The cascaded nature of lexical selection and integration in auditory sentence processing.

An event-related brain potential experiment was carried out to investigate the temporal relationship between lexical selection and the semantic integration in auditory sentence processing. Participants were presented with spoken sentences that ended with a word that was either semantically congruent or anomalous. Information about the moment in which a sentence-final word could uniquely be identified, its isolation point (IP), was compared with the onset of the elicited N400 congruity effect, reflecting semantic integration processing. The results revealed that the onset of the N400 effect occurred prior to the IP of the sentence-final words. Moreover, the factor early or late IP did not affect the onset of the N400. These findings indicate that lexical selection and semantic integration are cascading processes, in that semantic integration processing can start before the acoustic information allows the selection of a unique candidate and seems to be attempted in parallel for multiple candidates that are still compatible with the bottom-up acoustic input. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Perspectives of probabilistic inferences: Reinforcement learning and an adaptive network compared.

The assumption that people possess a strategy repertoire for inferences has been raised repeatedly. The strategy selection learning theory specifies how people select strategies from this repertoire. The theory assumes that individuals select strategies proportional to their subjective expectations of how well the strategies solve particular problems; such expectations are assumed to be updated by reinforcement learning. The theory is compared with an adaptive network model that assumes people make inferences by integrating information according to a connectionist network. The network's weights are modified by error correction learning. The theories were tested against each other in 2 experimental studies. Study 1 showed that people substantially improved their inferences through feedback, which was appropriately predicted by the strategy selection learning theory. Study 2 examined a dynamic environment in which the strategies' performances changed. In this situation a quick adaptation to the new situation was not observed; rather, individuals got stuck on the strategy they had successfully applied previously. This "inertia effect" was most strongly predicted by the strategy selection learning theory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

网管系统策略冲突解决的结果中存在的问题及检测与解决方法

当前，多种方法被用来解决网管系统中的策略冲突，不同方法有不同的应用范围，因此，通常需要综合应用多种方法来解决策略之间的冲突．各种方法解决策略冲突解决的过程是相对独立的，其策略冲突解决的结果也是相对独立的．在解决策略冲突的过程中，难以考虑到已经存在的策略冲突解决结果．因此。不同的策略冲突解决方法的结果之间可能存在冲突．分析了网管系统中多策略冲突解决方法的结果中可能存在的冲突，提出了检测及解决这些冲突的方法，并给出了实验结果及结论．     

探地雷达回波信号的特征提取和分类

探地雷达的回波信号具有非平稳特征.为实现非平稳信号的检测和分类,采用了二进小波变换、主分量分析与Fisher线性判别分析和前馈多层感知器分类器分别对探地雷达回波信号进行小波分解、去相关与特征选择和分类.实验结果表明,该算法具有很好的分类效果.     

谷物种子精选自动化系统研究

在计算机视觉动态检测技术基础上,研究了种子精选分级自动化系统.提出了系统检测工作原理及整体结构方案,并开发研制了样机.色标传感器对种子位置进行实时跟踪,自动获得运动中每一粒种子的位置信息.根据种子的形态学特征将种子分为4级.电磁阀控制高压气流的通断从而达到分级目的.整个试验台的控制由可编程控制器PLC完成.试验结果表明,当传送带速度达到0.3m/s,气压为0.85MPa时,种子分级合格率可达90%,系统处理速度为15粒/秒.     

产品总体方案评价与优选的证据推理决策

产品总体方案评价与优选决策是产品设计过程中的重要步骤,它是决定总体设计之后进行详细设计的关键环节。考虑产品总体方案评价与选择决策过程中不确定、不完全主观判断的混合多属性决策问题,提出基于证据推理的决策模型;对决策属性中定量属性的证据处理以及不同定性属性不同辨识框下的情况进行了讨论。最后给出了实例。     

基于粗糙集方法的水泥原材料选材算法研究

将粗糙集理论引入到水泥原材料的选材工作中，提出的方法以决策表作为主要工具，直接从实验样本集中导出选材规则，并揭示了选材实验数据信息的内在冗余性，通过例子表明了算法结果的有效性。     

基于粒子群优化算法的支持向量机参数选择及其应用

参数选择是支持向量机(SVM)研究领域的重要问题,它的本质是一个优化搜索过程,考虑到进化算法在求解优化问题上的有效性,提出了以最小化k-fold交叉验证误差为目标．粒子群优化(PSO)算法为寻优技巧的SVM参数调整方法．通过仿真例子验证该方法的有效性后,用其建立了聚丙烯腈生产过程中数均分子量的软测量模型,结果表明该方法有效．     

连锁门店选址与配送中心选择联合决策的f-MIGP模型

建立了连锁门店选址和配送中心选择联合决策问题的模糊多目标混合整数规划模型．针对该模型的特殊结构。提出一种适用的求解策略：首先确定每个模糊目标的隶属度函数；然后将模糊多目标混合整数规划模型转化为等价的清晰多目标混合整数规划模型，通过最大最小算子求出目标值；最后借助于两阶段算法，求出问题的最优解．通过应用算例进一步说明了该模型的有效性和可行性．     

智能交通系统模型的算法分析与改进

对智能交通系统中的求路段平均速度和平均旅行时间的算法进行了改进,采用间接法对路段平均行驶时间进行估测和对最优路径进行选择。通过收集多点的检测数据,在采用两点速度逼近平均速度的方法的同时,引入改进的流量融合技术来对某一路段的平均速度进行估测。在求平均旅行时间时,考虑到各路段旅行时间相互关联的情况,通过构造一个时间相关的协方差矩阵来描述各路段之间的相关性,与传统的算法相比,在实时更新方面更具优势。