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RISS 인기검색어
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- 저자 : Meng Fanqi (검색결과 4 건)
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Semi-supervised Software Defect Prediction Model Based on Tri-training
( Fanqi Meng ),( Wenying Cheng ),( Jingdong Wang ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.11
Aiming at the problem of software defect prediction difficulty caused by insufficient software defect marker samples and unbalanced classification, a semi-supervised software defect prediction model based on a tri-training algorithm was proposed by combining feature normalization, over-sampling technology, and a Tri-training algorithm. First, the feature normalization method is used to smooth the feature data to eliminate the influence of too large or too small feature values on the model's classification performance. Secondly, the oversampling method is used to expand and sample the data, which solves the unbalanced classification of labelled samples. Finally, the Tri-training algorithm performs machine learning on the training samples and establishes a defect prediction model. The novelty of this model is that it can effectively combine feature normalization, oversampling techniques, and the Tri-training algorithm to solve both the under-labelled sample and class imbalance problems. Simulation experiments using the NASA software defect prediction dataset show that the proposed method outperforms four existing supervised and semi-supervised learning in terms of Precision, Recall, and F-Measure values.
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Creating Knowledge Graph of Electric Power Equipment Faults Based on BERT–BiLSTM–CRF Model
Meng Fanqi,Yang Shuaisong,Wang Jingdong,Xia Lei,Liu Han 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.4
Creating a large-scale knowledge graph of electric power equipment faults will facilitate the development of automatic fault diagnosis and intelligent question answering (QA) in the electric power industry. However, most existing methods have lower accuracy in Chinese entity recognition, thus it is hard to build such a high-quality knowledge graph by extracting knowledge from Chinese technical literature. To solve the problem, a novel model called BERT–BiLSTM–CRF is proposed. It blends Bi-directional Encoder Representation from Transformers (BERT), Bi-directional Long Short-Term Memory (BiLSTM), and Conditional Random Field (CRF). The model fi rstly identifi es and extracts electric power equipment entities from preprocessed Chinese technical literature. Then, the semantic relations between the entities are extracted based on the relation classifi cation method based on dependency parsing. Finally, the extracted knowledge is stored in the Neo4j database in the form of the triplet and visualized in the form of a graph. Through the above steps, a Chinese knowledge graph of electric power equipment faults can be built. The novelty of the model just lies in its subtle blend: the BERT module can not only learn phrase-level information representation, but also learn rich semantic information features; the CRF module realizes the constraint on the label prediction value and reduces the irregular recognition rate, so the accuracy rate of entity recognition is improved. Taking the Chinese technological literature, which is about fault diagnosis of electric power equipment as the experimental object, the experimental results show that the model identifi es and extracts Chinese entities more accurately than traditional methods. Thus, a comprehensive and accurate Chinese knowledge graph of electric power equipment faults could be constructed more easily.
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기술기반 셀프서비스 사용태도 및 사용의도에 대한 기술준비도, 사용자 특성, 상황적 요인의 조절효과
맹범기(Meng, Fanqi),박경수(Park, Kyung Soo),오승원(Oh, Seung Won) 한국서비스경영학회 2017 서비스경영학회지 Vol.18 No.3
The rapid growth of Technology-Based Self-Service today is increasingly questioning the acceptance of these types of services by all kinds of users under different situational contexts. This study examined the causal relationship between effects of perceived performance, perceived ease of use, and enjoyment on the formation factors of attitude to TBSS, the usage attitude to TBSS, and the usage intention to TBSS. In addition, we investigated whether the technological readiness index, user traits, and situational factors as moderating variable have a moderating effect on the causal relationship between the formation factors of attitude to TBSS and the usage attitude to TBSS. As a component of the moderating variable, optimism was one for Technology Readiness Index. Self-efficacy, self-consciousness, novelty seeking, and need for interaction were the User Traits. Finally, Situational Factors included perceived waiting time and perceived crowding. As a result of the analysis, causal relationships was found to have a significant effect, and the moderating effect was different for each factor. This study suggests implications and directions for TBSS service providers.
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Detection and Monitoring of Potential Geological Disaster Using SBAS-InSAR Technology
Wei Niu,Xiaonong Hu,Bo Lin,Fanqi Meng,Yong Zhang,Jin Zhao 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.11
As a global geological environment problem, geological disasters are more likely to induce severe geological disasters and cause loss of personnel and property due to their suddenness and concealment, frequent heavy rainfall and regular extreme weather. In this paper, Sentinel-1A data and DEM data combined with short baseline synthetic aperture interferar (SBAS-InSAR) technology are used to analyze and calculate the spatial-temporal evolution characteristics of surface deformation in Zibo-Weifang area of Shandong Province during 2016-2019. Linear fitting of InSAR monitoring deformation results is performed using level monitoring data to verify the accuracy of the results. The findings indicate that surface deformation in most of the study area is relatively stable, but in some areas, especially near Lucun Town, the maximum negative deformation rate exceeds 80mm/a. Based on the surface deformation results, a total of 377 potential geological disasters are identified using an integrated multi-source stereo observation system of the sky and ground. This identification is done by observing optical remote sensing images and taking the absolute value of surface deformation rate greater than 10 mm/a as the judgment basis, along with ground investigation and review. Several typical geological disaster sites are screened and they are found to be in unstable state. The research results can provide scientific support for geological disaster prevention and control in Shandong Province.
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