On Intelligent Systems of the Data Acquisition in the Schedule Risk Analysis

It is an important task to analyze the schedule risk in a project management.As a semi-constructed or non-constructed complex system, there are many difficulties in the quantitative analysis of the schedule risk (SRA). The paper integrates intelligent techniques to obtain massive basic data required in the risk analysis process. It greatly improves the precision and efficiency of the SRA. In addition, the paper presents a mechanism and architecture of the integrated intelligent systems. Finally, the concluding remarks are provided for basic data acquisition in the SRA.     

Managing construction risks of AP1000 nuclear power plants in China

Large and complex construction projects face risk from various sources and the successful completion of such projects depends on effective risk management.This study investigates the risk faced by Chinese firms participating in constructing AP1000 nuclear power plants in China.AP1000 nuclear reactors are new,Generation III+ reactors designed by Westinghouse and to be built first in China.The semi-structured interview approach is used to elicit information from experts involved in the AP1000 projects in China.Based on the interviews,various sources of risk are identified.In addition to general risks that megaprojects normally face,there are unique risks that arise from various sources such as technological,political,organizational,and individual personnel risks.Risk management strategies are proposed to manage general and unique risks identified in the study.The findings of this study would be helpful for Chinese companies involved in the construction of AP1000 nuclear power plants to mitigate the risks associated with the projects.     

New data association technique based on ACO with directional information considered

Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.     

PLATFORM SELECTION FOR COMPLEX SYSTEMS:BUILDING AUTOMATION SYSTEMS

Automation systems for buildings interconnect components and technologies from the information technology industry and the telecommunications industry.In these industries,existing platforms and new platforms（that are designed to make building automation systems work） compete for market acceptance and consequently several platform battles among suppliers for building automation networking are being waged.It is unclear what the outcome of these battles will be and also which factors are important in achieving platform dominance.Taking the fuzziness of decision makers＇ judgments into account,a fuzzy multi-criteria decision-making methodology called the Fuzzy Analytic Hierarchy Process is applied to investigate the importance of such factors in platform battles for building automation networking.We present the relative importance of the factors for three types of platforms（subsystem platforms,system platforms,and evolved subsystem platforms）.The results provide a first indication that the set of important factors differs per type of platform.For example,when focusing on other stakeholders,for subsystem platforms,the previous installed base is of importance;for system platforms,the diversity of the network of stakeholders is essential;and for evolved subsystem platforms,the judiciary is an important factor.     

Project management: Recent developments and research opportunities

This paper studies the business process known as project management. This process has exhibited a remarkable growth in business interest over the last 15 years, as demonstrated by a 1000% increase in membership in the Project Management Institute since 1996. This growth is largely attributable to the emergence of many new diverse business applications that can be successfully managed as projects. The new applications for project management include IT implementations, research and development, new product and service development, corporate change management, and software development. The characteristics of modern projects are typically very different from those of traditional projects such as construction and engineering, which necessitates the development of new project management techniques. We discuss these recent practical developments. The history of project management methodology is reviewed, from CPM and PERT to the influential modern directions of critical chain project management and agile methods. We identify one important application area for future methodological change as new product and service development. A list of specific research topics within project management is discussed. The conclusions suggest the existence of significant research opportunities within project management.     

Using an Adaptive Genetic Algorithm to Improve Finance Decision

Optimising both qualitative and quantitative factors is a key challenge in solving construction finance decisions. The semi-structured nature of construction finance optimisation problems precludes conventional optimisation techniques. With a desire to improve the performance of the canonical genetic algorithm (CCA) which is characterised by static crossover and mutation probability, and to provide contractors with a profit-risk trade-off curve and cash flow prediction, an adaptive genetic algorithm (AGA) model is developed. Ten projects being undertaken by a major construction firm in Hong Kong were used as case studies to evaluate the performance of the genetic algorithm (CA). The results of case study reveal that the ACA outperformed the CGA both in terms of its quality of solutions and the computational time required for a certain level of accuracy. The results also indicate that there is a potential for using the GA for modelling financial decisions should both quantitative and qualitative factors be optimised simultaneously.     

Contractor Prequalification Based on Neural Networks

Contractor Prequalification involves the screening of contractors by a project owner, according to a given set of criteria, in order to determine their competence to perform the work if awarded the construction contract. This paper introduces the capabilities of neural networks in solving problems related to contractor prequalification. The neural network systems for contractor prequalification has an input vector of 8 components and an output vector of 1 component. The output vector represents whether a contractor is qualified or not qualified to submit a bid on a project.     

