检索结果-内蒙古大学图书馆

Oceans MTS/IEEE Washington (Conference)

作者： Yingli Tang Shijun He Haiyang He Peimin He Hairong Qi College of Information Shanghai Ocean University China

ISBN: (纸本)9781467393744

Green algae (Enteromorpha prolifera) bloom, also known as the green tide, is becoming a new type of marine ecological disaster. More and more studies have been conducted to investigate the cause of green tide as well as its growth and drifting characteristics. However, most existing works either rely on single factor analysis or support vector machine-based multi-factor analysis that do not have an appropriate mechanism to handle categorical data. In this paper, categorical data analysis is adopted to study the effect of multiple environmental factors to the green algae evolution. Among the five factors we studied, temperature, wind force, and wave height have numerical values but weather condition and wind direction are nominal variables. We focus on the study of the correlation between these environmental factors and the size of distribution area of the green tide. logistic regression models are built using remote sensing data from the Southern Yellow Sea acquired in 2013. Comprehensive analysis and evaluation are carried out, showing the main factors that affect the size of the bloom to be temperature and wave height, as well as their interaction. We also obtain the influence level of each main factor such that accurate prediction and early warnings of green tide can be made possible to alleviate the damage of the bloom.

关键词： Categorical analysis Green algae blooms Environmental monitoring Multi-factor analysis logistic regression model

来源：评论

学校读者我要写书评

暂无评论

Quantitative Measurement of Urban Expansion and Its Driving Factors in Qingdao:An Empirical Analysis Based on County Unit Data

引用

Journal of Resources and Ecology 2015年第3期6卷 172-179页

作者：李秋颖方创琳李广东任周鹏中国科学院地理科学与资源研究所北京100101 中国科学院大学北京100049

Qingdao is one of the essential growth poles in the process of new-type urbanization in Shandong Province. The study on the relationship between urban expansion and driving factors in this area is representative. This paper examined urban expansion from the perspective of non-urban to urban conversion, detailing an empirical investigation into the spatiotemporal variations and impact factors of urban expansion in Qingdao. By using the Urban Expansion Intensity Index （UEII） and Urban Expansion Differentiation Index （UEDI）, the spatial and temporal difference of urban expansion in the Municipal District, Jiaozhou County, Jimo County, Pingdu County, Jiaonan County and Laixi County were calculated on a county unit data set for the period 1990 to 2008. A GIS and logistical regression models were applied for discussing the results of various factors in land use change. Results indicated that the elevation and slope factors showed negative effects to urban expansion. Distance to the city center and to road both also conferred negative effects. The population density and GDP were vital and positive factors of urban conversion. Neighborhood factors showed consistently positive effects. The magnitude of factors was various in different counties. A better understanding of the factors influencing land use change could support land use management and planning decisions.

关键词： urban expansion driving factors logistic regression model Qingdao City

来源：评论

学校读者我要写书评

暂无评论

Predicting bank loan recovery rates with a mixed continuous-discrete model

引用

APPLIED STOCHASTIC modelS IN BUSINESS AND INDUSTRY 2014年第2期30卷 99-114页

作者： Calabrese, Raffaella Univ Milano Bicocca I-20123 Milan Italy

To represent the high concentration of recovery rates at the boundaries, we propose to consider the recovery rate as a mixed random variable, obtained as the mixture of a Bernoulli random variable and a beta random variable. We suggest to estimate the mixture weights and the Bernoulli parameter by two logistic regression models. For the recovery rates belonging to the interval (0,1), we model, jointly, the mean and the dispersion by using two link functions, so we propose the joint beta regression model that accommodates skewness and heteroscedastic errors. This methodological proposal is applied to a comprehensive survey on loan recovery process of Italian banks. In the regression model, we include some macroeconomic variables because they are relevant to explain the recovery rate and allow to estimate it in downturn conditions, as Basel II requires. Copyright (c) 2012 John Wiley & Sons, Ltd.

