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LSTM Deep Neural Network Based Power Data Credit Tagging Technology

TEHNICKI VJESNIK-TECHNICAL GAZETTE 2023年第1期30卷 324-334页

作者： LI, Ding Chen, Jiayi Wang, Zhuo Song, Yuehui State Grid Xiongan Financial Technol Grp Co Ltd Beijing Peoples R China

The value of power data credit reporting in the social credit system continues to increase, and the government, users and the whole society have deep expectations and support for power data credit reporting. This paper will combine the data labeling theory as the support, define the power data label and explain its labeling implementation. Based on the construction of knowledge graph, the method of labeling power data is introduced in detail: demand analysis method, index selection method, data cleaning method and data desensitization method. Use the sorted data labels to establish a label system for power data, and through its system, visualize the comprehensive situation of enterprise power data credit information to meet the development of power data credit business. This paper takes shell enterprises as the main representatives of credit risk enterprises, analyzes the power data in the three stages before and after loans, and builds a value mining model for power credit data. In the future, the data labeling technology and value mining model of the power data credit business will be comprehensively applied, and the power data label library and credit model library will be established and continuously improved, so as to facilitate the evaluation of the operation of the enterprise at different stages.

关键词： labeling logistic regression model power credit data value mining

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Evaluating the factors whether road humps affect the living environment of the residents in the residential areas in Malaysia

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Transportation Research Procedia 2023年 72卷 439-446页

作者： Khairun Sarah Radhiah Bachok Abdul Azeez Kadar Hamsa Deparrment of Urban and Regional Planning International Islamic University Malaysia P.O. Box 10 Kuala Lumpur 50728 Malaysia

In this study, six residential areas within Klang valley in Malaysia were selected to evaluate the perceptions of the residents on whether road humps had actually improved the living environment through reduction in traffic speed and noise level of the moving vehicles. About 480 duly filled-in questionnaires were used in this study. Two binary logistic regression models were developed, one evaluating factors that influence residents’ perceptions on whether road humps had any effect on improving living environment through reduction in the noise level of the vehicles (model 1) and the other on improving living environment through reduction in the speed of the vehicles (model 2). Overall, the results show that the residents were more likely to agree that road humps had, indeed, improved their living environment through reduction in traffic speeds as compared to traffic noise.

关键词： Road humps traffic calming measure living environment residential area logistic regression model Malaysia

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Landslides triggered by the 6 September 2018 Mw 6.6 Hokkaido, Japan: an updated inventory and retrospective hazard assessment

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EARTH SCIENCE INFORMATICS 2021年第1期14卷 247-258页

作者： Cui, Yulong Bao, Pengpeng Xu, Chong Ma, Siyuan Zheng, Jun Fu, Gui Anhui Univ Sci & Technol Sch Civil Engn & Architecture Huainan 232001 Anhui Peoples R China Minist Emergency Management China Natl Inst Nat Hazards Beijing 100085 Peoples R China China Earthquake Adm Inst Geol Key Lab Act Tecton & Volcano Beijing 100029 Peoples R China Zhejiang Univ Dept Civil Engn Hangzhou 310058 Zhejiang Peoples R China

On September 6, 2018, an Mw 6.6 earthquake occurred in Hokkaido, Japan, triggering massive landslides. Based on the 0.3 m-resolution Pleiades-1 satellite image on the Google Earth platform, we constructed an updated co-seismic landslide inventory for this event, which permitted to map 12,586 landslides. These slope failures are featured by a large number, wide spread, large scales, and local dense distribution. Considering nine influence factors, i.e. elevation, slope angle, slope aspect, curvature, distance to road, distance to river, distance to the epicenter, lithology, and topography, the logistic regression model was applied to carry out a retrospective hazard assessment of earthquake-triggered landslides in the affected area, and the rationality of such prediction was verified by the real landslides mapped. Results show that the landslide hazard evaluation map is in good agreement with the actual landslide distribution. The success rate of the hazard assessment map is 87.0% compared to training samples, and 86.5% compared to testing samples, respectively. The updated landslide inventory is a useful complement to the existing landslide inventory maps and the landslide hazard assessment map is helpful for landslide disaster prevention and reduction and reconstruction planning in the affected area.

