用面向对象编程实现问题求解自动化

本文从面向对象方法基本原理和面向对象编程的技术特征出发，阐明所建应用软件系统中的对象，类及相应类层次结构和类组合结构，使系统具有很强的表现真空世界复杂系统结构的能力，系统通过消息传递在程序执行中实现对操作的调用机制，使之在面向用户问题选择和执行求解策略方面有很强的适应性，这一点对于强调人－机交互和解题协作的智能决策支持系统设计至关重要，文章给出了用Ｃ＋＋实现的模型对象系统及消息传递机制。     

基于JavaScript实现随机数的分组抽取

通过一个随机数的分组抽取小实例,对JavaScript脚本语言做了简要说明,对初学者入门深有裨益。     

Transit smart card data mining for passenger origin information extraction

The automated fare collection(AFC) system,also known as the transit smart card(SC) system,has gained more and more popularity among transit agencies worldwide.Compared with the conventional manual fare collection system,an AFC system has its inherent advantages in low labor cost and high efficiency for fare collection and transaction data archival.Although it is possible to collect highly valuable data from transit SC transactions,substantial efforts and methodologies are needed for extracting such data because most AFC systems are not initially designed for data collection.This is true especially for the Beijing AFC system,where a passenger’s boarding stop(origin) on a flat-rate bus is not recorded on the check-in scan.To extract passengers’ origin data from recorded SC transaction information,a Markov chain based Bayesian decision tree algorithm is developed in this study.Using the time invariance property of the Markov chain,the algorithm is further optimized and simplified to have a linear computational complexity.This algorithm is verified with transit vehicles equipped with global positioning system(GPS) data loggers.Our verification results demonstrated that the proposed algorithm is effective in extracting transit passengers’ origin information from SC transactions with a relatively high accuracy.Such transit origin data are highly valuable for transit system planning and route optimization.     

一种基于光照变化补偿的颜色识别方法

针对RoboCup中型组足球机器人比赛中光照变化会使颜色发生色彩漂移,影响颜色识别的准确性问题,提出一种基于光照变化补偿的颜色识别方法。该方法首先利用球的历史信息预测球的位置,然后在较小的区域内用基于色调直方图反向投影的方法找到球后,通过球的亮度直方图的变化计算出光照变化率,用于动态补偿颜色查找表。实验表明该方法能提高颜色识别的光照自适应性。     

船舶抗沉辅助决策系统的研究与设计

抗沉辅助决策系统是船舶常规和紧急状态下进行损管行动的关键性依据。目前抗沉计算分析系统,可对船舶基础状态、浮稳性等信息进行管理,并进行仿真和辅助决策,但大多存在算法效率低,决策生成速度和精度不足、人机交互接口脱离实际等问题。本文从船舶抗沉操作的实际执行过程出发,制定抗沉算法,根据实时装载和破损情况,对液舱采用注入水或排水的损管操作,生成调整措施,使船舶恢复良好的浮态与稳性。系统基于面向对象过程控制平台设计和实现,仿真结果验证了系统的有效性和高效性。     

世界杯小组赛出线预测程序

每届足球世界杯都会受到无数人的关注,媒体和个人都很热衷比赛结果的预测。该程序根据世界杯比赛胜负出线规则对比赛结果进行预测。     

Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.     

基于SPOT-5多光谱影像的矿区塌塘水体提取方法研究

针对基于遥感影像的水体提取方法存在水体提取不完整和误提的现象,提出了一种基于SPOT-5多光谱影像的矿区塌塘水体提取方法。在利用波段合成增加一个可用波段的基础上对已有的水体提取方法进行适当的改进,并基于决策树分类器和改进后的方法进行矿区水体的四级提取,保证了水体提取的完整性,同时减少了误提率;最后利用实测数据对水体提取的精度进行了评定。试验结果表明,基于决策树分类器的水体提取方法具有较高的精度,能满足矿区实际应用的需要。     

Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment

We study the group decision making problem under intuitionistic fuzzy environment. Based on entropy and cross entropy, we give two methods to determine the optimal weights of attributes, and develop two pairs of entropy and cross entropy measures for intuitionistic fuzzy values. Then, we discuss the properties of these measures and the relations between them and the existing ones. Furthermore, we introduce three new aggregation operators, which treat the membership and non-membership information fairly, to aggregate intuitionistic fuzzy information. Finally, several practical examples are presented to illustrate the developed methods.