房地产投资过程中决策树概率加权现值分析的研究

本文根据房地产投资的基本特点,提出了一组决策树概率加权现值分析模型,并以案例分析为依据,剖析了这组模型的决策思路及其作用。     

CaCO3固硫炼焦及其对生铁含硫量影响的实验室研究

研究了用ＣａＣＯ３作固硫剂的焦炭性质,并探讨了固硫焦对生铁含硫量的影响因素,结果表明用ＣａＣＯ３作用硫剂炼焦是可行的。     

基于时空域集成判决的微小运动目标检测方法

提出了一种基于时-空域集成判决的序列图像中微小运动目标检测方法。首先,将背景杂波抑制后的残差图像沿时间轴进行累加,形成组合帧,在组合帧中经过二元假设门限判决,检测出疑似目标;然后,只对疑似目标按可能的运动方向进行空域能量集成;最后,对目标轨迹进行统计判别。算法的性能分析和实验仿真结果表明,该方法在保证较高检测概率的同时,大大减少了运算量,有利于实时实现。     

基于知识发现和决策规则的遥感图像城区土地覆盖/利用分类方法

提出一种利用地类的色度信息、小波提取纹理特征、植被指数及形状知识等采用规则推理有效识别遥感土地类别的方法。采用知识发现和决策规则方法,可以充分吸收遥感专家的思想和工作经验,可以充分利用多种模糊性地学知识来提高遥感影像分类效果。最后通过实例证明了该方法的有效性。     

数据的逻辑综合分析及决策算法

文章给出了逻辑综合分析的基本理论和决策算法。并利用逻辑综合中逻辑单元的随机覆盖问题产生的随机数据,对算法加以验证。实验结果表明决策算法的精确度可以达到97.2%。     

基于改进分辨矩阵的增量式数据挖掘模型研究

粗糙集理论是近年来出现的处理模糊和不确定性的数学工具,并已广泛应用于人工智能的许多领域。文章针对在增量式数据环境下挖掘决策规则的特点,在回顾基于分辨矩阵的数据挖掘算法及其不足的基础上,利用决策矩阵的概念有效地处理具有不同决策类的各种决策系统。在此基础上提出相应的对每一个决策类建立决策矩阵的增量式挖掘算法,最后利用算例验证了算法的合理性和有效性。该算法步骤同传统的分辨矩阵算法相比,能在增量式环境下快速而有效地进行确定性规则和可能性规则的学习并对可能性规则建立相应的置信度,使规则的获取更具实用性。     

基于数据仓库的电信事业决策支持系统

针对当前电信事业,建立了以数据仓库技术、OLAP技术、数据挖掘技术相结合的电信事业决策支持系统。     

基于Vague集模糊推理的多评价指标模糊决策方法

目前在智能领域中对Vague集的研究已越来越广泛与深入,并运用于决策问题中,有学者已把Vague集用于多评价指标的模糊决策中,但其决策方法在某些时候却难以得到目标。为此,本文提出了一个基于Vague集模糊推理的多评价指标模糊决策方法。在这个方法中,从基于Vague集的模糊推理的观点来看待模糊决策问题。将评价指标和候选方案之间的关系用一组基于Vague集的推理规则来表示,将决策者的要求用一组Vague集来表示,经过模糊推理等过程最后得到决策结果。然后还给出了一个实例说明这种多评价指标模糊决策方法。这个基于Vague集模糊推理的多评价指标模糊决策方法的提出为决策系统提供了一个有用的工具。     

Optimal load rating-based inspection planning of corroded steel girders using Markov decision process

Steel girder bridges are vulnerable to corrosion. To maintain their safety above a predefined target level, the load rating can be computed from the inspection results and guide the following maintenance actions. Optimizing inspection and maintenance based on load ratings has substantial practical and economic relevance. Load rating-based strategies can be categorized based on whether the inspection interval and replacement criteria are fixed or flexible. Existing studies focus on fixed inspection intervals throughout the service life. In general, their results are not optimal for inspection planning. To reduce life-cycle cost, aged steel girders may be inspected and repaired in an adaptive manner. To this end, a method based on Markov decision process (MDP) is proposed to compare the life-cycle cost of four load rating-based policies (i.e. uniform or adaptive non-uniform inspection interval, and fixed or adaptive replacement threshold). Load rating-based inspection planning is formulated as MDP and the optimal plans are obtained using dynamic programming. The conventional approach to discretize states cannot accurately approximate the non-stationary deterioration process, while state augmentation is successful in doing this but will increase computational cost. A comparison of two approaches is made to investigate their effects on life-cycle cost. A bridge girder under corrosion attack is used as an illustrative example. The results show that the load rating-based plan with an adaptive non-uniform inspection interval and fixed replacement threshold obtained using the state augmentation technique can be near-optimal.     

Efficient reliability analysis of dynamic k-out-of-n phase-AND mission systems

Motivated by real-world applications of satellites and wireless sensor networks, this paper models and evaluates a dynamic k-out-of-n phase-AND mission system (k/n-PAMS). The mission task conducted by a k/n-PAMS involves multiple consecutive phases; the mission is successful as long as the task is successful in any of the phases. Due to factors, such as scheduled maintenance, location changes in task execution during different phases, and resource sharing with other tasks, the total number of available components n for the considered mission task and the required number of working components k may change from phase to phase. In addition, due to varying load and working environments, component failure time distributions are also phase dependent. This paper proposes an analytical modeling approach based on multivalued decision diagrams (MDDs) for assessing reliability of the considered k/n-PAMS. The approach encompasses a new and fast MDD model generation algorithm that considers behaviors of all the mission phases simultaneously based on node labeling. As demonstrated through empirical studies on k/n-PAMSs with different sizes (different numbers of phases and different numbers of system components), the proposed algorithm is more efficient than the traditional phase-by-phase model generation method.