关键词： Co-seismic landslides Visual interpretation Landslide inventory logistic regression model Retrospective hazard assessment

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HUMAN VACCINES & IMMUNOTHERAPEUTICS 2021年第9期17卷 3214-3220页

作者： Feng, Yongliang Wang, Jianmin Shao, Zhihong Chen, Zhuanzhuan Yao, Tian Dong, Shuang Wu, Yuanting Shi, Xiaohong Shi, Jing Liu, Guangming Bai, Jingen Guo, Hongping Liu, Hongting Wu, Xiaofeng Liu, Liming Song, Xiaohui Zhu, Jiangtao Wang, Suping Liang, Xiaofeng Shanxi Med Univ Sch Publ Hlth Taiyuan Shanxi Peoples R China Shanxi Med Univ Ctr Clin Epidemiol & Evidence Based Med Taiyuan 030001 Shanxi Peoples R China Linfen Cent Hosp Dept Nephrol Linfen Shanxi Peoples R China Changzhi Med Coll Clin Lab Heping Hosp Changzhi Shanxi Peoples R China Lvliang Peoples Hosp Dept Nephrol Lvliang Shanxi Peoples R China Linfen Peoples Hosp Dept Nephrol Linfen Shanxi Peoples R China Yuncheng Cent Hosp Dept Nephrol Yuncheng Shanxi Peoples R China Second Peoples Hosp Jinzhong Dept Nephrol Jinzhong Shanxi Peoples R China Fenyang Hosp Shanxi Prov Dept Nephrol Fenyang Shanxi Peoples R China Changzhi Hosp Tradit Chinese Med Dept Nephrol Changzhi Shanxi Peoples R China Chinese Prevent Med Assoc Beijing 100000 Peoples R China

The non/hypo-response rate of the hepatitis B vaccine among hemodialysis (HD) patients is still high, it is of great significance to explore the influencing factors and their relationships. To study the related factors and their relationships using logistic regression model and Chi-squared Automatic Interaction Detection (CHAID) decision tree model. A randomized controlled trial was conducted between February 2014 and May 2015 in China. HD patients being serologically negative for HBsAg and anti-HBs were randomly assigned to receive three intramuscular injections of the standard dose (20 mu g) or high dose (60 mu g) of recombinant hepatitis B vaccine at months 0, 1, and 6. Those with anti-HBs concentrations <100 mIU/mL, and >= 100 mIU/mL at month 7 were considered as non/hypo-response and high-level response, respectively. The non/hypo-response was 31.34% (89/284). After adjustment for confounders, logistic analysis showed that males (OR = 2.203, 95%CI: 1.109-4.367) and those with higher dialysis frequency (>4 times per 2 weeks) (OR = 1.918, 95%CI: 1.015-3.626) had a significant risk of non/hypo-response. While the CHAID analysis showed that gender, dose, and dialysis frequency were influencing factors of non/hypo-response, and gender is most important. The interaction between gender and dialysis frequency had the greatest effect on immunization, and followed by the interaction between dialysis frequency and vaccine dose. Taken together, gender, dose and dialysis frequency were influencing factors of hepatitis B vaccine in HD patients.

关键词： Hepatitis B vaccine hemodialysis non hypo-response logistic regression model Chi-squared automatic interaction detection

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A Potential Three-Gene-Based Diagnostic Signature for Hypertension in Pregnancy

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INTERNATIONAL JOURNAL OF GENERAL MEDICINE 2021年 14卷 6847-6856页

作者： Liu, Yan Wang, Zhenglu Zhao, Lin Nankai Univ Tianjin Cent Hosp 1 Dept Obstet 24 Fukang Rd Tianjin 300192 Peoples R China Nankai Univ Tianjin Cent Hosp 1 Biobank Tianjin 300192 Peoples R China

