3篇
您的检索式：作者名="Fu Qunchao"
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| 1 | Sentence segmentation for classical Chinese based on LSTM with radical embedding显示文摘A low-than character feature embedding called radical embedding is proposed,and applied on a long-short term memory(LSTM) model for sentence segmentation of pre-modern Chinese texts.The dataset includes over 150 classical Chinese books from 3 different dynasties and contains different literary styles.LSTM-conditional random fields(LSTM-CRF) model is a state-of-the-art method for the sequence labeling problem.This model adds a component of radical embedding,which leads to improved performances.Experimental results based on the aforementioned Chinese books demonstrate better accuracy than earlier methods on sentence segmentation,especial in Tang’s epitaph texts(achieving an F1-score of 81.34%). | Han Xu Wang Hongsu Zhang Sanqian Fu Qunchao Liu Jun | 2019 | The Journal of China Universities of Posts and Telecommunications2019，26，2： | 7 |
| 2 | Comparison of three data mining methods in predicting 5-year survival of colorectal cancer patients显示文摘The prediction of colorectal cancer(CRC) survivability has always been a challenging research issue. Considering the importance of predicting CRC patients' survival rates, we compared the performance of three data mining methods: decision trees(DTs), artificial neural networks(ANNs) and support vector machines(SVMs), for predicting 5-year survival of CRC patients to assist clinicians in making treatment decisions. The CRC dataset used to build the prediction model comes from the surveillance, epidemiology, and end results(SEER) program. The 5-fold cross-validation and random forest algorithm were respectively utilized for measuring the model predictive accuracy and the importance of features. Experimental results show that the predictive accuracy of ANNs(0.73) and SVMs(0.75) were higher than that of DTs, and they also have the best result in the area under the receiver operating characteristic(ROC) curve(area under curve(AUC)=0.82). This result may indicate high predictive power of ANNs and SVMs for predicting 5-year survival of CRC patients. | Luo Yan Sun Yawei Fu Qunchao Xue Tengfei Zhou Ping | 2018 | The Journal of China Universities of Posts and Telecommunications2018，25，6： | 0 |
| 3 | Method for studying diatomic rovibrational spectra at a given vibrational state显示文摘An algebraic method for rotational energies at a given vibrational state(AMr(v)) is proposed in this study in order to obtain unknown high-lying rovibrational energies. Applications of this method to the ground electronic state X^1Σ^+of CO and the excited state C^1Σ^+of^(39)K^7Li molecules show the following:(1) the AMr(v) can give the rational upper limit J of a rotational quantum number of a diatomic electronic state;(2) the full AMr(v) rovibrational energies {E_(υJ)}_υ of given vibrational states not only reproduce all known experimental data excellently but also predict precisely the values of all high-lying rovibrational energies,which may not be available experimentally. | Yi Zhang WeiGuo Sun Jia Fu QunChao Fan Jie Ma LianTuan Xiao SuoTang Jia | 2019 | Science China(Physics,Mechanics & Astronomy)2019，62，4： | 0 |
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