Two Improved Digital Signature Schemes

1. INTRODUCTIONWith the rapid development of information technologyl the security and secrecy of computer network systemare becoming more and more important. Therefore, in order to guaratee the security of the network systemand data information, we must study new type of cipher and encryption technology. This is one of the mosteffective ways to guaratee that the system can be run dependably. Only if the data is encrusted, the integrityof the information content in communication links is a…     

Analysis of effect factors-based stochastic network planning model

Looking at all the indeterminate factors as a whole and regarding activity durations as independent random variables, the traditional stochastic network planning models ignore the inevitable relationship and dependence among activity durations when more than one activity is possibly affected by the same indeterminate factors. On this basis of analysis of indeterminate effect factors of durations, the effect factors-based stochastic network planning （EFBSNP） model is proposed, which emphasizes on the effects of not only logistic and organizational relationships, but also the dependent relationships, due to indeterminate factors among activity durations on the project period. By virtue of indeterminate factor analysis the model extracts and describes the quantitatively indeterminate effect factors, and then takes into account the indeterminate factors effect schedule by using the Monte Carlo simulation technique. The method is flexible enough to deal with effect factors and is coincident with practice. A software has been developed to simplify the model-based calculation, in VisualStudio.NET language. Finally, a case study is included to demonstrate the applicability of the proposed model and comparison is made with some advantages over the existing models.     

Optimal Investment with Noise Trading Risk

This paper investigates the optimal dynamic investment for an investor who maximizes constant absolute risk aversion （CARA） utility in a discrete-time market with a riskfree bond and a risky stock. The risky stock is assumed to present both the dividend risk and the price risk. With our assumptions, the dividend risk is equivalent to fundamental risk, and the price risk is equivalent to the noise trading risk. The analytical expression for the optimal investment strategy is obtained by dynamic programming. The main result in this paper highlights the importance of differentiating between noise trading risk and fundamental risk for the optimal dynamic investment.     

工程项目风险元传递的系统动力学模型

基于广义项目风险元传递理论, 将导致工程量增加的因素视为风险元, 对工程项目风险元影响的传递情况进行了分析, 运用系统动力学构造出相应的因果关系循环图, 建立了风险元传递的系统动力学模型. 给模型中的变量赋值, 确定变量之间的函数关系, 利用iThink软件进行了模拟仿真. 结果表明: 风险元的发生对工程费用、工期以及质量都会产生不同程度的影响, 而且这种通过项目内部结构的传递影响是随风险元的增加而加速增长的. 另外, 反映项目各要素随时间动态变化的风险元传递模型的结果图能为风险管理及项目管理提供有力依据.     

基于突变级数法的油田管输建设工程项目环境风险评价

油田管道建设工程项目一般跨越空间范围较广,涉及的环境要素多,油品介质一旦发生泄漏其造成的环境污染后果是十分严重的,因此当前油田管道建设工程项目环境风险评价已成为国内外学术界所关注的一个热点。本文应用突变理论及突变级数评价法对自然环境因素、社会环境因素、交通环境因素三大要素进行分类,识别环境风险,确定风险等级,构建了管输建设环境风险评价驱动力因素指标体系以及管输建设环境风险评价突变模型。以陕北安塞——永坪管输工程项目为案例进行了实证研究,结合实测数据,得出影响管段风险重要度排序,指出其主要影响因素,提出相应的治理措施。     

工程进度风险因素的非叠加性影响

工程活动有时会受到单个风险因素影响, 有时则同时会受到多个风险因素影响, 现有研究很少关注多个风险因素同时作用于某一活动而产生的影响是叠加性影响还是非叠加性影响, 这在一定程度上影响了工程管理者做风险应对时的决策准确性. 拟采用贝叶斯网络验证风险因素同时发生时产生的影响是否等于各风险因素单独作用下所产生的影响之和. 算例表明当多个风险因素同时发生变化时, 对活动进度产生的影响为非叠加性影响. 研究结果为决策者在做风险应对时提供了更完备的信息.     