Background: Hypertensive disorders of pregnancy affect approximately 5-10% of all pregnancies, and this study aims to identify potential diagnostic signatures. Methods: We downloaded the mRNA profiles of GSE75010 (placenta samples) and GSE48424 (blood samples) datasets with or without hypertension in pregnancy from the Gene Expression Omnibus database. Differential expression analysis was performed on the placenta samples using limma package of R language. GO terms and KEGG pathways enrichment analyses were performed on the placenta samples by the clusterProfiler package of R language. Infiltrating immune cell proportion of the placenta samples was evaluated using CIBERSORT software. The key genes involved in hypertension in pregnancy were screened from protein-protein interaction (PPI) network constructed based on the differentially expressed genes (DEGs). The logistic regression model was constructed by the glm package of R language, and receiver operating characteristic (ROC) curve was plotted to determine the accuracy of the model. Results: For the placenta samples, a total of 104 DEGs were identified, and 39 GO terms and 7 KEGG pathways were significantly enriched based on these 104 genes. Furthermore, the analysis of infiltrating immune cells indicated that the difference in the amount of immune cells might be the potential cause of hypertension in pregnancy. The logistic regression model was constructed based on three optimal genes (LEP, PRL and IGFBP1) screened from PPI network and could efficiently separate patients with hypertension in pregnancy from healthy subjects. Conclusion: A predictive model based on three potential genes LEP, PRL and IGFBP1 was obtained, suggesting that these genes might be potential diagnostic signatures for hypertension in pregnancy.

关键词： hypertension in pregnancy diagnostic signature GO terms and KEGG pathways analyses PPI network logistic regression model

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Bias-reduced estimators of conditional odds ratios in matched case-control studies with unmatched confounding

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BIOMETRICAL JOURNAL 2023年第4期65卷 2200133-2200133页

作者： Blagus, Rok Univ Ljubljana Inst Biostat & Med Informat Med Fac Ljubljana Slovenia Univ Ljubljana Fac Sports Ljubljana Slovenia Univ Primorska Fac Math Nat Sci & Informat Technol Koper Slovenia Univ Ljubljana Inst Biostat & Med Informat Med Fac Vrazov trg 2 Ljubljana 1000 Slovenia

We study bias-reduced estimators of exponentially transformed parameters in general linear models (GLMs) and show how they can be used to obtain bias-reduced conditional (or unconditional) odds ratios in matched case-control studies. Two options are considered and compared: the explicit approach and the implicit approach. The implicit approach is based on the modified score function where bias-reduced estimates are obtained by using iterative procedures to solve the modified score equations. The explicit approach is shown to be a one-step approximation of this iterative procedure. To apply these approaches for the conditional analysis of matched case-control studies, with potentially unmatched confounding and with several exposures, we utilize the relation between the conditional likelihood and the likelihood of the unconditional logit binomial GLM for matched pairs and Cox partial likelihood for matched sets with appropriately setup data. The properties of the estimators are evaluated by using a large Monte Carlo simulation study and an illustration of a real dataset is shown. Researchers reporting the results on the exponentiated scale should use bias-reduced estimators since otherwise the effects can be under or overestimated, where the magnitude of the bias is especially large in studies with smaller sample sizes.

关键词： bias correction Cox proportional hazards model data augmentation logistic regression model relative risk estimation

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Did new electricity progressive tariff system change energy usage pattern in Seoul apartments? Evidence from integrated multisource dataset and combined analytical models

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ENERGY AND BUILDINGS 2023年 287卷

作者： Quan, Steven Jige Kim, Kyungdo Seoul Natl Univ Grad Sch Environm Studies City Energy Lab Seoul South Korea Seoul Natl Univ Environm Planning Inst Seoul South Korea Seoul Natl Univ Artificial Intelligence Inst Seoul South Korea Seoul Inst Dept Safety & Environm Res Seoul South Korea

