复杂对象系统多目标综合评价的神经网络方法

复杂对象系统多目标综合评价是一个典型的定性与定量相结合的模糊决策问题，本文将神经网络理论应用于复杂对象系统的综合评价，提出了一种基于Ｂ－Ｐ神经网络的复杂对象系统多目标综合评价方法，并对神经网络的结构、神经网络输入指标属性值的量化方法、神经网络学习及其应用神经网络综合评价的计算机实现算法做了讨论。本文最后介绍了该方法在城市发展水平综合评价中的应用实例。     

不完备判断信息情境下群组DEMATEL决策方法

为克服群组决策试行与评价实验室（DEMATEL）方法难以处理不完备专家判断信息问题，以及预先指定评价标度和群组信息集成规则不适应复杂决策环境的内在缺陷，本文基于群共识排序理论，提出一种能够有效处理不完备判断信息的群组DEMATEL决策方法。该方法的创新之处在于：第一，它能够以灵活的标度方式有效地反映群组专家的偏好判断表达。第二，它也能通过序列转换和共识度的引入较好地处理群组DEMATEL不完备判断信息。第三，它能够合理地反映决策结果因群共识水平不同而变化的复杂机理。实例验证结果表明，所提方法是切实可行的，能够有效解决实践中的决策问题。     

改进AHP-BP神经网络算法研究——以建筑企业循环经济评价为例

针对传统AHP中专家权重确定方法的局限性,本文提出一种基于利益相关者视角的专家权重确定方法对AHP进行改进。首先计算专家之间的利益相关系数,然后依据评价值矩阵得到所有专家的综合评价值,进而确定每一位专家在专家群体中的评价权重,最后将传统AHP所得指标权重与专家评价权重进行加权平均即得各指标的综合权重。再以改进AHP得到的评价值作为先验样本进行BP神经网络的训练与测试,得到可供推广的分类器。以建筑企业循环经济评价进行实证研究,结果表明构建的改进AHP-BP神经网络模型所得评价结果较已有方法更为准确可靠。     

应用BP神经网络模糊推理的资源城市主导产业评价

确定主导产业是决定资源城市产业转型成败重要因素,为了能够更有效地评价主导产业,文中引入BP神经元网络技术,结合模糊逻辑和专家意见法进行主导产业的评价.其中为了提高BP神经网络的准确性,结合资源城市的特点,对国内外产业选择指标进行了分析比较、归纳并确立了评价指标体系.最后以实例验证了应用BP神经网络结合模糊逻辑和专家意见法进行主导产业的评价的准确性.     

基于熵和证据理论的NPD项目复杂性模糊评价

基于文献综述和专家调查,构建了NPD项目复杂性评价指标体系,并运用"结构熵权法"确定了各指标权重。基于证据"可信度"和"确定性",定义了证据"有效性",结合证据冲突全局分配的思想,改进了证据合成方法;运用改进的证据合成方法综合专家评价信息,构造了"模糊评价矩阵"。依据模糊评价原理对NPD项目复杂性进行评价,并结合算例分析说明了该方法的可行性和实用性。     

基于改进模糊层次分析的管理咨询评价方法研究

文章讨论了一种处理管理咨询公司选择评价中不确定与不精确性的方法.视评价过程为不确定性环境下、基于多尺度定性定量判断的决策问题,决策者的判断用模糊数表示.基于三角模糊数对传统层次分析法做了改进.在评价过程中,两两比较矩阵用三角模糊数表示并将模糊优先问题转化为非线性规划.示例表明该方法可应用于服务评价.     

