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Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity SCIE
期刊论文 | 2021 , 18 (4) , 4586-4602 | MATHEMATICAL BIOSCIENCES AND ENGINEERING
WoS核心集被引次数: 8
摘要&关键词 引用

摘要 :

Semi-supervised learning has always been a hot topic in machine learning. It uses a large number of unlabeled data to improve the performance of the model. This paper combines the co training strategy and random forest to propose a novel semi-supervised regression algorithm: semi supervised random forest regression model based on co-training and grouping with information entropy (E-CoGRF), and applies it to the evaluation of depression symptoms severity. The algorithm inherits the ensemble characteristics of random forest, and combines well with co-training. In order to balance the accuracy and diversity of co-training random forests, the algorithm proposes a grouping strategy to decision trees. Moreover, the information entropy is used to measure the confidence, which avoids unnecessary repeated training and improves the efficiency of the model. In the practical application of evaluation of depression symptoms severity, we collect cognitive behavioral data of emotional conflict based on the depressive affective disorder. And on this basis, feature construction and normalization preprocessing are carried out. Finally, the test is conducted on 35 labeled and 80 unlabeled depression patients. The result shows that the proposed algorithm obtains MAE (Mean Absolute Error) = 3.63 and RMSE (Root Mean Squared Error) = 4.50, which is better than other semi-supervised regression algorithms. The proposed method effectively solves the modeling difficulties caused by insufficient labeled samples, and has important reference value for the diagnosis of depression symptoms severity.

关键词 :

depression depression E-CoGRF E-CoGRF emotional conflict emotional conflict semi-supervised learning semi-supervised learning symptoms severity symptoms severity

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GB/T 7714 Lu, Shengfu , Shi, Xin , Li, Mi et al. Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity [J]. | MATHEMATICAL BIOSCIENCES AND ENGINEERING , 2021 , 18 (4) : 4586-4602 .
MLA Lu, Shengfu et al. "Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity" . | MATHEMATICAL BIOSCIENCES AND ENGINEERING 18 . 4 (2021) : 4586-4602 .
APA Lu, Shengfu , Shi, Xin , Li, Mi , Jiao, Jinan , Feng, Lei , Wang, Gang . Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity . | MATHEMATICAL BIOSCIENCES AND ENGINEERING , 2021 , 18 (4) , 4586-4602 .
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An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory EI
会议论文 | 2020 , 1684-1690 | 4th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2020
摘要&关键词 引用

摘要 :

The method from DS evidence theory based multi-modal information decision fusion uses the classification structure information which the correct and error classification information provided by the classifiers. These two types of information affect the fusion results of DS evidence theory. This paper proposes a new method(DShW) for correct and error classification information in the balanced classification structure information based on DS evidence theory. That is, a method based on inertia weight normalization is introduced in the confusion matrix. To adjust the specific gravity of correct and error classification in classification structure information by changing the size of the value h, so as to achieve the purpose of balancing correct and error classification information. By comparing with other classifiers, we find that the DShW method effectively improves the accuracy of decision fusion. © 2020 IEEE.

关键词 :

Classification (of information) Classification (of information) Modal analysis Modal analysis Errors Errors Decision theory Decision theory

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GB/T 7714 Lu, Shengfu , Li, Peng , Li, Mi . An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory [C] . 2020 : 1684-1690 .
MLA Lu, Shengfu et al. "An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory" . (2020) : 1684-1690 .
APA Lu, Shengfu , Li, Peng , Li, Mi . An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory . (2020) : 1684-1690 .
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An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory CPCI-S
会议论文 | 2020 , 1684-1690 | 4th IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
WoS核心集被引次数: 2
摘要&关键词 引用

摘要 :

The method from DS evidence theory based multi-modal information decision fusion uses the classification structure information which the correct and error classification information provided by the classifiers. These two types of information affect the fusion results of DS evidence theory. This paper proposes a new method(DShW) for correct and error classification information in the balanced classification structure information based on DS evidence theory. That is, a method based on inertia weight normalization is introduced in the confusion matrix. To adjust the specific gravity of correct and error classification in classification structure information by changing the size of the value h, so as to achieve the purpose of balancing correct and error classification information. By comparing with other classifiers, we find that the DShW method effectively improves the accuracy of decision fusion.