A new electricity progressive tariff (PT) system was introduced to cities in South Korea at the end of 2016 to replace the previous one as a policy response to increased energy demand and costs in hotter summers. Public concerns have been raised over its effects on annual energy use and energy poverty. However, studies on this topic are very few due to the lack of relevant data. In the broader literature on the effect of the PT system, studies are limited in that they mostly focus on household characteristics. This study contributes to the literature and practical discussions by examining how the new PT system influences residential electricity use in 243 sample apartments in Seoul, considering a wide range of factors that impact energy use decisions. An integrated urban dataset was developed based on urban big data from multiple sources, and a combination of two models was used for analysis. The interrupted time series analysis was adopted to find whether the change in household electricity use was significant for each apartment using the dataset. A logistic regression model was then used to examine the relationships between the significance of change and influential factors in energy use and building, household, apartment, and neighborhood. Results suggest that nearly half of the sample apartments significantly increased electricity usage, and energy and built environment factors significantly influenced the change. Furthermore, higher-income groups were found to benefit more from the new PT system. The findings provide a reference for policymakers to evaluate the new policy and develop strategies toward broad sustainability goals. Given the wicked nature of urban energy policy, suggestions were made on policy implementation design and urban data integration for more rigorous evaluation. (c) 2023 Elsevier B.V. All rights reserved.

关键词： Energy pricing policy Residential electricity use Policy outcome evaluation Urban big data Interrupted time series analysis logistic regression model

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The study of plain CT combined with contrast-enhanced CT-based models in predicting malignancy of solitary solid pulmonary nodules

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SCIENTIFIC REPORTS 2024年第1期14卷 1-9页

作者： Zhang, Wenjia Cui, Xiaonan Wang, Jing Cui, Sha Yang, Jianghua Meng, Junjie Zhu, Weijie Li, Zhiqi Niu, Jinliang Shanxi Med Univ Dept Med Imaging 56 Xinjian Rd Taiyuan 030000 Shanxi Peoples R China Tianjin Med Univ Canc Inst & Hosp Natl Clin Res Ctr Canc Dept Radiol Key Lab Canc Prevent & Therapy Tianjin Peoples R China Hangzhou Med Coll Sch Publ Hlth Dept Epidemiol & Hlth Stat Hangzhou Peoples R China Shanxi Med Univ Hosp 2 Dept Radiol Taiyuan Peoples R China Shanxi Med Univ Hosp 2 Dept Cardiothorac Surg Taiyuan Peoples R China

To compare the diagnostic performance between plain CT-based model and plain plus contrast CT-based modelin the classification of malignancy for solitary solid pulmonary nodules. Between January 2012 and July 2021, 527 patients with pathologically confirmed solitary solid pulmonary nodules were collected at dual centers with similar CT examinations and scanning parameters. Before surgery, all patients underwent both plain and contrast-enhanced chest CT scans. Two clinical characteristics, fifteen plain CT characteristics, and four enhanced characteristics were used to develop two logistic regression models: model 1 (plain CT only) and model 2 (plain + contrast CT). The diagnostic performance of the two models was assessed separately in the development and external validation cohorts using the AUC. 392 patients from Center A were included in the training cohort (median size, 20.0 [IQR, 15.0-24.0] mm;mean age, 55.8 [SD, 9.9] years;male, 53.3%). 135 patients from Center B were included in the external validation cohort (median size, 20.0 [IQR, 16.0-24.0] mm;mean age, 56.4 [SD, 9.6] years;male, 51.9%). Preoperative patients with 201 malignant (adenocarcinoma, 148 [73.6%];squamous cell carcinoma, 35 [17.4%];large cell carcinoma,18 [9.0%]) and 326 benign (pulmonary hamartoma, 118 [36.2%];sclerosing pneumocytoma, 35 [10.7%];tuberculosis, 104 [31.9%];inflammatory pseudonodule, 69 [21.2%]) solitary solid pulmonary nodules were gathered from two independent centers. The mean sensitivity, specificity, accuracy, PPV, NPV, and AUC (95%CI) of model 1 (Plain CT only) were 0.79, 0.78, 0.79, 0.67, 0.87, and 0.88 (95%CI, 0.82-0.93), the model 2 (Plain + Contrast CT) were 0.88, 0.91, 0.90, 0.84, 0.93, 0.93 (95%CI, 0.88-0.98) in external validation cohort, respectively. A logistic regression model based on plain and contrast-enhanced CT characteristics showed exceptional performance in the evaluation of malignancy for solitary solid lung nodules. Utilizing this contrast-enhanced CT mod