关键词： downturn recovery rate mixed random variable joint beta regression model logistic regression model

来源：评论

学校读者我要写书评

暂无评论

A Mathematical View of Weights-of-Evidence, Conditional Independence, and logistic regression in Terms of Markov Random Fields

引用

MATHEMATICAL GEOSCIENCES 2014年第6期46卷 691-709页

作者： Schaeben, Helmut 1. Geomathematics and Geoinformatics Freiberg Germany

New light is shed on mathematical methods of potential modeling from the point of view of Markov random fields. In particular, weights-of-evidence and logistic regression models are discussed in terms of graphical models possessing Markov properties, where the notion of conditional independence is essential, and will be related to log-linear models. While weights-of-evidence with respect to indicator predictor variables and logistic regression with unrestricted predictor variables model conditional probabilities of an indicator random target variable, the subject of log-linear models is the joint probability of random variables. The relationship to log-linear models leads to a likelihood ratio test of conditional independence, rendering an omnibus test of conditional independence restricted by a normality assumption obsolete. Moreover, it reveals a hierarchy of methods comprising weights-of-evidence, logistic regression without interaction terms, and logistic regression including interaction terms, where each former method is a special case of the consecutive latter method. The assumptions of conditional independence of all predictor variables given the target variable lead to logistic regression without interaction terms. Violations of conditional independence are compensated exactly by corresponding interaction terms, no cumbersome approximate corrections are needed. Thus, including interaction terms into logistic regression models is an appropriate means to account for lacking conditional independence. logistic regression exempts from the burden to worry about lack of conditional independence. Eventually, the relationship to log-linear models renders logistic regression with indicator predictor variables optimum for discrete predictor variables. Weights-of-evidence applies for indicator predictor variables only, logistic regression applies without restrictions of the type of predictor variables and approximates the proper distribution in the general case.

关键词： Weights-of-evidence Conditional independence logistic regression model Graphical models Markov random field Log-linear models

来源：评论

学校读者我要写书评

暂无评论

UNDERSTANDING SOIL CONSERVATION DECISION OF FARMERS IN THE GEDEB WATERSHED, ETHIOPIA

引用

LAND DEGRADATION & DEVELOPMENT 2014年第1期25卷 71-79页

作者： Tesfaye, A. Negatu, W. Brouwer, R. van der Zaag, P. Vrije Univ Amsterdam Inst Environm Studies Dept Environm Econ NL-1081 HV Amsterdam Netherlands Univ Addis Ababa Ctr Rural Dev Coll Dev Studies Addis Ababa Ethiopia Inst Water Educ UNESCO IHE Delft Netherlands Delft Univ Technol Delft Netherlands

The aim of this study was to investigate the main factors that influence smallholders' adoption decision of soil conservation measures in the Gedeb watershed. Data from 498 household heads who live in the three districts of the watershed were analysed using the binary logistic regression model. We find that farmers need adequate cash to invest in soil conservation measures. Moreover, farmers would be more encouraged to implement soil conservation measures when they have larger areas of cropland. We explore the possibility that when farmers presume that they have fertile land, they exploit their land more. This hints at the need for extension advice about the benefit of sustainable use of farmers' cropland so that they can maintain their land and pass it on to the future generation. Farmers' awareness about the benefit of land management practices and recognition of the problem erosion is causing on their crop land are central to their decision to adopt soil conservation measures. Furthermore, to adopt these measures, farmers have to be convinced about the effectiveness of these measures. Thus, awareness creation and demonstration of the effectiveness of these measures is essential. Because of the transboundary nature of the problem, policy makers in downstream countries that are suffering from the off-site impact (e.g. Sudan) would benefit from the information provided and support efforts in the implementation of soil conservation measures. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： soil erosion soil conservation measures logistic regression model Gedeb watershed Ethiopia

来源：评论

学校读者我要写书评

暂无评论

Identification of interconnections between landscape pattern and urban dynamics-Case study Bratislava, Slovakia

