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Analysis of debt-paying ability of real estate enterprises based on fuzzy mathematics and K-means algorithm

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第5期37卷 6403-6414页

作者： Qiang, Qunli Anhui Jianzhu Univ Sch Econ & Management Hefei Anhui Peoples R China

Currently, there is a certain fluctuation in the real estate industry, so it is particularly important to analyze the solvency of real estate enterprises. In order to find a reliable model suitable for studying the difference in house prices, this study collects the research data through data collection, and uses the K-means clustering method to construct the corresponding model as a basic research in combination with the machine learning research method. At the same time, this paper compares the analysis effects of several common machine learning models and finds the advantages and disadvantages of these methods through mathematical statistics. In addition, combined with practice, this paper constructs a nonlinear generalized additive model, and based on machine learning technology, validates the validity of the model based on data analysis, the collected predictors. In view of the improvement of the solvency of real estate enterprises, diversified operation of real estate enterprises can maintain reasonable cash flow and make up for the defect of poor liquidity of real estate. Furthermore, this paper uses the stability method to find the optimal model. In addition, the generalized additive model effectively reveals the complex nonlinear relationship between continuous predictors and house prices. Through research, it can be seen that the nonlinear generalized additive model based on machine learning can play an important role in real estate industry forecasting and has certain theoretical reference significance for subsequent related research.

关键词： Real estate generalized additive model machine learning K-means Algorithm

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Isoscapes reveal patterns of δ¹³C and δ¹⁵N of pelagic forage fish and squid in the Northwest Pacific Ocean

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PROGRESS IN OCEANOGRAPHY 2019年 175卷 124-138页

作者： Ohshimo, Seiji Madigan, Daniel J. Kodama, Taketoshi Tanaka, Hiroshige Komoto, Kaoru Suyama, Satoshi Ono, Tsuneo Yamakawa, Takashi Seikai Natl Fisheries Res Inst 1551-8 Taira Machi Nagasaki 8512213 Japan Gulf Calif Int Res Ctr Santa Rosalia Bcs 23920 Mexico Japan Sea Natl Fisheries Res Inst Chuo Ku 5939-22 Suido Cho Niigata 9518121 Japan Natl Inst Far Seas Fisheries Shimizu Ku 5-7-1 Orido Shizuoka 4248633 Japan Univ Tokyo Bunkyo Ku 1-1-1 Yayoi Tokyo 1138657 Japan Tohoku Natl Fisheries Res Inst 25-259 Shimo Mekurakubo Same Hachinohe Aomori 0310841 Japan Natl Inst Far Seas Fisheries Kanazawa Ku 2-12-4 Fukuura Yokohama Kanagawa 2368648 Japan

Isoscapes of stable isotope ratios of carbon (delta C-13) and nitrogen (delta N-15) in pelagic fish and squid were generated using 1967 measured values of forage fish and squid in the Northwest Pacific Ocean. We then used generalized additive models (GAMs) to assess the explanatory variables that best predicted regional fish and squid delta C-13 and delta N-15 values. A total of 522 squid and 1445 forage fish were analyzed for delta C-13 and delta N-15. The explanatory variables/variates used in GAM analyses were geographical parameters (longitude and latitude), body mass, season, category of organism (fish or squid), and vertical habitat. The resulting isoscapes of delta C-13 showed higher values in the sub-tropical region and lower values in the sub-arctic region. The isoscape patterns of delta(15) N were more complex;higher values were found in both tropical and temperate regions, and lower values were observed in sub-tropical and sub-arctic regions. These heterogeneities in isoscapes of delta C-13 and delta N-15 in the Northwest Pacific could be caused by productivity dynamics, ocean currents and upwelling, and the degree of atmospheric fixation of carbon and nitrogen. These new isoscapes can be used in conjunction with predator delta C-13 and delta N-15 values to evaluate movements and trophic dynamics of predatory marine animals, including tunas, billfish, sharks, seabirds, and marine mammals, in the Northwestern Pacific Ocean.

