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Search Results: 1 - 10 of 16624 matches for " 王国长 "
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信用卡违约预测模型分析以及影响因素探究
Study on Analysis and Influence Factors of Credit Card Default Prediction Model
 [PDF]

梅瑞婷, 徐扬, 王国
Statistics and Applications (SA) , 2016, DOI: 10.12677/SA.2016.53026
Abstract: 信用卡对于银行来说是高收益和高风险并存的业务,伴随信用卡业务发展的是各大银行都在利用网络和移动端的数据来建立客户的信用评分系统。如何从客户所填的资料里对客户进行信用评估、如何鉴别所填资料的真假性及应该要求客户填什么类型的资料等对银行来说是至关重要的。本文基于2005年台湾信用卡客户数据,建立Lasso-Logistic及随机森林模型来探索影响客户信用的关键因素,包括个体特征及某些客观特征,通过比较模型的预测准确度以及F得分等指标来选择预测效果更优的模型对银行信用卡违约进行预测分析。信用卡违约预测模型的建立以及影响客户信用的关键因素的探索,对于银行选择客户和设计资料填写具有重要的指导价值,并且能够为信贷决策提供一定的理论支持,具有很强的理论和现实意义。
Credit cards are a bank business in which high income and heavy risk coexist. Along with the de-velopment of the credit card business, banks are using the Internet and mobile data to establish customer credit rating system. How to evaluate customer credit from the information that cus-tomers fill in, and how to identify the information true or false, and what type of information that customers are asked to fill are crucial for banks. Based on the credit card customer data of 2005 in Taiwan, this article established Lasso-Logistic model and random forest model to explore the key factors which effect customer credit, including individual characteristics and some objective cha-racteristics. Through comparing the prediction accuracy of the model and F score index, we selected the model of better prediction effect to forecast the bank credit card defaults. The establishment of the credit card default prediction model and the exploration of the key factors influencing the customer credit not only have a important guidance value for banks to choose customers and design data, but also can provide certain theoretical support for the credit decisions. In addition, it has a strong theoretical and practical significance.
基于LASSO-SVM模型的银行定期存款电话营销预测
Telephone Marketing Forecast of Bank Time Deposits Based on the LASSO-SVM Model
 [PDF]

梅瑞婷, 徐扬, 王国
Statistics and Applications (SA) , 2016, DOI: 10.12677/SA.2016.53029
Abstract: 定期存款一直以来都是银行的主要资金来源,而电话营销也成为一种低成本,广受银行欢迎的营销模式。因此,如何提高电话营销成功率成为银行急需解决的重要问题。其中,影响客户订购定期存款的因素复杂多样,而这些因素之间可能存在多重共线性,如果银行不加选择地引入众多影响因素来进行订购定期存款的预测,往往不能取得良好的预测效果,甚至产生错误的决策。在统计学习方法中,LASSO方法可以同时进行参数估计和变量选择,所以本文提出了基于LASSO与支持向量机的组合预测方法。同时,与SVM、神经网络、LASSO-神经网络方法的预测效果进行比较,验证了LASSO-支持向量机组合预测方法的拟合预测效果要优于另外三种预测方法。
Time deposits have always been the main source of funds for the bank, and the telephone mar-keting has become a low-cost marketing model, which is widely popular with the bank. Therefore, how to improve the success rate of telemarketing has become an important problem to solve. Among them, the factors that affect customers ordering deposits are complicated, which may have multicollinearity. If banks indiscriminately use many influence factors to predict deposits, they often cannot obtain good prediction effects, and even make the wrong decision. In the statistical learning methods, the LASSO method can be used to estimate parameters and select variables, so this paper presents a combination forecast method based on the LASSO and Support Vector Ma-chine (SVM). At the same time, compared with SVM, neural network, LASSO-neural network me-thods, we find that the effect of LASSO-SVM forecasting method is better than the other three kinds of forecasting methods.?
广州市财政收入分析及预测模型
Analysis and Prediction Model of Financial Income in Guangzhou
 [PDF]

陈庚, 卢丹丹, 万浩文, 王国
Statistics and Applications (SA) , 2015, DOI: 10.12677/SA.2015.43021
Abstract: 地方财政收入是国家财政收入的重要组成部分。利用1994~2013年广州市的财政收入相关数据,建立Adaptive-Lasso变量选择模型,并自动识别出广州市财政收入的关键影响因素。并且在变量选择的基础上,又构建了灰色预测与BP神经网络的组合模型来预测广州市2014、2015年的财政收入。模型分析结果表明,社会从业人数、在岗职工工资总额、社会消费品零售总额、城镇居民人均可支配收入、城镇居民人均消费性支出以及全社会固定资产投资额与财政收入的关联性较大,之后进行的组合模型预测也有较好的效果。最后,根据分析结果提出相关的政策性建议。
Local financial revenue is an important part of national fiscal revenues. In order to identify the impact affecting factors of Guangzhou’s fiscal revenue automatically, we established a variable se-lection model in Adaptive-Lasso based on 1994-2013 years’ economic data. Under the research above, the paper offered the predictive value of fiscal revenue from 2014 to 2015 based on grey prediction and BP neural network combined model. The results of the variable selection models showed that the social number of employees, the total of worker’s salary, total volume of retail sales of the social consumer goods, per capita disposable income in urban residents, per capita expenditure on consumption in urban residents and social fixed assets investment were more re-lated to fiscal revenue; afterwards the combined model had better effects. Furthermore, some ad-vices were presented.
