Adaptive flexibility and maladaptive routines in selecting fast and frugal decision strategies.

Decision routines unburden the cognitive capacity of the decision maker. In changing environments, however, routines may become maladaptive. In 2 experiments with a hypothetical stock market game (n = 241), the authors tested whether decision routines tend to persist at the level of decision strategies rather than at the level of options in strategy selection. The payoff structure of the task was changed after 80 decision trials, rendering a new strategy optimal with respect to expected payoff. Whereas most participants detected the appropriate strategy at the beginning of the task, they tended to retain it even when it was no longer optimal. A hint about a possible change had only a small influence on this maladaptive routine; a monetary incentive had none. Switching to a similar but not identical task relaxed the routine, but not much. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

利用模糊评判方法确定张东构造油藏储量计算的可靠程度

张巨河油田张东构造地处大港滩海交接处,海域部分探井少.目前用油藏描述方法计算的探明储量,其落实程度备受关注.储量落实程度的评价是一个多因素综合评判问题,而且这些因素还分属不同层次.模糊综合评判是应用较为广泛的模糊数学方法之一.该方法建立的综合评判涉及三个要素,即因素集、评判集和单因素评判,由此所构造的模糊评判关系是模糊综合评判的基础.本文用该方法对张东构造沙二段油藏的探明储量落实程度作了尝试性评价.     

堆底熔穿事故的场外后果及其对策

在压水堆核电站应急计划和应急响应中，堆底熔穿事故占有重要位置。本文用法国核电厂事故源项Ｓ３（对应于堆底熔穿事故）计算了在典型气象条件下的场外放射学的后果，根据一般防护决策原则和我国颁布的干预水平，提出了保护公众的应急防护措施的建议。     

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Sql Server BI平台和决策树技术的CET-4成绩分析

文章首先对Sql Server 2008商业智能平台及决策树技术相关理论作了介绍,然后对挖掘数据源数据进行了一系列预处理。利用Sql Server 2008商业智能平台下的决策树技术并采用数据挖掘扩展语言即DMX语言创建了CET-4成绩分析决策树模型。分类矩阵和挖掘提升图分别对该模型的评估结果表明了模型具有较高的可靠性和分类准确度,同时模型对应的一些规则可作为英语教学管理和改革的重要参考依据。     

基于加权决策树的蛋白质序列分类算法研究

针对蛋白质序列分类的需求,深入研究了蛋白质序列分类算法。对蛋白质序列的特征属性进行了大量的分析和研究,给出了蛋白质序列特征属性的描述形式。在此基础上设计了一种基于加权决策树的蛋白质序列分类算法,详细阐述了加权决策树的构造过程以及决策树的主要参数计算方法,而且根据蛋白质序列的特征,对决策树进行了改进,给出了加权决策树的实现方法。测试结果表明：设计的蛋白质序列分类算法具有较高的分类精度和较快的执行速度。     

MULTICRITERIA SORTING METHODOLOGY: APPLICATION TO FINANCIAL DECISION PROBLEMS

Abstract

The primary objective in the sorting approach is to assign a set of alternatives into predefined classes. This type of problem is often encountered in many real world decision problems. During the last two decades several new approaches have been proposed to overcome the shortcomings of traditional statistical and econometric techniques. This paper focuses on the multicriteria decision aid (MCDA) approach; it briefly reviews the main MCDA sorting techniques, and presents the multigroup hierarchical discrimination method. This new MCDA sorting technique is applied to the portfolio selection problem. A comparison with discriminant analysis is also performed. Furthermore, the efficiency of the proposal approach can be easily improved for solving large-scale problems in a multiprocessing environment.     

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.     

数据挖掘技术在学校管理中的应用

数据挖掘技术是一门多学科相互交叉融合而形成的新兴学科。目前,该技术已在商业、金融业、农业、互联网、医药业等多个领域中得到广泛应用。而将数据挖掘技术与学校管理相结合,可以从大量事务管理数据中提取出了隐藏在其中的有用信息,因此可以帮助教学人员合理安排教学工作,协助辅导员对学生的管理,从而促进教育体制的进一步完善与发展。本文由数据挖掘技术概述入手,论述了数据挖掘技术在学校管理中的作用,最后,将数据挖掘技术应用在学生成绩管理中,可以实现透过现象看本质,提炼有价值的信息。     

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。