关键词 :

decision-level fusion decision-level fusion DS evidence theory DS evidence theory inertia weight inertia weight multimodal data fusion multimodal data fusion

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GB/T 7714 Lu, Shengfu , Li, Peng , Li, Mi . An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory [C] . 2020 : 1684-1690 .
MLA Lu, Shengfu et al. "An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory" . (2020) : 1684-1690 .
APA Lu, Shengfu , Li, Peng , Li, Mi . An Improved Multi-modal Data Decision Fusion Method Based on DS Evidence Theory . (2020) : 1684-1690 .
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Depression Classification Model Based on Emotionally Related Eye-Movement Data and Kernel Extreme Learning Machine SCIE SSCI
期刊论文 | 2020 , 10 (11) , 2668-2674 | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
WoS核心集被引次数: 1
摘要&关键词 引用

摘要 :

The paper constructed a depression classification model based on emotionally related eye-movement data and kernel extreme learn machine (ELM). In order to improve the classification ability of the model, we use particle swarm optimization (PSO) to optimize the model parameters (regularization coefficient C and the parameter a in the kernel function). At the same time, in order to avoid to be caught in the local optimum and improve PSO's searching ability, we use improved chaotic PSO optimization algorithm and Gauss mutation strategy to increase PSO's particle diversity. The classification results show that the accuracy, sensitivity and specificity of classification models without parameter optimization and Gauss mutation strategy are 80.23%, 80.31% and 79.43%, respectively, while those results of classification model using improved chaotic projection model and Gauss mutation strategy are improved to 88.55%, 87.71% and 89.42%, respectively. Compared with other classification methods of depression, the proposed classification method has better performance on depression recognition.

关键词 :

Chaos Chaos Depression Depression Extreme Learning Machine (ELM) Extreme Learning Machine (ELM) Mutation Mutation Particle Swarm Optimization (PSO) Particle Swarm Optimization (PSO)

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GB/T 7714 Lu, Shengfu , Liu, Sa , Li, Mi et al. Depression Classification Model Based on Emotionally Related Eye-Movement Data and Kernel Extreme Learning Machine [J]. | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS , 2020 , 10 (11) : 2668-2674 .
MLA Lu, Shengfu et al. "Depression Classification Model Based on Emotionally Related Eye-Movement Data and Kernel Extreme Learning Machine" . | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 10 . 11 (2020) : 2668-2674 .
APA Lu, Shengfu , Liu, Sa , Li, Mi , Shi, Xin , Li, Richeng . Depression Classification Model Based on Emotionally Related Eye-Movement Data and Kernel Extreme Learning Machine . | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS , 2020 , 10 (11) , 2668-2674 .
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Method of Depression Classification Based on Behavioral and Physiological Signals of Eye Movement SCIE
期刊论文 | 2020 , 2020 | COMPLEXITY
WoS核心集被引次数: 13
摘要&关键词 引用

摘要 :

This paper presents a method of depression recognition based on direct measurement of affective disorder. Firstly, visual emotional stimuli are used to obtain eye movement behavior signals and physiological signals directly related to mood. Then, in order to eliminate noise and redundant information and obtain better classification features, statistical methods (FDR corrected t-test) and principal component analysis (PCA) are used to select features of eye movement behavior and physiological signals. Finally, based on feature extraction, we use kernel extreme learning machine (KELM) to recognize depression based on PCA features. The results show that, on the one hand, the classification performance based on the fusion features of eye movement behavior and physiological signals is better than using a single behavior feature and a single physiological feature; on the other hand, compared with previous methods, the proposed method for depression recognition achieves better classification results. This study is of great value for the establishment of an automatic depression diagnosis system for clinical use.