基于FNN的软件项目绩效评价模型研究

从分析软件项目绩效评价指标体系不完善、评价方法不规范和模型考虑因素过于单一入手,应用统计分析理论建立软件组织状态、软件项目自身特征的指标体系;以文献研究的方式,界定软件项目绩效的内涵;提出了一种新的网络拓扑结构设计方法,建立了基于模糊神经网络的软件项目绩效评价模型;引入改进粒子群学习算法,准确高效地解决了评价模型连接权系数的确定问题。实证研究表明,该模型能够有效地评价软件项目绩效和识别项目风险因素,对软件组织制定风险规避策略、改善项目绩效水平、提供了决策支持信息。     

基于BP神经网络的电子政务绩效评价研究

在构建电子政务绩效评价指标体系的基础上,提出了一种基于BP神经网络的电子政务绩效综合评价方法。神经网络方法有效克服了现有专家评价方法的不足,为评价电子政务系统的建设质量、成本耗费及绩效水平提供了一种新的模型。     

基于人工神经网络的企业知识管理综合评价模型研究

本文主要研究人工神经网络在企业知识管理评价中的应用问题。为了克服综合评价过程的随机性与评价专家主观上的不确定性,本文提出基于人工神经网络的企业知识管理综合评价模型。该模型采用多层前馈神经网络及BP算法,其仿真实现是以MATLAB下神经网络工具箱作为开发工具。通过仿真实例与专家评估相比较,验证了该模型的有效性。     

基于知识和模糊神经网络的学习型评价系统

提出一种学习型评价系统的建立方法. 评价功能是基于决策者(专家) 的知识和模糊神经 网络实现的,适用于以语言型变量为主的系统的评价问题. 样本数据集的建立及语言型变量的 描述,是通过挖掘专家知识,建立符合其偏好的隶属函数实现的. 该评价系统可以充分利用以 往的决策案例,通过学习获取决策者的知识和经验,从而得到与决策者的评价结论相同的评价 结果.     

基于DEA理论的ANP/BOCR方案评价值综合集成新方法

网络分析法(ANP)是一种能够有效处理复杂决策问题的多准则决策方法。然而现有ANP文献在对收益、机会、成本、风险(统称为BOCR)评价值综合集成时会因评价值之间的不匹配而可能得出错误的方案排序结果和绩效表示。为克服上述缺陷,本文基于数据包络分析理论提出一种新的针对ANP/BOCR评价值的综合集成方法,使用摆幅置权区间估计方式反映出了决策者在判断BOCR相对权重时所面临的不精确性和模糊性。实例验证结果表明,所提方法对BOCR评价值的处理更符合实际情况。     

Supply Networks as a Complex Adaptive System: Toward Simulation‐Based Theory Building on Evolutionary Decision Making

In this article, we examine how the firms embedded in supply networks engage in decision making over time. The supply networks as a complex adaptive system are simulated using cellular automata (CA) through a dynamic evolution of cooperation (i.e., “voice” decision) and defection (i.e., “exit” decision) among supply network agents (i.e., firms). Simple local rules of interaction among firms generate complex patterns of cooperation and defection decisions in the supply network. The incentive schemes underlying decision making are derived through different configurations of the payoff‐matrix based on the game theory argument. The prisoner's dilemma game allows capturing the localized decision‐making process by rational agents, and the CA model allows the self‐organizing outcome to emerge. By observing the evolution of decision making by cooperating and defecting agents, we offer testable propositions regarding relationship development and distributed nature of governance mechanisms for managing supply networks.     

The Impact of Joint Responses of Devices in an Airport Security System

In this article, we consider a model for an airport security system in which the declaration of a threat is based on the joint responses of inspection devices. This is in contrast to the typical system in which each check station independently declares a passenger as having a threat or not having a threat. In our framework the declaration of threat/no-threat is based upon the passenger scores at the check stations he/she goes through. To do this we use concepts from classification theory in the field of multivariate statistics analysis and focus on the main objective of minimizing the expected cost of misclassification. The corresponding correct classification and misclassification probabilities can be obtained by using a simulation-based method. After computing the overall false alarm and false clear probabilities, we compare our joint response system with two other independently operated systems. A model that groups passengers in a manner that minimizes the false alarm probability while maintaining the false clear probability within specifications set by a security authority is considered. We also analyze the staffing needs at each check station for such an inspection scheme. An illustrative example is provided along with sensitivity analysis on key model parameters. A discussion is provided on some implementation issues, on the various assumptions made in the analysis, and on potential drawbacks of the approach.     