关键词： Carbon and nitrogen fixation generalized additive model Marine predator Migration Stable isotope

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Chlorophyll a predictability and relative importance of factors governing lake phytoplankton at different timescales

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SCIENCE OF THE TOTAL ENVIRONMENT 2019年 648卷 472-480页

作者： Liu, Xia Feng, Jianfeng Wang, Yuqiu Nankai Univ Minist Educ Key Lab Pollut Proc & Environm Criteria Tianjin 300071 Peoples R China Nankai Univ Coll Environm Sci & Engn Tianjin Key Lab Environm Remediat & Pollut Contro Tianjin 300071 Peoples R China

Assessing the key drivers of eutrophication in lakes and reservoirs has long been a challenge, and many studies have developed empirical models for predicting the relative importance of these drivers. However, the relative roles of various parameters might differ not only spatially (between regions or localities) but also at a temporal scale. In this study, the relative roles of total phosphorus, total nitrogen, ammonia, wind speed and water temperature were selected as potential drivers of phytoplankton biomass by using chlorophyll a as a proxy for biomass. A generalized additive model (GAM) and a random forest model (RF) were developed to assess the predictability of chlorophyll a and the relative importance of various predictors driving algal blooms at different timescales in a freshwater lake. The results showed that the daily datasets yielded better predictability than the monthly datasets. In addition, at a daily scale, water temperature was a more important predictor of chlorophyll a than nutrients, and the importance of phosphorus was comparable to that of nitrogen. In contrast, at a monthly scale, nutrients are more important predictors than water temperature and phosphorus is a better predictor than nitrogen. This study indicates that the drivers of phytoplankton fluctuations vary at different timescales and that timescale has an influence on the relative roles of nitrogen and phosphorus limitation in lakes, which suggests that the temporal scale should be considered when explaining phytoplankton fluctuations. Moreover, this study provides a reference for the monitoring of phytoplankton fluctuations and for understanding the mechanisms underlying phytoplankton fluctuations at different timescales. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Phytoplankton Predictability Random forest generalized additive model Timescale

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Succession and interaction of surface and subsurface cyanobacterial blooms in oligotrophic/mesotrophic reservoirs: A case study in Miyun Reservoir

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SCIENCE OF THE TOTAL ENVIRONMENT 2019年 649卷 1553-1562页

作者： Su, Ming Andersen, Tom Burch, Michael Jia, Zeyu An, Wei Yu, Jianwei Yang, Min Chinese Acad Sci State Key Lab Environm Aquat Chem Res Ctr Ecoenvironm Sci POB 2871 Beijing 100085 Peoples R China Univ Oslo Dept Biosci POB 1033 N-0315 Oslo Norway Univ Adelaide Dept Ecol & Environm Sci Adelaide SA 5005 Australia Univ Chinese Acad Sci Beijing 100049 Peoples R China

Subsurface cyanobacterial blooms, are a significant source of odor problems in source water and have been recorded in many oligotrophic/mesotrophic drinking water reservoirs. In this study, we explored the key driving forces responsible for the succession between surface and subsurface cyanobacteria using ecological niche modelling based upon a case study in Miyun Reservoir, China. The results suggest a negative effect of water depth and surface light irradiance (I-0) on subsurface Planktothrix sp. growth (p-values < 0.001), and a unimodal effect of surface water temperature (T-0) with the optimum at 23 degrees C (p-value < 0.001). While the surface Microcystis spp. shows a strong positive relationship with temperature (T-0;p-value < 0.001), and significant effects for the interaction between T-0 and I-0 (p- value < 0.01). In addition, we identified the extent and type of interaction between subsurface and surface cyanobacteria and conclude that the high irradiance surface water combined with sufficient nutrients at the pre-bloom stage are key factors responsible for the preferential growth of surface cyanobacteria, while the gradual decline of the surface cyanobacteria in post-bloom stage is associated with nutrient reduction. This decline and loss of surface populations enhanced underwater irradiance and thus promoted the growth and allowed for succession of subsurface cyanobacteria in deeper layers where the nutrient supply was still adequate. Based upon this, the growth potentials for the subsurface and surface cyanobacteria are different under different environmental conditions: the subsurface cyanobacteria have greater growth potential than surface cyanobacteria in shallow oligotrophic and deep eutrophic reservoirs during median light irrigation seasons. (C) 2018 Elsevier B.V. All rights reserved.