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GB/T 7714 Li, Mi , Cao, Lei , Zhai, Qian et al. Method of Depression Classification Based on Behavioral and Physiological Signals of Eye Movement [J]. | COMPLEXITY , 2020 , 2020 .
MLA Li, Mi et al. "Method of Depression Classification Based on Behavioral and Physiological Signals of Eye Movement" . | COMPLEXITY 2020 (2020) .
APA Li, Mi , Cao, Lei , Zhai, Qian , Li, Peng , Liu, Sa , Li, Richeng et al. Method of Depression Classification Based on Behavioral and Physiological Signals of Eye Movement . | COMPLEXITY , 2020 , 2020 .
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Unified Strength Models of an Asphalt Mixture under Different Temperatures and Three-Dimensional Stresses SCIE
期刊论文 | 2020 , 32 (11) | JOURNAL OF MATERIALS IN CIVIL ENGINEERING
WoS核心集被引次数: 1
摘要&关键词 引用

摘要 :

The goal of this paper is to reveal the influence of temperatures on the triaxial strength of asphalt mixtures. The triaxial compression and triaxial tensile tests, as well as plane tensile and compression/axial tensile tests, which were developed by the self-developed triaxial test equipment to carry out the complex stress state under different temperatures (5 degrees C, 10 degrees C, 15 degrees C, 20 degrees C, and 25 degrees C), were performed on the asphalt mixture. The ultimate failure strength of the material shows that the temperature and stress state significantly affect the triaxial strength characteristics of the asphalt mixture, and the three-dimensional strength decreases by the increase in temperature. Under the triaxial compression and triaxial tensile stress state, the resistance of the octahedral shear stress increases with the hydrostatic stress. A three-dimensional strength calculation model is established based on the influence of temperature and characterization by the tensile meridian, compression meridian, and failure strength envelope. It reveals the change of failure strength envelope with increasing temperatures and decreasing hydrostatic stress under complex stress state. It provides experimental and theoretical references to the design of asphalt pavement structure of different temperature conditions according to the three-dimensional stress state.

关键词 :

Hydrostatic stress Hydrostatic stress Pavement engineering Pavement engineering Three-dimensional strength model Three-dimensional strength model Triaxial tests Triaxial tests

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GB/T 7714 Huang, Tuo , Li, Mi , Yang, Yi et al. Unified Strength Models of an Asphalt Mixture under Different Temperatures and Three-Dimensional Stresses [J]. | JOURNAL OF MATERIALS IN CIVIL ENGINEERING , 2020 , 32 (11) .
MLA Huang, Tuo et al. "Unified Strength Models of an Asphalt Mixture under Different Temperatures and Three-Dimensional Stresses" . | JOURNAL OF MATERIALS IN CIVIL ENGINEERING 32 . 11 (2020) .
APA Huang, Tuo , Li, Mi , Yang, Yi , Xie, Jing , Liu, Hongfu , Yao, Hui et al. Unified Strength Models of an Asphalt Mixture under Different Temperatures and Three-Dimensional Stresses . | JOURNAL OF MATERIALS IN CIVIL ENGINEERING , 2020 , 32 (11) .
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An Eye Gaze Tracking Method of Virtual Reality Headset Using A Single Camera and Multi-light Source EI
会议论文 | 2020 , 1518 (1) | 2020 4th International Conference on Machine Vision and Information Technology, CMVIT 2020
摘要&关键词 引用

摘要 :

For the problems the hardware configuration of multi-camera and multi-light source is complicated and the eye image of little auxiliary light source is too dark in the eye gaze tracking system, A new eye gaze tracking system based on two-dimensional mapping model is proposed, which achieved the transformation from two-dimensional coordinates to three-dimensional coordinates combined attitude angle of virtual reality headset. In this paper, the mapping relationship between visual features and eye gaze points is established by improving the method of pupil image recognition and eye gaze estimation based pupil-corneal, which the accuracy of eye gaze estimation is further improved. The experimental results show that the error of eye gaze tracking system is less than 1.1 °, which achieved the good effect of eye gaze tracking. © 2020 Published under licence by IOP Publishing Ltd.