茄二十八星瓢虫为害对不同基因型番茄叶内三种抗性酶活性的影响
王国,曹彬,,戈峰
应用昆虫学报 , 2015,
Abstract: 【目的】研究茉莉酸合成相关基因在番茄抗茄二十八星瓢虫henosepilachnavigintioctopunctatafabricius中的作用,探讨茉莉酸信号因子在植物防御过程中起到的作用。【方法】利用3种基因型番茄茉莉酸合成缺失突变体spr2、茉莉酸合成过量表达体35s、野生型番茄wt为材料,通过经2龄茄二十八星瓢虫分别取食6、24、48h后,利用分光光度计测定3种基因型番茄叶片内苯丙氨酸解氨酶(phenylalanineammonialyase,pal)、胰蛋白酶抑制剂(proteaseinhibitors,pi)和脂氧合酶(lipoxygenase,lox)酶活性的动态变化。【结果】35s型番茄叶片内pi活性显著高于另两种番茄叶片,而spr2型番茄叶片pi活性最低。瓢虫为害后,3种基因型番茄pi酶活性明显提高,在35s和wt型番茄中,pi和lox酶活性在胁迫24h和6h达到最高值,而spr2型番茄没有显著变化。受到瓢虫侵染的系统叶中,pi和lox酶活性也受到了诱导,系统叶变化趋势同危害叶相同,但诱导的pi和lox酶活性明显低于危害叶。在危害处理过程中,均呈现上升-下降的趋势,在系统叶中,则pal活性没有显著变化。番茄叶片受害后,pi和lox酶活性上升辐度大于pal,说明pi和lox对取食胁迫响应比pal更敏感。【结论】35s茉莉酸合成过量表达体的番茄对茄二十八星瓢虫有一定的抗虫作用,因此,茉莉酸在植物抗性中起了一定作用。
气候变化对黄河水资源的影响
王国,王云璋,
人民黄河 , 2000,
Abstract: ?首先简要介绍了黄河月水文模型,然后在分析气温变化对黄河流域蒸发能力影响的基础上,采取假定气候方案,分析了黄河主要产流区径流对气候变化的敏感性,最后根据全球气候模型gcms输出的降水、气温结果,估算了温室效应对主要产流区水资源的影响,并进一步分析得出:黄河未来几十年径流量呈减少趋势,汛期径流和年径流约分别减少25.4和35.7亿m3,其中兰州以上减少最多,占总减少量的一半以上.
用SAS MACRO程序建立多项式模型与变量筛选
Using SAS MACRO Programs to Build a Polynomial Model and Do the Selection of Variables
 [PDF]

王国
Advances in Applied Mathematics (AAM) , 2015, DOI: 10.12677/AAM.2015.42021
Abstract:
本篇论文是希望藉助SAS MACRO程序,提出一个能解决建立多项式模型上的困恼。多项式模型在统计分析上一直是被忽略的,这可以很清楚的知道因为在所有的统计分析的出版品中很难找到以多项式回归为主提的例子。这原因无非是无法解决大量变量的模型建立与分析。举例来说要建立一个完整的5个变量的3次多项式总共需要55个变量,而如果变量增加到18个,那建立1个2次多项式就高达189个变量,因此在实用分析上是鲜有这样的例子。本篇论文就是希望能提出1个解决模型建立与初步分析的方法,读者可以藉由在第三章的例子的输出报表中很清楚去比较各个模型的优劣点,这就是为何统计分析需要工具去产生整合型的报表。欠缺这些报表,要去判定模型的好坏(基于预测值的准确度)是很困难的工作。而我之所以强调要用多项式的模型去分析数据有下列几点原因;1) 如果模型为平滑曲面则多项式模型可以提供一个可接受的模型。这可以很容易由泰勒定理得到验证;2) 只要观测值够多,大部分模型的不配合均可以用高阶多项式模型解决;3) 可以避免因为经过模型筛选而删除掉可能是有用的变量。那是因为模型会产生很多的交叉相乘项,既使用模型筛选的程序也很难将一个变量完全去除掉,因此可以保存几乎所有的变量,而因此将不失模型的完整性。本篇论文提供了两支主要的SAS MACRO程序;%Homopoly和%Model_Selection分别会在下个两章节中介绍。程序%Homopoly是用在建立多项式数据文件,而%Model_Selection则是用来提供SAS模型筛选后的总结数据,报表格式是仿照表11.8 Montgomery制作的。读者可以很容易复制到其他的分析。为了要编写程序,我同时提供了20支工具程序,读者可以至以下的网站下载http://tsp.ec.tku.edu.tw/QuickPlace/054569qp/Main.nsf/h_Toc/BADD7D0BFF0 904A1482576D300229684/?OpenDocument。请依循档案README.TXT中的指示去安装即可。
The purpose of this paper is trying to provide a useful solution to build a polynomial model. In the past years, there are a few applications on polynomial model; the reason is that it is difficult to create a large number of variables. For example, if you want to build a 3rd order polynomial with 5 variables, then you need 55 variables. If the variables increase to 18, then a 2nd order polynomial model will need 189 variables. It is far away from our ability. That is the reason why I wrote the following programs. There are 3 major reasons that I would like to deal with the polynomial model: 1) if the unknown model was smooth plan curve, then a polynomial model can provide an acceptable approximation. This can be easily seen from the Taylor’s polynomial; 2) as long as we have enough observations, then using a high order polynomial model can solve the unfitted problems; 3) it can avoid deleting important variables from the selection steps, since it is not easy to remove a variable completely from the model because there are too many cross product terms shown in the model. This paper will provide 2 major SAS MACRO programs, %Homopoly and %Model_Selection. The first program is used to generate a polynomial model and the next one will provide summarized result tables similar to the Table 11.8 of Montgomery including the information of the models and necessary statistics. Users can easily apply to do the further analysis. To write those programs, I also wrote another 20 SAS MACRO programs which can be downloaded from the web-site http://tsp.ec.tku.edu.tw/QuickPlace/054569qp/Main.
