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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
引用：
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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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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
引用：
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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 . |
| 导入链接 | NoteExpress RIS BibTex |
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)
引用：
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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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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
引用：
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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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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 . |
| 导入链接 | NoteExpress RIS BibTex |
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) . |
| 导入链接 | NoteExpress RIS BibTex |
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) Decision theory Decision theory Errors Errors Modal analysis Modal analysis
引用：
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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 . |
| 导入链接 | NoteExpress RIS BibTex |
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
引用：
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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) . |
| 导入链接 | NoteExpress RIS BibTex |
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
引用：
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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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摘要 ：
近年来,人工智能技术取得了突破性进展,为人们的生活带来了改变.高等教育作为教育的重要组成部分,是我国培养高科技人才的关键所在.而面临人工智能时代的到来,我国传统高等教育受到了冲击与挑战.本文对人工智能的发展历程及趋势进行了介绍,对当前我国高等教育模式进行了分析,探讨了人工智能技术在高等教育中的应用,进而探讨人工智能时代高等教育的改革,旨在实现我国创新型人才的培养.
关键词 ：
创新性人才 创新性人才 高等教育 高等教育 人工智能 人工智能 改革 改革
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| GB/T 7714 | 李文静 , 栗觅 , 奥顿 . 论人工智能时代高等教育改革 [J]. | 未来与发展 , 2019 , 43 (3) : 67-71 . |
| MLA | 李文静 et al. "论人工智能时代高等教育改革" . | 未来与发展 43 . 3 (2019) : 67-71 . |
| APA | 李文静 , 栗觅 , 奥顿 . 论人工智能时代高等教育改革 . | 未来与发展 , 2019 , 43 (3) , 67-71 . |
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