引用

ECOLOGICAL INDICATORS 2014年 42卷 104-111页

作者： Baus, Peter Kovac, Urban Paudisova, Eva Kohutkova, Ivana Kornornik, Jozef Slovak Univ Technol Bratislava SPECTRA Ctr Excellence Bratislava 81243 Slovakia Slovak Acad Sci Inst Forest Ecol Bratislava 81243 Slovakia Comenius Univ Fac Nat Sci Dept Landscape Ecol Bratislava 84215 Slovakia Comenius Univ Fac Management Dept Econ & Finance Bratislava 82005 25 Slovakia

The change of land use in urban and suburban areas is an on-going process. The aim of this paper is to study and statistically model landscape patterns changes in the Bratislava region (Slovakia) between 2002 and 2011. In the study, we perform the classic landscape-ecological method of land use mapping, and several spatial analytical tools provided by the GIS environment with statistical modeling using obtained spatial data. In order to explicitly study the determinants of landscape patterns changes between 2002 and 2011, firstly an exploratory principal component analysis (PCA) is performed with variables obtained from GIS modeling. Secondly, the results from PCA are used in the logistic regression model. The landscape patterns changes were defined as transition areas in which the change of function has been performed in the study time period. The proposed regression model estimates the threshold probability of the landscape patterns' changes of transition areas under the effect of the adjacent areas. In order to accurately capture land use changes, high resolution aerial photographs of the Bratislava area including the city and surrounding villages from 2002 to 2011 were analyzed. The spatial buffers mapping of the transition areas in the GIS environment was based on data from ortophotos in the precise scale of 1:2000. Key methodology findings are regularities about the process of urban dynamics, focused on the change of urban boundaries in the urban system contact area. Various behavior rules have been defined such as embedded distance, spatial pattern and transition probabilities, which are essential in the proposed logistic regression model. In order to pragmatically incorporate the regression model as a software model tool, it needs to generate effective urban simulations consistent with GIS data inputs, outputs and related functionality. This enables utilizing the software model, which might be incorporated as a plugin in the GIS environment. Both GIS and sta

关键词： Urban dynamics Landscape pattern GIS Bratislava Principal component analysis logistic regression model

来源：评论

学校读者我要写书评

暂无评论

The application of bacterial indicator phylotypes to predict shrimp health status

引用

APPLIED MICROBIOLOGY AND BIOTECHNOLOGY 2014年第19期98卷 8291-8299页

作者： Xiong, Jinbo Zhu, Jianlin Zhang, Demin Ningbo Univ Sch Marine Sci Ningbo 315211 Zhejiang Peoples R China Ningbo Univ Fac Architectural Civil Engn & Environm Ningbo 315211 Zhejiang Peoples R China 2011 Ctr Modern Marine Aquaculture East China Sea Ningbo Zhejiang Peoples R China

The incidence of shrimp disease is closely associated with the microbial composition in surrounding water, but it remains uncertain whether microbial indicator phylotypes are predictive for shrimp health status (healthy or diseased). To test this idea, we combined the data from our previous works, to investigate the feasibility of indicator phylotypes as independent variables to predict the health status during a shrimp culture procedure. The results showed linearly increased dissimilarities (P < 0.001) of the bacterioplankton community over time, while the communities dramatically deviated from this defined trend when disease occurred. This sudden shift in the bacterial community appears to cause severe mass mortality of the shrimps. In particular, we created a model to identify indicators that discriminated ponds with diseased shrimp populations from these with healthy shrimp populations. As a result, 13 indicative families were screened, in which seven are healthy indicator and six are diseased indictor. An improved logistic regression model additionally revealed that the occurrences of these indicator families could be predictive of the shrimp health status with a high degree of accuracy (> 79 %). Overall, this study provides solid evidences that indicator phylotypes could be served as independent variables for predicting the incidences of shrimp disease.