An Information-Maximizing Interactive Procedure for Scenario Probability Elicitation

Various approaches have been proposed for determining scenario probabilities to facilitate long-range planning and decision making. These include microlevel approaches based on the analysis of relevant underlying events and their interrelations and direct macrolevel examination of the scenarios. The determination of a unique solution demands excessive consistency and time requirements on the part of the expert and often is not guaranteed by these procedures. We propose an interactive information maximizing scenario probability query procedure (IMQP) that exploits the desirable features of existing methods while circumventing their drawbacks. The approach requires elicitation of cardinal probability assessments and bounds for only marginal and first-order conditional events, as well as ordinal probability comparisons (probability orderings or rankings) of carefully selected scenario subsets determined using concepts of information theory. Guidelines for implementation based on simulation results are also developed. A goal program for handling inconsistent ordinal probability responses is also integrated into the procedure. The results of behavioral experimentation (which compared our approach to Expert Choice and showed that the IMQP was viable) compared favorably in terms of ease of use and time requirements, and works best for problems with a large number of scenarios. Design modifications to IMQP learned from the experiments, such as incorporating interactive graphics, are also in progress.     

工程项目资源均衡的遗传算法及其MATLAB实现

本文采用基于生物进化理论的遗传算法进行工程项目的资源均衡研究,克服了传统资源平衡算法的不足,并利用MATLAB语言进行编程实现,根据目标函数的具体要求,有效解出单资源和多资源平衡问题的最优解,同时得到每项作业的最优开始时间,通过实例分析,验证了算法的有效性和可靠性,取得了良好的效果。     

洪水灾害风险分析的系统理论

从系统论的观点出发 ,提出了洪水灾害复杂大系统的概念 ,并以这一概念为基础 ,探讨了洪水灾害风险特征及洪水灾害风险评价的基本内容 ,提出并系统地阐述了以洪水危险性分析、承灾体易损性分析和洪水灾害灾情评估为核心内容的洪水灾害风险分析的系统理论     

基于复杂网络理论的股票指标关联性实证分析

复杂网络理论是研究股票市场内在结构和功能的有力工具,股票指标的关联性已成为研究股票市场的一个新视角。基于复杂网络理论对深沪300指数(2011年7月28至2012年2月28)构建网络拓扑结构。利用DFA进行数据筛选,计算筛选后数据的股票指标的绝对相关系数。根据股票指标的绝对相关系数概率分布确定阈值,构建网络拓扑结构,计算股票指标的网络统计特征指标,分析收益率、成交量、市盈率的网络结构。研究结果表明,股票收益率和成交量指标的具有较强的关联性,具有小世界性质;市盈率指标具有较弱的关联性,不具有小世界性质,是随机网络且受外界影响较大、效率低下,风险比较大。     

组织知识系统的知识超网络模型及应用

利用网络模型研究知识系统,是当前知识管理研究者感兴趣的热点问题之一.现有的单一要素模式的知识网络不能反映组织知识系统的复杂构成和整体结构.采用超网络的思想和方法对这一问题进行了研究,提出了组织知识系统的知识超网络模型.该模型由三种节点、六种边构成,可用于表示组织知识系统中的知识、人、存储载体等三类要素及其之间的复杂关系,因而可反映组织知识系统的复杂构成及结构形态.文中对模型的应用做了初步探讨,包括:知识组织、知识表示、知识结构分析、知识定位搜索、分析组织知识管理活动等.该模型为组织知识管理提供了一种新的工具和思路.     

Reconstruction of decision-making behavior in shareholder and stakeholder theory: implications for management accounting systems

This paper focuses on two interrelated research questions. First, an analysis of managerial decision-making is incorporated into shareholder and stakeholder theory. Secondly, the paper investigates what consequences result for management accounting from inherent conceptions of managerial decision-making behavior. These research questions are based on assumptions of complex interrelationships among decision-making managers, management accountants, and techniques they employ. The findings of this research support that tenets of management accounting systems correspond best with shareholder theory. In doing so they apply financial measures, pursue the goal of profit maximization, and focus on decision-making behavior resulting from the agency relationship between shareholder and manager. Stakeholder theory, however, is fundamentally different from shareholder theory in terms of goals, management philosophy, relationships, behavioral assumptions etc. For these reasons differences with respect to managerial decision-making behavior are reasonable and different requirements related to management accounting systems appear appropriate.