关键词： generalized additive model Ecological niche Surface cyanobacteria Subsurface cyanobacteria Source water Taste and odor

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modeling PM2.5 Speciation Concentrations over California Using the MISRV23 Aerosol Product

Modeling PM2.5 Speciation Concentrations over California Usi...

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作者： Pelayo, Christian California State University Los Angeles

学位级别：M.S., Master of Science/Master of Surgery

Public health organizations are interested in better understanding the spatiotemporal variability of fine particulate matter (PM2.5) to relate exposure levels to human health effects. High levels of PM2.5 have been attributed to higher rates of human respiratory disease and premature death. While the health effects of total PM2.5 have been extensively studied, the health effects of speciated PM2.5 are poorly understood. The Interagency Monitoring of Protected Visual Environments (IMPROVE) and Chemical Speciation Network (CSN) ground monitor sites are capable of measuring speciated PM2.5. These data sets lack the necessary spatial resolution to capture the complex behavior of speciated PM2.5 because of emission, transport, and mixing processes. Aerosol optical depth (AOD) retrievals by the Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard Terra have previously been incorporated into models to predict ground level PM2.5 concentrations. The newly reprocessed MISRV23 data set has a 4.4 km2 resolution for the entire global MISR record, making it useful for epidemiology studies (Chau et al., 2020). In this study, fractional AOD, spatial, and temporal variable predictors from the MISRV23 data set are coupled with North American Regional Reanalysis (NARR) planetary boundary layer height (PBLH) and colocated with CSN and IMPROVE PM2.5 data into a generalized additive model (GAM) capable of predicting speciated PM2.5 concentrations of elemental carbon, organic carbon, nitrate, and sulfate over the entire state of California. Each model has an R2 of 0.553, 0.37, 0.487, and 0.607 respectively. model performance summaries indicate that every predictor variable is significant and that the models are capable of incorporating additional parameters to further improve performance. These models are used to generate surface maps of annual averaged speciated PM2.5 concentrations for the state of California.

关键词： Air quality California CSN generalized additive model IMPROVE MISR

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Urban landscape thresholds for bird diversity in China's major cities

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Global Ecology and Conservation 2025年 61卷

作者： Chi, Yueteng Liu, Zhenhuan Zhou, Yi Yang, Fan Carbon-Water Research Station in Karst Regions of Northern Guangdong School of Geography and Planning Sun Yat-Sen University Guangzhou 510006 China

Cities face significant biodiversity loss, but the thresholds of urban landscape alterations causing this loss remain unclear. Bird diversity serves as a key indicator, yet its large-scale response to landscape changes requires further exploration. Bird diversity is affected by multi-dimensional landscape and environmental factors;however, it is still unclear which variables play a major role and under what threshold conditions different variables increase or decrease bird diversity. This study used public datasets and citizen science bird records to quantify bird diversity and landscape patterns across China's 43 major cities. generalized additive models (GAMs) were employed to analyze bird diversity responses to landscape metrics and identify landscape thresholds. Our findings show that high bird diversity is predominantly observed in low-latitude and eastern coastal cities, and 42 cities hosting threatened species. Urban bird diversity distribution is non-linearly influenced by landscape patterns, and the main driving factors are the aggregation and coverage of forests and water bodies. We identified nine landscape thresholds conducive to maintaining urban bird diversity, recommending the preservation of 6.4–17.9 % of forest cover and more than 10.9 % of water bodies in cities, alongside strategies to optimize the connectivity of both green and blue spaces. While the thresholds linking bird diversity indicators to urban landscape metrics are not fully generalizable, certain robust thresholds offer valuable insights for landscape management, presenting a novel approach to bird conservation amidst urbanization. © 2025 The Authors

关键词： Bird diversity pattern Citizen science generalized additive model Landscape threshold Urban landscape management

