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Yarn Quality Prediction for Small Samples Based on adaboost algorithm

Journal of Donghua University(English Edition) 2023年第3期40卷 261-266页

作者：刘智玉陈南梁汪军 College of Textiles Donghua UniversityShanghai 201620China Key Laboratory of Textile Science&Technology Ministry of EducationDonghua UniversityShanghai 201620China

In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an adaboost algorithm(adaboost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for *** prediction experiments of the yarn evenness and the yarn strength were *** coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these *** the prediction experiments,the determination coefficient of the yarn evenness prediction result of the adaboost model is 76% and 87% higher than that of the LR model and the MLP model,*** determination coefficient of the yarn strength prediction result of the adaboost model is slightly higher than that of the other two *** that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the adaboost model has the best adaptability for the nonlinear dataset among the three *** addition,the adaboost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample *** is proved that the adaboost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.

关键词： stability and generalization ability for small samples.Key words:yarn quality prediction adaboost algorithm small sample generalization ability

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An Online Education Data Classification Model Based on TrMadaboost algorithm

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Chinese Journal of Electronics 2019年第1期28卷 21-28页

作者： YU Lasheng WU Xu YANG Yu School of Information Science & Engineering Central South University

With the rapid development of network information technology and the wide application of smart phones, tablet PCs and other mobile terminals, online education plays an increasingly important role in social life. This article focuses on mining useful data from the massive online education data, by using transfer learning, relying on Hadoop, to construct Online education data classification framework(OEDCF), and design an algorithm Tradaboost. This algorithm overcomes the traditional classification algorithms in which the required data must be restricted to independent and identically distributed data, since online education using this new algorithm can achieve the correct classification even it has different data distribution. At the same time, with the help of Hadoop’s parallel processing architecture, OEDCF can greatly enhance the efficiency of data processing, create favorable conditions for learning analysis, and promote personalized learning and other activities of big data era.

关键词： Transfer learning Online education OEDCF adaboost algorithm Tr_Madaboost algorithm

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Feature Extraction and Modeling of Welding Quality Monitoring in Pulsed Gas Touch Argon Welding Based on Arc Voltage Signal

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Journal of Shanghai Jiaotong university(Science) 2014年第1期19卷 11-16页

作者：张志芬钟继勇陈玉喜陈善本 Institute of Welding Engineering School of Material Science and Engineering Shanghai Jiaotong University

Arc sensing plays a significant role in the control and monitoring of welding quality for aluminum alloy pulsed gas touch argon welding(GTAW). A method for online quality monitoring based on adaptive boosting algorithm is proposed through the analysis of acquired arc voltage signal. Two feature extraction algorithms were developed in time domain and frequency domain respectively to extract six statistic characteristic parameters before removing the pulse interference using the wavelet packet transform(WPT), based on which the adaboost classification model is successfully established to evaluate and classify the welding quality into two classes and the classified accuracy of the model is as high as 98.81%. The adaboost algorithm has been verified to be feasible in the online evaluation of welding quality.

关键词： gas touch argon welding(GTAW) arc voltage signal feature extraction adaboost algorithm

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An improved image-based iris-tracking for driver fatigue detection system

An improved image-based iris-tracking for driver fatigue det...

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第36届中国控制会议

作者： Fei Wang Xiaofeng Chen Daoxiong Wang Bo Yang School of Automation Northwestern Polytechnical University

ISBN: (纸本)9781538629185

With rapid development of highway transportation and increasing number of vehicles,the incidence rate of road traffic accidents also sets *** them,fatigue driving has become the main reason of traffic *** this paper,we utilize OpenCV（Open Source Computer Vision） to implement face detection as well as eyes detection on Android platform and to compare the frequency of eyes closed.A fatigue detection system which is able to determine the examinee’s fatigue state accurately was ***,this paper improve the traditional face detection algorithm（adaboost algorithm） and increase the efficiency of face ***,we use the template matching method to track the eye（iris） in real time,constantly updating the iris template to improve the accuracy of ***,the implementation of system is described in detail under the Android *** show that the system can make full use of real time nature and robustness of adaboost face detection algorithm,to achieve high detection rate.

关键词： fatigue driving adaboost algorithm iris tracking template matching

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Expert Evidence Document Recognition Integrating Relationship of Expert

Expert Evidence Document Recognition Integrating Relationshi...

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第25届中国控制与决策会议

作者： Meng Wang Tao Shen Zhengtao Yu School of Information Engineering and Automation Kunming University of Science and Technology School of Material Science and Engineering Kunming University of Science and Technology

ISBN: (纸本)9781467355339

Focus on the issue that the existing expert evidence document recognition method is not effective use of the relationship between experts, this paper proposed a method to recognize the expert evidence documents which integrate the feature of webpage content and the complex relationship between the experts. First of all, the method analyses characteristics of expert evidence document, to select Coauthors and organization as relationship feature, and then extracts feature values. Secondly, select 10130 expert evidence pages, and build data sets which integrate the feature values of and webpage content and the relationship, and then select different learning algorithms to build recognition model. Finally, experiment of expert evidence document recognition is carried out in the field of information processing. The experimental results shows that the proposed method achieves a good recognition effect. Using relationship can effectively improve the accuracy of the evidence document recognition. Its accuracy is improved by 4% compared to method using the page content feature recognition only.

关键词： Expert evidence document recognition Relationship feature Content feature adaboost algorithm

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The System of Face Detection Based on OpenCV

The System of Face Detection Based on OpenCV

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第24届中国控制与决策会议

作者： Xianghua Fan, Fuyou Zhang, Haixia Wang, Xiao Lu Key Laboratory for Robot & Intelligent Technology of Shandong Province, Shandong University of Science and Technology, Qingdao 266590

Face detection technology has widely attracted attention due to its enormous application value and market potential, such as face recognition and video surveillance system. Real-time face detection not only is one part of the automatic face recognition system but also is developing an independent research subject. So, there are many approaches to solve face detection. Here the modified adaboost algorithm based on OpenCV is presented, and experiments of real-time face detecting are also given through two methods of timer and dual-thread. The result shows that the method of face detection with dual-thread is simpler, smoother and more precise.

关键词： Face detection adaboost algorithm OpenCV Timer Dual-thread

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Design and Implementation of Number Gesture Recognition System Based on Kinect

Design and Implementation of Number Gesture Recognition Syst...

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第三十九届中国控制会议

作者： Xingxiu He Jia Zhang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control of Complex System

The paper designs a number gesture recognition system based on Kinect. The system uses the depth image captured by Kinect sensor to extract gesture information for recognition. In the process of recognition, the adaboost algorithm in machine learning is adopted firstly, by the help of Visual Gesture Builder to train the number gesture classifier,and export the classifiers to the recognition program to recognize the current gesture. Finally, numbers are outputted according to the recognized gesture, and the basic functions of number gesture recognition system are realized. Through the experimental verification, the recognition system has enough accuracy, and the system is suitable for various factors such as environment, personnel, etc., which has a certain practical value.

关键词： Kinect sensor number gesture recognition adaboost algorithm human-computer interaction

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