
Get full text

LIFE PREDICTION OF ROLLING BEARING BASED ON MULTI-RESOLUTION SINGULAR VALUE DECOMPOSITION AND ECNN-LSTM by XIONG Jun, CHEN Lin, WANG ShangQing

“…Secondly,a high-efficiency channel attention mechanism module was added to the two-layer one-dimensional convolutional neural network structure,and the convolution kernel was adaptively adjusted for multi-channel interaction without dimension reduction,so as to fully extract bearing degradation characteristics and establish effective life degradation indicators. …”
Get full text

An Automatic Detection Method of Nanocomposite Film Element Based on GLCM and Adaboost M1 by Hai Guo, Jinghua Yin, Jingying Zhao, Yuanyuan Liu, Lei Yao, Xu Xia

“…The features of gray level cooccurrence matrix (GLCM) can be extracted from different types of surface morphology images of film; after that, the dimension reduction of film can be handled by principal component analysis (PCA). …”
Get full text

Extraction of Fetal Electrocardiogram by Combining Deep Learning and SVD-ICA-NMF Methods by Said Ziani, Yousef Farhaoui, Mohammed Moutaib

“…It is based on the Convolutional Neural Network (CNN) combined with advanced mathematical methods, such as Independent Component Analysis (ICA), Singular Value Decomposition (SVD), and a dimension-reduction technique like Nonnegative Matrix Factorization (NMF). …”
Get full text

Research status and prospect of fault diagnosis technology for mine high voltage circuit breaker by Ali HUI, Qi QIN, Rui LI, Xiang RONG

“…According to the basic process of fault diagnosis, the current research status and main shortcomings of mechanical fault diagnosis technology of high voltage circuit breaker are summarized from four aspects: circuit breaker state characteristic signal, signal preprocessing, feature extraction and dimension reduction screening and fault diagnosis method. …”
Get full text

Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model by Changming Liu, Di Zhou, Zhigang Wang, Dan Yang, Gangbing Song

“…By means of the principle component analysis (PCA) for dimension reduction, the fifteen related parameters can be reduced to two parameters. …”
Get full text