第19届世界杯足球赛决赛阶段进球得分类型变化特征的研究

采用录像观察法对第19届世界杯足球赛决赛阶段进球得分情况进行观察统计,对进球得分情况进行分类,分析现代竞技足球高水平赛事进球得分类型的特征,探讨足球比赛得分类型变化发展的内在规律,为各级足球教练员组织训练比赛提供科学的理论指导。     

一种基于属性加权综合直觉梯形模糊数多属性决策方法

在解决属性值为直觉模糊数的多属性决策问题中,其权重信息未知.先采用熵值法来求其权重,并用直觉梯形模糊数权重平均算子求出各指标的平均属性值,给出了直觉梯形模糊数得分函数公式,期望函数公式.并提出了解决此类问题的方法与步骤,根据得分函数值大小进行排序,选择出最优方案.通过一个实例对此方法进行验证.     

Mixture cure models in credit scoring: If and when borrowers default

Mixture cure models were originally proposed in medical statistics to model long-term survival of cancer patients in terms of two distinct subpopulations - those that are cured of the event of interest and will never relapse, along with those that are uncured and are susceptible to the event. In the present paper, we introduce mixture cure models to the area of credit scoring, where, similarly to the medical setting, a large proportion of the dataset may not experience the event of interest during the loan term, i.e. default. We estimate a mixture cure model predicting (time to) default on a UK personal loan portfolio, and compare its performance to the Cox proportional hazards method and standard logistic regression. Results for credit scoring at an account level and prediction of the number of defaults at a portfolio level are presented; model performance is evaluated through cross validation on discrimination and calibration measures. Discrimination performance for all three approaches was found to be high and competitive. Calibration performance for the survival approaches was found to be superior to logistic regression for intermediate time intervals and useful for fixed 12 month time horizon estimates, reinforcing the flexibility of survival analysis as both a risk ranking tool and for providing robust estimates of probability of default over time. Furthermore, the mixture cure model’s ability to distinguish between two subpopulations can offer additional insights by estimating the parameters that determine susceptibility to default in addition to parameters that influence time to default of a borrower.     

A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism

Structure-based virtual screening techniques require reliable scoring functions to discriminate potential substrates effectively. In this study we compared the performance of GOLD, PMF, DOCK and FlexX scoring functions in FlexX flexible docking to cytochrome P450cam binding site. Crystal structures of protein-substrate complexes were most effectively reproduced by the FlexX/PMF method. On the other hand, the FlexX/GOLD approach provided the best correlation between experimental binding constants and predicted scores. Binding modes selected by the FlexX/PMF approach were rescored by GOLD to obtain a reliable measure of binding energetics. The effectiveness of the FlexX/PMF/GOLD method was demonstrated by the correct classification of 32 out of the 33 experimentally studied compounds and also in a virtual HTS test on a library of 10,000 compounds. Although almost all the available functions were developed to be general, our study on cytochrome P450cam substrates suggests that careful selection or even tailoring the scoring function might increase the prediction power of virtual screens significantly. The FlexX/PMF/GOLD methodology was tested on cytochrome P450 3A4 substrates and inhibitors. This preliminary study revealed that the combined function was able to recognise 334 out of the 345 compounds bound to 3A4.     

第12届欧洲足球锦标赛进球特征分析

运用文献资料法、观察法、数理统计法等研究方法,以第12届欧洲足球锦标赛的31场比赛为研究对象,对所有比赛中射门和进球的情况进行统计.通过对射门的效率、进球区域、进球方式、进球时间和进球队员位置进行分析,来探寻欧洲足球的进球规律,为我国足球教练员在以后的训练中提供理论依据.结果发现:中路2区是射门得分的最佳区域,传切配合是得分的主要手段.远射是破门的有效手段.头球破门、左右脚得分和定位球得分的能力很重要.教练员的换人对比赛有一定的影响.     

Reverse fingerprinting, similarity searching by group fusion and fingerprint bit importance

Summary Recent research has shown that using data fusion rules in fingerprint-based similarity searching can improve results over traditional searches. Group fusion scores, which use multiple reference compounds, have in particular been shown to be quite effective in increasing enrichment rates over single reference structure based searches. In this paper, the effectiveness of using data fusion with multiple reference compounds to increase similarity search recall rates was investigated using 44 biological targets and four different 2D fingerprinting systems, including a new 2D typed triangle fingerprinting system introduced here. Scaffold-hopping abilities using data fusion rules were investigated using eight (8) different classes of scaffolds active against cGMP phosphodiesterase isoform 5 (PDE5). An approach to using the reference group for ranking and visualizing important fingerprints bits, or reverse fingerprinting, was presented, and used to score and visualize important pharmacophore features within sample active molecules. Finally, similarity statistics within the reference groups were investigated and compared to recall rates.     

蛋白质拓扑结构Alignment与相似性打分的算法

蛋白质结构分类是当今“后基因组”研究的热点 ,是探索蛋白质折叠 /功能关系的有效方法 .创立一种新型的分类体系就意味着对复杂的蛋白质结构的有了进一步的理解 .本文基于蛋白质结构域的拓扑结构 ,将拓扑量化 ,以Alignment矩阵方法对结构域进行比较 ,并按拓扑结构相似性对任意 2个蛋白质进行打分 .上述算法已经实现了程序化 .依此算法可将一组蛋白质进行新的分类 ,并可望将结构分类与生物功能的关系进行分析 .     

多层感知器信用评价模型研究

建立多层感知器(MLP)神经网络信用评价模型，用来对我国2000年96家上市公司进行信用评级。按照各上市公司的经营状况分为“好”、“中”、“差”三类，每一类由32家上市公司构成数据样本。对于每一家上市公司，主要考虑其经营状况的四个主要财务指标：每股收益，每股净资产，净资产收益率和每股现金流量，所有数据都来自于2000年上市公司年报。对于MLP网络结构，隐层结点的个数是采用试验的方法来确定的。先从1个开始，然后逐个逐个地增加，一直增加到不能再改善网络性能为止。仿真结果表明，多层感知器信用评价模型分类的准确率达到79．17％。此外，还详细给出MLP网络模型的学习算法和步骤。     

The Advantage of Case-Tailored Information Metrics for the Development of Predictive Models,Calculated Profit in Credit Scoring

This paper compares model development strategies based on different performance metrics. The study was conducted in the area of credit risk modeling with the usage of diverse metrics, including general-purpose Area Under the ROC curve (AUC), problem-dedicated Expected Maximum Profit (EMP) and the novel case-tailored Calculated Profit (CP). The metrics were used to optimize competitive credit risk scoring models based on two predictive algorithms that are widely used in the financial industry: Logistic Regression and extreme gradient boosting machine (XGBoost). A dataset provided by the American Fannie Mae agency was utilized to conduct the study. In addition to the baseline study, the paper also includes a stability analysis. In each case examined the proposed CP metric that allowed us to achieve the most profitable loan portfolio.     

Measuring retail company performance using credit scoring techniques

This paper discusses models for evaluating credit risk in relation to the retailing industry. Hunt’s [Hunt, S.D., 2000. A General Theory of Competition. Sage Publications Inc., California] Resource–Advantage Theory of Competition is used as a basis for variable selection, given the theory’s relevancy to retail competition. The study focuses on the US retail market. Four standard credit scoring methodologies: Naïve Bayes, Logistic Regression, Recursive Partitioning and Artificial Neural Network, are compared with Sequential Minimal Optimization (SMO), using a sample of 195 healthy companies and 51 distressed firms over five time periods from 1994 to 2002.