一个含端粒序列的水稻BAC克隆的分析和定位
翟文学,陈浩,颜辉煌,,王国,朱立
中国科学 生命科学 , 1999,
Abstract: 对一个含(TTTAGGG)n同源序列的水稻BAC克隆(BAC2)进行了分析,揭示出水稻近端区DNA的组成.BAC2的插入片段中除含有大量的以串联形式存在的称之为TA352序列的卫星DNA外,还含有TTTAGGG或其变体组成的简单重复.荧光原位杂交(FISH)将含(TTTAGGG)n序列的0.8kbPstⅠ片段定位在至少5对染色体的端粒区.通过对BAC2中低拷贝序列的RFLP分析,BAC2被定位在水稻第6号染色体端部.这些结果说明水稻的端粒序列可能也是TTTAGGG或其变体构成的简单重复,而与其相连的卫星DNATA352则属于端粒相关序列.
多源地学信息数字图像综合技术及在盛源盆地的应用研究
刘德,邹景轲,孙茂荣,王国
国土资源遥感 , 1989, DOI: 10.6046/gtzyyg.1989.02.05
Abstract: 通过图像显示系统,实现了铀资源多种地学信息数字图像的综合处理,其内容包括资料的输入处理、资料配准和插值处理以及多源地学信息的增强、分解、提取、分类、叠合、复合等处理。以盛源盆地为样区进行了试验性研究。利用图像的信息增强、叠合技术,研究了试验区的地质构造环境;利用图像信息的分解、叠合技术,分析了铀、针、钾的分布格局及其地质意义;通过矿床找矿判据的复合、提取,进行了找矿靶区的初选;来用信息的分类技术,进行了盛源盆地地区铀资源的总体评价。通过上述计算机信息处理技术,对这个研究程度较高的老矿区,在某些重要地质问题上,取得了一些新认识,并经野外检验,预测了六片成矿远景地段。在上述研究基础上,初步建立了铀资源多种地学信息数字图像综合技术系统。
常量喷布植物乳油对大田害虫杀虫活性类型分析
刘浩官,陈松恩,王国,陈一安,林丛,王乾超
昆虫学报 , 1986,
Abstract:
苏北沿海土地利用变化对土壤易氧化碳含量的影响
王国,赵小龙,王明慧,阮宏华**,,徐亚明
应用生态学报 , 2013,
Abstract: 土壤易氧化碳(readilyoxidizablecarbon,roc)作为指示土壤有机碳(soc)早期变化的敏感指标,对研究人类干扰及全球变化背景下的土壤有机碳库稳定性及其动态具有重要的指示意义.为深入了解土地利用变化对土壤易氧化碳含量的影响,本文对苏北沿海地区草地、农田、杨-农复合经营及杨树纯林4种不同土地利用方式的土壤roc含量及其相关因子进行了测定.结果表明:苏北沿海地区不同土地利用类型的roc含量表现为草地<农田<杨-农复合系统<杨树林,不同土地利用方式间roc含量在0~10cm土层差异最为显著;roc及roc/soc随着土层深度的增加而递减,且不同土层之间差异显著;4种土地利用方式roc的季节变化趋势一致,其值均为夏季最大,冬季次之,春季最小;roc与土壤ph值、土壤容重呈极显著负相关,与soc、土壤水溶性有机碳(wsoc)、全n、土壤c/n、mg呈显著或极显著正相关,而与土壤湿度、全p的相关性不显著.土地利用方式的变化显著影响了土壤易氧化碳的空间分布特征,土壤容重、ph值、全n和soc是roc在不同土地利用方式间产生差异的主要-原因.
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