关键词 :

Cameras Cameras Computer vision Computer vision Eye tracking Eye tracking Image enhancement Image enhancement Image recognition Image recognition Light sources Light sources Mapping Mapping Virtual reality Virtual reality

引用:

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GB/T 7714 Lu, Shengfu , Li, Richeng , Jiao, Jinan et al. An Eye Gaze Tracking Method of Virtual Reality Headset Using A Single Camera and Multi-light Source [C] . 2020 .
MLA Lu, Shengfu et al. "An Eye Gaze Tracking Method of Virtual Reality Headset Using A Single Camera and Multi-light Source" . (2020) .
APA Lu, Shengfu , Li, Richeng , Jiao, Jinan , Kang, Jiaming , Zhao, Nana , Li, Mi . An Eye Gaze Tracking Method of Virtual Reality Headset Using A Single Camera and Multi-light Source . (2020) .
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Comparison of veracity and application of different CFD turbulence models for refrigerated transport of apple Scopus
会议论文 | 2019 , 1261 , 225-233
摘要&关键词 引用

摘要 :

With the rapid development of computing power and commercial computational fluid dynamics (CFD) packages, the accuracy of such simulations and their reliability are being constantly improved. This technology has been widely used in refrigerated transport of apples. To improve the accuracy of the simulation results, a key factor is to select appropriate CFD turbulence models. This study was based on an experimental platform that was similar to a refrigerated vehicle or small-scale cold storage. The objective of the study was to establish a comprehensively verified 3D CFD model of this experimental platform to simulate the airflow and heat transfer in different unsteady turbulence models and to predict the temporal-spatial temperature and velocity variations during cooling. Different two-equation eddy viscosity turbulence models, such as standard κ-ε, RNG κ-ε, Realizable κ-ε, standard κ-ω, SST κ-ω, and RSM, were compared. Good agreement between model prediction and measured data was obtained. The root-mean-square error (RMSE) was 1.049, 1.033, 1.039, 1.037, 1.014, and 1.064°C for standard κ-ε, RNG κ-ε, Realizable κ-ε, standard κ-ω, SST κ-ω, and RSM, respectively. Therefore, there were no significant differences in different turbulence models on simulating the temperature distribution, and there was similar accuracy when solving the energy equation on different turbulence models with the two-equation eddy viscosity. The study also revealed that the simulation values of high Reynolds numbers turbulence model, e.g., standard κ-ε, RNG κ-ε, Realizable κ-ε, and RSM were slightly lower than measured values near the plane wall, and the standard κ-ω model predicted higher values than measured ones in the area of the fully developed turbulence. After comparing the accuracy of six two-equation turbulence models, the SST κ-ω model gave more accurate predictions by a comparison of the experimental and simulated results. This study analyzed the accuracy of predicting the 3D spatial and temporal distribution of temperature and velocity with comparison of different two-equation turbulence models inside the experimental platform. This research thus provided a reliable method for better understanding and selecting CFD turbulence models of refrigerated transport of apple. © 2019 International Society for Horticultural Science. All rights reserved.

关键词 :

Apple; Cold-chain logistics; Computational fluid dynamics (CFD); Cooling; Numerical analysis; Turbulence model Apple; Cold-chain logistics; Computational fluid dynamics (CFD); Cooling; Numerical analysis; Turbulence model

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GB/T 7714 Han, J.-W. , Qian, J.-P. , Li, M. et al. Comparison of veracity and application of different CFD turbulence models for refrigerated transport of apple [C] . 2019 : 225-233 .
MLA Han, J.-W. et al. "Comparison of veracity and application of different CFD turbulence models for refrigerated transport of apple" . (2019) : 225-233 .
APA Han, J.-W. , Qian, J.-P. , Li, M. , Fan, B. . Comparison of veracity and application of different CFD turbulence models for refrigerated transport of apple . (2019) : 225-233 .
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Automated model generation for electronic devices using neural network approaches EI
会议论文 | 2019 , 1419 (1) | 2019 International Conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2019
摘要&关键词 引用

