基于D-S证据理论的磨粒识别

基于D-S证据理论的信息融合方法应用于磨损颗粒的自动识别,编制了相应的计算机识别程序。在对磨粒图象的形态特征参数进行筛选和统计分析的基础上,确定了各参数的统计容许限和决策基元概率。通过对一组标准磨粒的模拟识别试验,显示该方法具有算法简单、运行可靠、识别正确率高以及识别速度快的优点。      

人工智能在航天飞行任务规划中的应用研究

 在航天飞行任务中,如何设计航天器的飞行过程,如何确定地面对航天器的控制操作,如何制定飞行控制计划等,是地面飞行控制中心面临的重大问题,也是航天飞行任务规划所要解决的基本问题。在充分认识和把握人工智能基本原理、方法和技术的基础上,提出了一个基于规则演绎和状态演化的生长式推理模型,并对模型的特性进行了详细讨论,然后导出了该模型在航天飞行任务规划问题中的具体形式,从而成功地解决了航天任务自动规划的难题。通过在实际航天任务中的应用和验证,不仅证明该模型和方法是正确的、可行的和高效的,而且证明人工智能在航天飞行任务规划中有着广阔的应用前景。     

基于滑油监控信息的发动机磨损状态融合评估

针对现有航空发动机磨损状态评估方法的局限性,基于光谱分析和自动磨粒检测2种滑油分析方法的结果,提出了1种新的融合评估方法。结合专家经验,将各监控对象的磨损量和磨损率进行模糊推理,得到发动机的磨损状态可能向量,解决了发动机磨损状态评估过程中的模糊性问题。在决策层,运用D-S证据理论对2种滑油分析方法的推理结果进行融合时,考虑2种滑油分析方法的有效性,基于粗糙集理论与专家经验求得二者的可靠程度,最终得到更为合理的评估结果。实例表明:该方法可有效融合多种检测信息,解决评估过程中的不确定性问题,并可得到较为准确的评估结果。     

考虑扰动的无人机集群协同态势感知一致性评估

无人机（UAV）集群协同态势感知（SA）一致性是无人机集群协同作战的关键,对一致性进行评估至关重要。针对态势感知过程中面临的强不确定性等问题,在一致性评估指标体系的基础上,提出了基于证据推理规则的态势感知一致性评估方法,将各类指标信息统一至置信结构,并充分考虑指标的权重与可靠度。采用扰动分析法对复杂战场环境进行模拟,提出考虑扰动的态势感知一致性评估方法,并对算法进行了总结。最后,通过仿真算例和对比研究验证了所提方法在不确定性表达、一致性评估和无人机集群的环境适应性研究等方面的有效性。     

高校思政课教学中“以理服人”的路径探析

高校思政课教学最突出的特点是其理论性很强,这也正是学生觉得枯燥无味的地方,而这一年龄段的学生,其思维的独立性、全面性、深刻性与批判性有了很大发展,喜欢探究事情背后的原因。因此,要增强高校思政课教学实效,关键还在于思政课教师在教学活动中能否"以理服人",而要做到"以理服人",就要求教师要加强科研,以科研促教学;要创新教学方法和艺术,培养学生理论联系实际的能力;在教学过程中处理好政治性与学术性的关系。     

The cognitive adequacy of Allen's interval calculus for qualitative spatial representation and reasoning

Qualitative spatial reasoning (QSR) is often claimed to be cognitively more plausible than conventional numerical approaches to spatial reasoning, because it copes with the indeterminacy of spatial data and allows inferences based on incomplete spatial knowledge. The paper reports experimental results concerning the cognitive adequacy of an important approach used in QSR, namely the spatial interpretation of the interval calculus introduced by Allen (1983). Knauff, Rauh and Schlieder (1995) distinguished between the conceptual and inferential cognitive adequacy of Allen's interval calculus. The former refers to the thirteen base relations as a representational system and the latter to the compositions of these relations as a tool for reasoning. The results of two memory experiments on conceptual adequacy show that people use ordinal information similar to the interval relations when representing and remembering spatial arrangements. Furthermore, symmetry transformations on the interval relations were found to be responsible for most of the errors, whereas conceptualneighborhood theory did not appear to correspond to cognitively relevant concepts. Inferential adequacy was investigated by two reasoning experiments and the results show that in inference tasks where the number of possible interval relations for the composition is more than one, subjects ignore numerous possibilities and interindividually prefer the same relations. Reorientations and transpositions operating on the relations seem to be important for reasoning performance as well, whereas conceptual neighborhood did not appear to affect the difficulty of reasoning tasks based on the interval relations.     

On early cognitive mapping

In this paper we examine the nature of theearly cognitive map – the beginnings of acognitive map formed from one's earlyimpressions of the environment one is in. Twodistinct paradigms have emerged from ourstudies of what information is initially identified in a cognitive map. The first, which weterm a space-based approach, emphasises makingexplicit the spatial extent of the currentlocal environment. The second emphasises makingexplicit the relationships between objects inthe local environment and we call this anobject-based approach. For both paradigms weexamine the psychological literature to findsupport for the approach and the roboticists'attempts at implementing the idea. We arguethat a space-based approach is the moreappropriate way to compute an early cognitivemap. In particular, we find that Siegel andWhite's (1975) object-based hypothesis, whichstates that the developmental progression of acognitive map is from landmark to route tosurvey map, is not supported. The space-basedparadigm underpins our own work in this areaand we outline our own space-based theory forcomputing an early cognitive map.     

基于规则的航空发动机孔探图像诊断方法研究

针对军用航空发动机内部损伤频率高、诊断决策时间长的问题,运用基于规则的推理方法,结合案例推理,进行了航空发动机内部损伤维修决策的专家诊断研究,开发了基于孔探图像的航空发动机内部损伤维修决策专家系统。依据领域专家的经验,通过分析得到了对该型发动机的专家知识,并将其转换为if-then的知识规则存放于知识库中;利用图像处理方法,对损伤进行测量,得到损伤的尺寸参数;根据损伤尺寸,依据相应的知识规则,应用正向推理得到损伤的维修决策。运用多个航空发动机内部损伤实例验证了所开发的专家系统的有效性。     

Space,Language, and Ontology: A Response to Bateman

Abstract

Some of John Bateman's critiques of my article “Qualitative Spatial Reasoning in Interpreting Text and Narrative” are certainly valid. However, the alternative solutions that he proposes do not seem to me to be improvements.     

Managing Temporal Constraints with Preferences

Abstract

Preferences in temporal problems are common but significant in many real world applications. In this paper, we extend our temporal reasoning framework, managing numeric and symbolic information, in order to handle preferences. Unlike the existing models managing single temporal preferences, ours supports four types of preferences, namely: numeric and symbolic temporal preferences, composite preferences and conditional preferences. This offers more expressive power in representing a wide variety of temporal constraint problems. The preferences are considered here as a set of soft constraints using a c-semiring structure with combination and projection operators. Solving temporal constraint problems with preferences consists in finding a solution satisfying all the temporal constraints while optimizing the preference values. This is handled by a variant of the branch and bound algorithm, we propose in this paper, and where constraint propagation is used to improve the time efficiency. Experimental tests, we conducted on randomly generated temporal constraint problems with preferences, favor a variant of MAC as the constraint propagation strategy that should be used within the branch and bound algorithm.