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Estimates of influenza-associated hospitalisations in tropical Singapore, 2010-2017: Higher burden estimated in more recent years

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INFLUENZA AND OTHER RESPIRATORY VIRUSES 2019年第6期13卷 574-581页

作者： Ng, Yixiang Chua, Lily Ai Vee Ma, Stefan Jian Ming Lee, Vernon Minist Hlth Epidemiol & Dis Control Div Coll Med Bldg16 Coll Rd Singapore 169854 Singapore Minist Hlth Communicable Dis Div Singapore Singapore

Background We previously estimated Singapore's influenza-associated hospitalisation rate for pneumonia and influenza (P&I) in 2010-2012 to be 29.6 per 100 000 person-years, which corresponds to 11.2% of all P&I hospitalisations. Objectives This study aims to update Singapore's estimates of the influenza-associated pneumonia and influenza (P&I) hospitalisation burden using the latest data from 2010 to 2017. Methods We estimated the number of P&I hospitalisations associated with influenza using generalised additive models. We specified the weekly number of admissions for P&I and the weekly influenza positivity in the models, along with potential confounders such as weekly respiratory syncytial virus (RSV) positivity and meteorological data. Results In 2010-2017, 16.3% of all P&I hospitalisations in Singapore were estimated to be attributed to influenza, corresponding to an excess influenza-associated P&I hospitalisation rate of 50.1 per 100 000 person-years. Higher excess rates were estimated for children aged 0-4 years (186.8 per 100 000 person-years) and elderly aged >= 65 years (338.0 per 100 000 person-years). Higher influenza-associated hospitalisation rates were estimated for 2016 and 2017 (67.9 and 75.1 per 100 000 persons, respectively) years when the influenza A(H3N2) subtype was dominant. Conclusion Influenza burden in Singapore has increased since 2010. Influenza vaccination programmes should continue to be prioritised for the young and the elderly.

关键词： burden generalized additive model hospitalisation influenza pneumonia Singapore tropics

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Effects and interaction of meteorological factors on influenza: Based on the surveillance data in Shaoyang, China

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ENVIRONMENTAL RESEARCH 2019年 172卷 326-332页

作者： Liu, Zhidong Zhang, Jing Zhang, Ying Lao, Jiahui Liu, Yanyu Wang, Hui Jiang, Baofa Shandong Univ Sch Publ Hlth Dept Epidemiol 44 Wenhuaxi Rd Jinan 250012 Shandong Peoples R China Univ Sydney China Studies Ctr Sch Publ Hlth Sydney NSW Australia Shandong Univ Hosp 2 Dept Med Adm 247 BeiYuan Rd Jinan 250033 Shandong Peoples R China

Background: Previous studies have demonstrated that meteorological factors influence the incidence of influenza. However, little is known regarding the interactions of meteorological factors on the risk of influenza in China. Objective: The study aimed to evaluate the associations between meteorological factors and influenza in Shaoyang of southern China, and explore the interaction of temperature with humidity and rainfall. Methods: Weekly meteorological data and disease surveillance data of influenza in Shaoyang were collected from 2009 to 2012. According to the incubation period and infectious period of influenza virus, the maximum lag period was set as 3 weeks. A generalized additive model was conducted to evaluate the effect of meteorological factors on the weekly number of influenza cases and a stratification model was applied to investigate the interaction. Results: During the study period, the total number of influenza cases that were notified in the study area was 2506, with peak times occurring from December to March. After controlling for the confounders, each 5 degrees C decrease in minimum temperature was related to 8% (95%CI: 1-15%) increase in the number of influenza cases at a 1-week lag. There was an interaction between minimum temperature and relative humidity and the risk of influenza was higher in cold and less humid conditions than other conditions. The interaction between minimum temperature and rainfall was not statistically significant in our study. Conclusions: The study suggests that minimum temperature is inversely associated with influenza in the study area of China, and the effect can be modified by relative humidity. Meteorological variables could be integrated in current public health surveillance system to better prepare for the risks of influenza.