摘要 :

This paper describes artificial neural network approaches to convert the conventionally expensive process of electronic modelling into an automated model generation process. Artificial neural networks are trained using machine learning algorithm to learn the electronic behaviour, and the trained neural network becomes a model to help predict the electronic device behaviour. The automated model generation algorithm performs adaptive data sampling to determine the amount and the distribution of training data needed to train neural networks. The algorithm also determines the number of hidden neurons needed to achieve a compact and accurate model. Also incorporated into the automated model generation method is an efficient interpolation approach to make the process much faster. The objective of the described method is to generate a compact neural-network based model with better accuracy and in less time than conventional approach. Examples of automated modeling of radio-frequency and microwave filters used in wireless electronic systems are described showing the advantage of this technique. © 2019 IOP Publishing Ltd.

关键词 :

Neural networks Neural networks Thermoelectric equipment Thermoelectric equipment Learning algorithms Learning algorithms Machine learning Machine learning Microwave filters Microwave filters Automation Automation

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GB/T 7714 Zhang, Q.J. , Na, W. , Li, M. et al. Automated model generation for electronic devices using neural network approaches [C] . 2019 .
MLA Zhang, Q.J. et al. "Automated model generation for electronic devices using neural network approaches" . (2019) .
APA Zhang, Q.J. , Na, W. , Li, M. , Ding, Q. , Wu, G. . Automated model generation for electronic devices using neural network approaches . (2019) .
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Experimental study on seismic performance of full-scale concrete-filled steel tube columns with openings in the steel tube wall [管壁开孔足尺钢管混凝土柱抗震性能试验研究] Scopus CSCD PKU
期刊论文 | 2019 , 35 (1) , 53-61 | World Earthquake Engineering
摘要&关键词 引用

摘要 :

For the connection form of rebar perforation between reinforced concrete beam and concrete-filled steel tube (CFST), the effects of the seismic performances of CFST columns with and without holes by rebar penetration on the tube wall and reinforcement for the holes were studied. Low-cyclic repeated loading tests were carried out on three full-scale CFST columns with diameter of 610 mm. Among the specimens, one is designed without opening holes, another is with opening holes and the last one is with opening holes and reinforcements. The results show that local buckling failure is occurred for the specimen without opening holes at the location of 100 mm from the root of column. The failure of the specimen with holes is the buckling and tear at the edge of holes. Small holes by rebar penetration have little influence on the initial stiffness and peak load capacity of the CFST column. However, after the peak load, due to the tearing damage at the edge of holes, the stiffness and strength of the specimen deteriorate rapidly, and both the ductility and energy dissipation capacity of the specimen decrease. The failure position of the CFST column with reinforcement is located at 90 mm above the reinforcement section, and this specimen shows similar seismic performance with the CFST column without holes. © 2019, Editorial Board of World Earthquake Engineering. All right reserved.

关键词 :

Concrete-filled steel tube columns; Full scale; Openings; Reinforcements; Seismic performance Concrete-filled steel tube columns; Full scale; Openings; Reinforcements; Seismic performance

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GB/T 7714 Ma, H. , Li, M. , Wang, Q. et al. Experimental study on seismic performance of full-scale concrete-filled steel tube columns with openings in the steel tube wall [管壁开孔足尺钢管混凝土柱抗震性能试验研究] [J]. | World Earthquake Engineering , 2019 , 35 (1) : 53-61 .
MLA Ma, H. et al. "Experimental study on seismic performance of full-scale concrete-filled steel tube columns with openings in the steel tube wall [管壁开孔足尺钢管混凝土柱抗震性能试验研究]" . | World Earthquake Engineering 35 . 1 (2019) : 53-61 .
APA Ma, H. , Li, M. , Wang, Q. , Wang, W. , Li, Z. , Chen, H. . Experimental study on seismic performance of full-scale concrete-filled steel tube columns with openings in the steel tube wall [管壁开孔足尺钢管混凝土柱抗震性能试验研究] . | World Earthquake Engineering , 2019 , 35 (1) , 53-61 .
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