关键词： Pulmonary nodules logistic regression model Prediction Contrast-enhanced CT

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The design of early warning software systems for financial crises in high-tech businesses using fusion models in the context of sustainable economic growth

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PEERJ COMPUTER SCIENCE 2023年 9卷 e1326页

作者： Guo, Houfang Suzhou Ind Pk Inst Serv Outsourcing Suzhou Jiangsu Peoples R China

Enterprises are urged to continue implementing the sustainable development strategy in their business operations as "carbon neutrality" and "carbon peak" gradually become the current stage's worldwide targets. High-tech businesses (HTE) need to be better equipped to manage financial risks and avoid financial crises in the face of severe market competition. The most popular machine learning models- logistic regression, XGBoost, and BP neural networks-are chosen as the base models in this study. The three models are combined using the stacking method to train and forecast the fusion models while offering other researchers some basic model research ideas. The financial crisis early warning (FCEW) of HTE is built concurrently by contrasting the fusion of various quantitative basis models and the fusion procedures of voting and averaging. The outcomes demonstrate that the fusion model outperforms the single model in terms of performance, and the stacked fusion model has the best early warning impact. By comparing and comparing the effect of three fusion models on financial crisis warnings of high-tech enterprises, it makes up for the defect of low accuracy of traditional forecasting methods. It improves the sustainable development path of enterprises.

关键词： High-tech enterprises logistic regression model XGboost BP neural network Fusion model

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Novel Prognostic models for Predicting the 180-day Outcome for Patients with Hepatitis-B Virus-related Acute-on-chronic Liver Failure

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Journal of Clinical and Translational Hepatology 2021年第4期9卷 514-520页

作者： Ran Xue Jun Yang Jing Wu Zhongying Wang Qinghua Meng Department of Medical Oncology Beijing You’an HospitalCapital Medical UniversityBeijingChina Key Laboratory of Carcinogenesis&Translational Research(Ministry of Education/Beijing) Early Drug Development CenterPeking University Cancer Hospital&InstituteBeijingChina Department of Integrated Traditional and Western Liver Disease Beijing You’an HospitalCapital Medical UniversityBeijingChina Department of Infection Center Beijing You’an HospitalCapital Medical UniversityBeijingChina

Background and Aims:It remains difficult to forecast the 180-day prognosis of patients with hepatitis B virus-acuteon-chronic liver failure(HBV-ACLF)using existing prognostic *** present study aimed to derive novel-innovative models to enhance the predictive effectiveness of the 180-day mortality in ***:The present cohort study examined 171 HBV-ACLF patients(non-survivors,n=62;survivors,n=109).The 27 retrospectively collected parameters included the basic demographic characteristics,clinical comorbidities,and laboratory *** stepwise logistic regression(LR)and the classification and regression tree(CART)analysis were used to derive two predictive ***,a nomogram was created based on the LR *** accuracy of the LR and CART model was detected through the area under the receiver operating characteristic curve(AUROC),compared with model of end-stage liver disease(MELD)***:Among 171 HBV-ACLF patients,the mean age was 45.17 years-old,and 11.7%of the patients were *** LR model was constructed with six independent factors,which included age,total bilirubin,prothrombin activity,lymphocytes,monocytes and hepatic *** following seven variables were the prognostic factors for HBV-ACLF in the CART model:age,total bilirubin,prothrombin time,lymphocytes,neutrophils,monocytes,and blood urea *** AUROC for the CART model(0.878)was similar to that for the LR model(0.878,p=0.898),and this exceeded that for the MELD scores(0.728,p<0.0001).Conclusions:The LR and CART model are both superior to the MELD scores in predicting the 180-day mortality of patients with *** the LR and CART model can be used as medical decision-making tools by clinicians.

关键词： Classification and regression tree Acute-on-chronic hepatitis B liver failure MELD scores logistic regression model

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