Wavelet Robust Filtering of Out-Trajectory Data

2013 ◽  
Vol 756-759 ◽  
pp. 344-348
Author(s):  
Ling Jing Meng ◽  
Hai Bo Liu
Keyword(s):  
Engineering Application ◽  
Original Data ◽  
Robust Filtering ◽  
The Novel ◽  
Trajectory Data ◽  
Process Data ◽  
Filtering Method ◽  
Noise Simulation ◽  
Simulation Calculation ◽  
Suppress Noise

Wavelet-based robust filtering of process data is proposed in order to reduce the influence of the outliers and noise in Out-trajectory data. We utilize the moving median filtering method to reject outliers in the original data and then combine wavelet de-noising method with empirical Wiener threshold to suppress noise. Simulation calculation and real engineering application has shown that the novel algorithm reliably preserves the information encapsulated in a process signal corrupted with noise and outliers. The methodology has been proved to be reliable and robust.

A spatio-temporal noise robust filtering method for separation of 2D incident and reflected irregular waves

2021 ◽  
Vol 237 ◽  
pp. 109544
Author(s):  
Gustavo E. Coelho ◽  
Maria Graça Neves ◽  
António Pascoal ◽  
Álvaro Ribeiro ◽  
Peter Frigaard
Keyword(s):  
Irregular Waves ◽  
Robust Filtering ◽  
Filtering Method ◽  
Temporal Noise ◽  
Spatio Temporal ◽  
Noise Robust

What makes users willing or hesitant to use Fintech?: the moderating effect of user type

2018 ◽  
Vol 118 (3) ◽  
pp. 541-569 ◽  
Author(s):  
Hyun-Sun Ryu
Keyword(s):  
Least Squares Method ◽  
Original Data ◽  
The Novel ◽  
Continuance Intention ◽  
Content Type ◽  
Factors Affecting ◽  
Proposed Model ◽  
Negative Effect ◽  
Partial Least Squares Method ◽  
Benefit And Risk

Purpose The purpose of this paper is to better understand why people are willing or hesitant to use Financial technology (Fintech) as well as to determine whether the effect of perceived benefits and risks of continuance intention differs depending on user types. Design/methodology/approach Original data were collected via a survey of 243 participants with Fintech usage experience. The partial least squares method was used to test the proposed model. Findings The results reveal that legal risk had the most negative effect on the Fintech continuance intention, while convenience had the strongest positive effect. Differences in specific benefit and risk impacts are found between early and late adopters. Originality/value This empirical study contributes to the novel understanding of the benefit and risk factors affecting the Fintech continuance intention.

scholarly journals Adaptive Dual-Polarization Filtering Method for Countering Active Jamming

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Qiang Zhang ◽  
Rui Zhou ◽  
Xianbo Shi ◽  
Yixin Zhao
Keyword(s):  
Engineering Application ◽  
Dual Polarization ◽  
Work Situation ◽  
Polarization Filter ◽  
Signal Model ◽  
Filtering Method ◽  
Filtering Algorithm ◽  
Polarization Characteristics ◽  
Polarization Filtering ◽  
Combination Mode

In order to counter active jamming, an adaptive polarization filtering method based on dual polarization radar is put forward. First, the signal flow principle of the dual polarization radar and its signal model are introduced. Then, the weighted coefficient matrices of the polarization filter are calculated adaptively according to the actual work situation of the current radar. Finally, the specific polarization filtering algorithm and the output criterion of the optimal filtering results are given. Experimental results show that this method does not need to know the type, quantity, combination mode, polarization characteristics, and other prior knowledge of active jamming but has well effect on both active deception jamming and active blanket jamming, so it has strong engineering application value.

Wavelet-based robust filtering of process data

2001 ◽  
Vol 25 (11-12) ◽  
pp. 1549-1559 ◽  
Author(s):  
Fuat Doymaz ◽  
Amid Bakhtazad ◽  
Jose A. Romagnoli ◽  
Ahmet Palazoglu
Keyword(s):  
Robust Filtering ◽  
Process Data

scholarly journals Improved Multiobjective Harmony Search Algorithm with Application to Placement and Sizing of Distributed Generation

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Wanxing Sheng ◽  
Ke-yan Liu ◽  
Yunhua Li ◽  
Yuan Liu ◽  
Xiaoli Meng
Keyword(s):  
Distributed Generation ◽  
Search Algorithm ◽  
Harmony Search ◽  
Engineering Application ◽  
Test System ◽  
Harmony Search Algorithm ◽  
Optimal Placement ◽  
The Novel ◽  
Nsga Ii ◽  
Intelligent Optimization Algorithm