关键词： Bacterioplankton community Indicator phylotypes Incidence of disease logistic regression model

来源：评论

学校读者我要写书评

暂无评论

Climate change increases risk of fusarium ear blight on wheat in central China

引用

ANNALS OF APPLIED BIOLOGY 2014年第3期164卷 384-395页

作者： Zhang, X. Halder, J. White, R. P. Hughes, D. J. Ye, Z. Wang, C. Xu, R. Gan, B. Fitt, B. D. L. Univ Hertfordshire Sch Life & Med Sci Hatfield AL10 9AB Herts England Chongqing Normal Univ Elementary Educ Coll Chongqing Peoples R China Rothamsted Res Harpenden Herts England Southwest Univ Chongqing Peoples R China Univ London Imperial Coll Sci Technol & Med Sch Publ Hlth London SW7 2AZ England Hadley Ctr Met Off Exeter Devon England Hubei Plant Protect Stn Wuhan Peoples R China Anhui Acad Agr Sci Crop Res Inst Hefei Peoples R China

To estimate potential impact of climate change on wheat fusarium ear blight (FEB), simulated weather for the A1B climate change scenario was input into a model for estimating FEB in central China. In this article, a logistic weather-based regression model for estimating incidence of wheat FEB in central China was developed, using up to 10 years (2001-2010) of disease, anthesis date and weather data available for 10 locations in Anhui and Hubei provinces. In the model, the weather variables were defined with respect to the anthesis date for each location in each year. The model suggested that incidence of FEB is related to number of days of rainfall in a 30-day period after anthesis and that high temperatures before anthesis increase the incidence of disease. Validation was done to test whether this relationship was satisfied for another five locations in Anhui province with FEB data for 4-5 years but no nearby weather data, using simulated weather data obtained employing the regional climate modelling system PRECIS. How climate change may affect wheat anthesis date and FEB in central China was investigated for period 2020-2050 using wheat growth model Sirius and climate data simulated using PRECIS. The projection suggested that wheat anthesis dates will generally be earlier and FEB incidence will increase substantially for most locations.

关键词： food security wheat fusarium ear blight weather-based disease forecasting logistic regression model Climate change impacts sustainable agriculture

来源：评论

学校读者我要写书评

暂无评论

Differentially private distributed logistic regression using private and public data

引用

BMC MEDICAL GENOMICS 2014年第1-Sup期7卷 1-10页

作者： Ji, Zhanglong Jiang, Xiaoqian Wang, Shuang Xiong, Li Ohno-Machado, Lucila Univ Calif San Diego Div Biomed Informat La Jolla CA 92093 USA Emory Univ Dept Math & Comp Sci Atlanta GA 30322 USA

Background: Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e. g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. Methodology: In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. Experiments and results: We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Conclusion: logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee.

关键词： logistic regression model Newton Method Public Data Hessian Matrix Differential Privacy

来源：评论

学校读者我要写书评

暂无评论

Fatigue and crashes: The case of freight transport in Colombia

引用

ACCIDENT ANALYSIS AND PREVENTION 2014年 72卷 440-448页

作者： Torregroza-Vargas, Nathaly M. Pablo Bocarejo, Juan Ramos-Bonilla, Juan P. Univ Los Andes Urban & Reg Sustainabil Grp Bogota Colombia Univ Los Andes Dept Civil & Environm Engn Bogota Colombia

Truck drivers have been involved in a significant number of road fatalities in Colombia. To identify variables that could be associated with crashes in which truck drivers are involved, a logistic regression model was constructed. The model had as the response variable a dichotomous variable that included the presence or absence of a crash during a specific trip. As independent variables the model included information regarding a driver's work shift, with variables that could be associated with driver's fatigue. The model also included potential confounders related with road conditions. With the model, it was possible to determine the odds ratio of a crash in relation to several variables, adjusting for confounding. To collect the information about the trips included in the model, a survey among truck drivers was conducted. The results suggest strong associations between crashes (i.e., some of them statistically significant) with the number of stops made during the trip, and the average time of each stop. Survey analysis allowed us to identify the practices that contribute to generating fatigue and unhealthy conditions on the road among professional drivers. A review of national regulations confirmed the lack of legislation on this topic. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Truck drivers Road safety Fatigue logistic regression model modelling data analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：