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第三十九届中国控制会议

作者： Zhiying Lu Tianqi Ni Xiaolei Sun Jingchun Yan School of Electrical and Information Engineering Tianjin University

The winds that often occur on the ocean surface have a great impact on economic activities such as the development of ports and harbor engineering. The accurate forecast of wind speeds on the ocean surface is of great significance. A Genetic Algorithm-Leaked Integral Echo State Network（GA-LIESN） on-line learning Model for ocean surface wind prediction is proposed in this paper. First of all, the model uses correlation analysis to select the features which are most relevant to the wind speed label as the input of the forecast model. Then introduce leaky integral neurons into echo state network（ESN） to improve the model’s short-term memory for time series. Next, an on-line learning algorithm is used to correct the model in real time by introducing new samples to make the model adaptive. Finally, in order to overcome the blind selection of network parameters,genetic algorithm（GA） is used to optimize the network parameters. The meteorological observation data which are measured from a station in the Bohai Bay are selected as experimental data. Compared with Auto-Regressive and Moving Average Model（ARMA） and ESN, the GA-LIESN on-line learning Model shows a higher prediction accuracy.

关键词： Ocean surface wind prediction Leaked Integral ESN on-line learning Genetic Algorithm

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IMPROVING LEARNER MOTIVATION IN EFL WRITING THROUGH on-line learning

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Chinese Journal of Applied Linguistics 2007年第1期30卷 66-72,127页

作者：王懿上海交通大学

This paper introduces process writing approach, and theories of learner motivation and learner autonomy. A fieldwork experiment is conducted on the comparison of on-line learning and traditional face-to-face learning to find out whether on-line learning can improve learners' writing ability and learners motivation in EFL writing. The results show that on-line learning with its distinctive advantages where process writing approach can be carried out relatively easily can arouse learners' intrinsic motivation and enhance learner autonomy, thus improving learners' writing ability significantly.

关键词： on-line learning process writing learning motivation

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Adaptive foreground and shadow segmentation using hidden conditional random fields

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2007年第4期8卷 586-592页

作者： CHU Yi-ping YE Xiu-zi QIAN Jiang ZHANG Yin ZHANG San-yuan School of Computer Science State Key Lab. of CAD ＆ CG Zhejiang University Hangzhou 310027 China

Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is proposed, which models spatio-temporal constraints of video sequence. In order to improve the segmentation quality, the weights of spatio-temporal con- straints are adaptively updated by on-line learning for HCRFs. Shadows are the factors affecting segmentation quality. To separate foreground objects from the shadows they cast, linear transform for Gaussian distribution of the background is adopted to model the shadow. The experimental results demonstrated that the error ratio of our algorithm is reduced by 23% and 19% respectively, compared with the Gaussian mixture model (GMM) and spatio-temporal Markov random fields (MRFs).

关键词： Video segmentation Shadow elimination Hidden conditional random fields (HCRFs) on-line learning

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On-line least squares support vector machine algorithm in gas prediction

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Mining Science and Technology 2009年第2期19卷 194-198页

作者： ZHAO Xiao-hu WANG Gang ZHAO Ke-ke TAN De-jian School of Information ＆ Electronic Engineering China University of Mining ＆ Technology Xuzhou Jiangsu 221008 China

Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction *** Support Vector Machine(SVM) is a new machine learning algorithm that has excellent *** least squares support vector machine(LS-SVM) algorithm is an improved algorithm of *** the common LS-SVM algorithm,used directly in safety predictions,has some *** have first studied gas prediction problems and the basic theory of *** these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on ***,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its *** simulation results have verified the validity of the new algorithm.

关键词： LS-SVM gas on-line learning prediction

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On-line Peer Assessment of Chinese Students＇ Oral Presentation in English

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Sino-US English Teaching 2012年第3期9卷 1005-1009页

作者： LIU Li LU Lei-na Dalian University of Technology Dalian China Nanjing University of Science and Technology Nanjing China

The current paper aims to conduct a research of on-line peer assessment of Chinese students＇ oral presentation in English. Based on the theoretical framework： social cognitive theory and constructivism, on-line peer assessment enhances interaction and improvement. The result comes up with the conclusion that this way of assessment is effective, especially for Chinese students, to improve efficacy, to develop confidence in oral presentation, and to foster autonomy in learning

关键词： on-line learning peer assessment oral presentation

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