To solve the comprehensive multiobjective optimization problem, this study proposes an improved metaheuristic searching algorithm with combination of harmony search and the fast nondominated sorting approach. This is a kind of the novel intelligent optimization algorithm for multiobjective harmony search (MOHS). The detailed description and the algorithm formulating are discussed. Taking the optimal placement and sizing issue of distributed generation (DG) in distributed power system as one example, the solving procedure of the proposed method is given. Simulation result on modified IEEE 33-bus test system and comparison with NSGA-II algorithm has proved that the proposed MOHS can get promising results for engineering application.

scholarly journals Fault Detection and Diagnosis in Process Data Using Support Vector Machines

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Fang Wu ◽  
Shen Yin ◽  
Hamid Reza Karimi
Keyword(s):  
Dimensional Space ◽  
Industrial Process ◽  
Principal Component ◽  
Original Data ◽  
Fault Detection And Diagnosis ◽  
Fault Classification ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Process Data ◽  
Tennessee Eastman Process

For the complex industrial process, it has become increasingly challenging to effectively diagnose complicated faults. In this paper, a combined measure of the original Support Vector Machine (SVM) and Principal Component Analysis (PCA) is provided to carry out the fault classification, and compare its result with what is based on SVM-RFE (Recursive Feature Elimination) method. RFE is used for feature extraction, and PCA is utilized to project the original data onto a lower dimensional space. PCAT2, SPE statistics, and original SVM are proposed to detect the faults. Some common faults of the Tennessee Eastman Process (TEP) are analyzed in terms of the practical system and reflections of the dataset. PCA-SVM and SVM-RFE can effectively detect and diagnose these common faults. In RFE algorithm, all variables are decreasingly ordered according to their contributions. The classification accuracy rate is improved by choosing a reasonable number of features.

scholarly journals Geospatial User Feedback: How to Raise Users’ Voices and Collectively Build Knowledge at the Same Time

2021 ◽  
Vol 10 (3) ◽  
pp. 141
Author(s):  
Alaitz Zabala ◽  
Joan Masó ◽  
Lucy Bastin ◽  
Gregory Giuliani ◽  
Xavier Pons
Keyword(s):  
Original Data ◽  
Scientific Paper ◽  
User Feedback ◽  
Practical Implementation ◽  
Process Data ◽  
Data Usage ◽  
New Information ◽  
The Status ◽  
Open Geospatial Consortium ◽  
Analytical Tools

Geospatial data is used not only to contemplate reality but also, in combination with analytical tools, to generate new information that requires interpretation. In this process data users gain knowledge about the data and its limitations (the user side of data quality) as well as knowledge on the status and evolutions of the studied phenomena. Knowledge can be annotations on top of the data, responses to questions, a careful description of the processes applied, a piece of software code or scripts applied to the data, usage reports or a complete scientific paper. This paper proposes an extension of the current Open Geospatial Consortium standard for Geospatial User Feedback to include the required knowledge elements, and a practical implementation. The system can incrementally collect, store, and communicate knowledge elements created by users of the data and keep them linked to the original data by means of permanent data identifiers. The system implements a Web API to manage feedback items as a frontend to a database. The paper demonstrates how a JavaScript widget accessing this API as a client can be easily integrated into existing data catalogues, such as the ECOPotential web service or the GEOEssential data catalogue, to collectively collect and share knowledge.

A Winch Fault Classification Algorithm Based on Cluster Kernel Semi-Supervised Support Vector Machine

2012 ◽  
Vol 220-223 ◽  
pp. 452-458
Author(s):  
Xian Xin Shi ◽  
Zhong Xiang Zhao ◽  
Chang Jian Zhu ◽  
Xiao Xiao Kong ◽  
Jun Fei Chai ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Spectral Clustering ◽  
Cluster Algorithm ◽  
Original Data ◽  
Fault Classification ◽  
Support Vector ◽  
The Novel ◽  
High Classification Accuracy ◽  
Novel Approach ◽  
Cluster Assumption

A cluster kernel semi-supervised support vector machine (CKS3VM) based on spectral cluster algorithm is proposed and applied in winch fault classification in this paper. The spectral clustering method is used to re-represent original data samples in an eigenvector space so as to make the data samples in the same cluster gather together much better. Then, a cluster kernel function is constructed upon the eigenvector space. Finally, a cluster kernel S3VM is designed which can satisfy the cluster assumption of semi-supervised study. The experiments on winch fault classification show that the novel approach has high classification accuracy.

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