基于范例推理的后勤非对抗性仿真作业系统研究

在介绍基于范例推理方法基本原理的基础之上,分析了基于范例推理的后勤仿真作业系统的框架结构和工作原理;探索了应用范例推理方法实现后勤仿真作业系统的技术框架,仿真作业系统中对范例检索采用最相邻近策略,将范例属性采用对称二维表结构方式存储,对范例特征的影响程度依次检索。说明了仿真作业系统的学习机制,范例库学习中采用的多范例集成机制。     

新技术商业化的风险要素及其作用机理: 基于社会技术系统理论的实证研究

风险管理对新技术商业化项目的成长具有积极的影响, 但现有研究在深入考察企业新技术商业化活动面临的风险要素、 风险结构及其作用机理方面还存在不足. 社会技术系统理论被用来分析社会系统风险、技术系统风险与管理风险要素, 及其对企业新技术商业化项目绩效的影响. 应用结构方程模型进行实证研究, 结果表明: 1)社会子系统风险对技术子系统风险具有显著的正向影响; 2)技术子系统的风险增加会使项目管理的风险增加; 3)社会子系统风险对项目管理风险具有正向影响, 但不显著; 4)新技术商业化项目管理的风险越高, 项目成长的过程绩效就越低; 5)过程绩效对产品绩效具有显著正向影响.     

航天研发项目风险分析、等级评估及相关性研究

从航天项目风险案例统计分析出发,确定了影响航天项目研制的主要风险因素并对它们进行归纳和分类,给出了航天项目风险分析指标和结论。以航天项目风险案例统计和专家调查结果为依据,应用主客观相结合的方法将航天项目各种风险因素对项目研制性能指标的影响进行了评估,在此基础上综合得出各种风险因素对项目的综合影响度,并以此为依据对航天项目风险因素的等级进行了排序。同时,利用专用软件对各种风险因素之间的相关性进行分析,获得了各种风险因素排序和相互之间的相关系数,定量地反映出航天项目各类风险之间的关联度。构建了项目综合风险管理模型,设计了航天项目风险预警系统,增强了抵御航天项目风险的能力。     

基于BAM-Hamming神经网络的风险估计研究

现代弹药系统是一种集多门学科于一身的复杂系统 ,在研制过程中 ,由于受到不确定性因素的影响 ,会给研制工作带来一定的风险。提出了风险分析在弹药系统研制中的重要性 ,分析了各种风险分析与估计方法 ,给出了项目研制中风险特征因子及其估计方法 ,并将其转换成相应的二元码序列。利用BAM Hamming神经网络建立风险估计模型 ,采用最优编码方式 ,提高神经网络的容错性。以反直升机智能雷为例 ,验证了该方法的有效性和可靠性 ,以及一定的实用价值。     

基于复杂网络和随机游走算法的研发项目组合风险分析

针对项目组合中的风险分析问题,本文通过构建"项目组合-风险"双层网络模型,提出了基于随机游走算法的项目组合风险定量分析方法,以更准确地预测项目组合风险.首先,本文在研发项目间依赖关系分析的基础上,构建了项目组合网络,并采用设计结构矩阵(DSM)法建立了基于复杂网络中"邻接节点"的项目间连接强度模型.然后,采用多领域矩阵建立了由风险事件推导风险因素间依赖关系的模型.进一步,通过集成项目组合中项目间依赖关系、项目与风险因素间对应关系、以及风险因素间初始的依赖关系,构建了"项目组合-风险"双层网络模型,采用随机游走算法得到稳定状态下最终的"项目-风险因素"域映射矩阵(DMM)和风险因素DSM.最后,以某研发项目组合为例,采用随机游走算法进行项目组合风险的精准预测,并采用PageRank方法对风险因素进行排序,验证了本文提出模型和方法的有效性.     

国际工程承包的资金风险管理研究

将风险分析技术用于国际工程资金管理领域，在总结以往的风险分析理论的基础上，通过对国际工程承包资金风险的辨识、估计和评价，结合对工程现金流分析，系统分析了国际工程承包中可能遇到的风险，建立了一组资金风险评价的数学模型，并结合计算机模拟技术，编制了风险模拟计算程序．最后，以承包尼泊尔某工程为例，证明了该方法的可行性和有效性．     

数字建造情境下重大工程交易行为监管的协同演化仿真

数字建造平台的构建，提高了重大工程交易信息的共享程度，即降低了工程交易信息的不对称程度，因而成为重大工程交易行为监管的有力工具。为探讨在数字建造情境下重大工程交易行为监管系统中主体的策略形成及行为演化过程，结合演化博弈理论和系统动力学方法，构建了数字建造情境下重大工程交易行为监管的演化博弈系统动力学模型，探究了此情境下不同外部变量对工程发包方、工程监理方和工程承包方策略变化的影响，以及数字建造平台的等级对演化博弈策略稳定性的影响。结果表明，惩罚力度、监管成本和违规收益期望值对参与主体的交易行为有较大影响，以及随着数字建造平台等级的提升能有效地遏制工程监理方和工程承包方的违规行为。由这一结果，围绕数字建造平台设计科学合理的管理方式和博弈主体行为提出了相关建议，以高效实现重大工程建设目标。