关键词： Influenza Meteorological factors Interaction generalized additive model Stratification model

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Short-term effect of PM2.5 on pediatric asthma incidence in Shanghai, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2019年第27期26卷 27832-27841页

作者： Ma, Yuxia Yu, Zhiang Jiao, Haoran Zhang, Yifan Ma, Bingji Wang, Fei Zhou, Ji Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Gansu Peoples R China Tacheng Meteorol Bur Tacheng 834700 Peoples R China Key Lab Meteorol & Hlth Shanghai Shanghai 200030 Peoples R China

Recent epidemiological studies pointed out that air pollution has a significant impact on pediatric asthma. Shanghai is one of the biggest cities in China, and the short-term effect of atmospheric particulate matter on the incidence of pediatric asthma has become a hot topic. From January 1, 2009, to December 31, 2010, we used daily measurements of pollutant concentrations, daily weather data, and daily records of pediatric asthma hospital visits from local authorities to evaluate the short-term effect of air pollution on pediatric asthma incidence in Shanghai, China. We used a generalized additive model (GAM) in the analysis, and the controlled confounding factors include long-term trends, day-of-the-week effects, and weather elements. We divided the entire study group into different age-subgroups. In addition, we took a variety of lag models into consideration. The results showed a strong connection between concentrations of fine particulate matter (PM2.5) and pediatric asthma hospital visits from 2009 to 2010 in Shanghai, China. For the entire study group, the greatest relative risk (RR) of PM2.5 on pediatric asthma hospital visits was 1.060 on a lag of 4 days. As for the three different age-subgroups, the greatest RR of PM2.5 on pediatric asthma hospital visits was 1.061 (at a lag of 5 days), 1.071 (at a lag of 4 days), and 1.052 (at a lag of 2 days), for the under-2-year-olds, 3-to-5-year-olds, and the 6-to-18-year-olds, respectively. The overall short-term effect of PM2.5 on pediatric asthma hospital visits was relatively stronger in younger children. Within the year, we detected the strongest seasonal effect of PM2.5 on pediatric asthma hospital visits in Summer. When adding other air pollutants in the analysis model, RR of PM2.5 on pediatric asthma hospital visits would be increased.

关键词： Pediatric asthma PM2 5 generalized additive model Hospital visits Relative risk

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On statistical nowcasting of road surface temperature

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METEOROLOGICAL APPLICATIONS 2019年第1期26卷 1-13页

作者： Yin, Zhicong Hadzimustafic, Jasmina Kann, Alexander Wang, Yong Nanjing Univ Informat Sci & Technol Joint Int Res Lab Climate & Environm Change ILCEC Key Lab Meteorol Disaster Minist EducCIC FEMD Nanjing Jiangsu Peoples R China Beijing Meteorol Bur Beijing Meteorol Serv Ctr Beijing Peoples R China Cent Inst Meteorol & Geodynam ZAMG Dept Forecasting Models Vienna Austria

In this study, multiple linear regression (MLR) and the generalized additive model (GAM) approaches were used to build statistical models for 6 hr nowcasts of road surface temperature (RST) in the northeast of Vienna, Austria. GAMs were more suitable for historical analysis, particularly for decomposing the terms to identify the different influences of the meteorological covariates on RST. By contrast, for RST nowcasting, the simpler and more robust MLR models are recommended, with better applicability for real-time operational runs. In MLR models, the forecasted air temperature was the most prominent predictor, followed by the measured RST. In independent testing, the MLR models showed better prediction skill, with daily root-mean-square error (RMSE) around 1 degrees C. In accordance with the linear correlativity, the MLR models were built with more predictors for daytime than at night but still generated a larger RMSE at midday. Furthermore, the MLR models could reproduce the correct diurnal variation and could forecast RST below freezing point better than above 0 degrees C. Four case studies, i.e. snowy, cold front, cloudy and sunny, were diagnosed in detail. The predicted RSTs were close to the measurements and depicted the trend well, including the persistent and rapid cooling (warming) and correct diurnal variation.

关键词： generalized additive model multiple linear regression nowcasting road surface temperature

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