Automatic detection of electroencephalographic changes using adaptive neuro-fuzzy inference system employing Lyapunov exponents

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for automatic detection of electroencephalographic changes. Decision making was performed in two stages: feature extraction by computation of Lyapunov exponents and classification by the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of electroencephalogram (EEG) signals were classified by five ANFIS classifiers. To improve diagnostic accuracy, the sixth ANFIS classifier (combining ANFIS) was trained using the outputs of the five ANFIS classifiers as input data. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the saliency of features on classification of the EEG signals were obtained through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in classifying the EEG signals.     

A transaction pattern analysis system based on neural network

Customer segmentation is a key element for target marketing or market segmentation. Although there are quite a lot of ways available for segmentation today, most of them emphasize numeric calculation instead of commercial goals. In this study, we propose an improved segmentation method called transaction pattern based customer segmentation with neural network (TPCSNN) based on customer’s historical transaction patterns. First of all, it filters transaction data from database for records with typical patterns. Next, it reduces inter-group correlation coefficient and increases inner cluster density to achieve customer segmentation by iterative calculation. Then, it utilizes neural network to dig patterns of consumptive behaviors. The results can be used to segment new customers. By this way, customer segmentation can be implemented in very short time and costs little. Furthermore, the results of segmentation are also analyzed and explained in this study.     

基于聚度的PSO参数分析

对PSO方法中粒子运行规律给出较为完整的分析,考察随机性对粒子运动过程的影响,提出聚度的概念,并 通过粒子的聚度考察粒子在实际运行条件下的分布情况,给出更加具体的参数设置区间,提出一种粒子在运动过程中 的速度补偿策略,对于一些参数设置可以通过该策略提高搜索性能,该策略对实际应用中选择和调整PSO算法参数 有较强的指导意义。     

An optimal online algorithm for halfplane intersection

The intersection of N halfplanes is a basic problem in computational geometry and computer graphics,The optimal offline algorithm for this problem runs in time O(N log N).In this paper,an optimal online algorithm which runs also in time O(N log N) for this problem is presented.The main idea of the algorithm is to give a new definition for the left side of a given line,to assign the order for the opoints of a convex polygon.and then to use binary search method in an ordered vertex set.The data structure used in the algorithm is no more complex than array.     

木质素栲胶的制备、表征及复鞣的作用

采用氢气还原降解木质素的方法制备了木质素栲胶,用Folin-Ciocalteu试剂法对木质素栲胶中酚羟基含量的变化进行了测定,并利用紫外吸收光谱和红外吸收光谱对其化学结构进行了分析。用木质素栲胶对铬鞣猪皮正面革进行复鞣实验,研究了不同用量木质素栲胶对成革感观和物理性能的影响。结果表明,降解后木质素栲胶中酚羟基的质量摩尔浓度增加了30.12%;当木质素栲胶的加入量为2%时,成革的弹性和柔软性好,丰满度良好,粒面紧实,收缩温度为94.8℃,抗张强度为14.5N/mm2,撕裂强度为19.3N/mm,复鞣效果最佳。木质素栲胶的复鞣性能达到了植物复鞣剂的水平。     

TiO2中空纤维光催化研究及设备设计

利用生物模板法-脱脂棉为模板,于不同温度烧结得二氧化钛（TiO2）中空纤维,利用X射线衍射、扫描电镜等进行表征,研究得出550℃高温下烧结的TiO2中空纤维光催化性能最佳,以浓度为10mg/L甲基橙为目标降解物,在pH值为2,TiO2中空纤维浓度为2.5g/L,紫外灯照射180min后降解率可达90%以上,二次降解率可达77%以上。在此最优实验条件的基础上,设计了一套新型光催化降解有机废水二级处理装置,第一级装置采用TiO2中空纤维作为催化剂,第二级装置采用活性炭和TiO2混合物作为催化剂,实验测试结果较好,极具实际应用与推广价值。     

低碳酒店发展策略探析

低碳旅游是顺应全球低碳经济的发展而提出的,低碳酒店作为低碳旅游的重要部分,在当代社会也发挥着重要的节能减排作用。通过对国内低碳酒店的现状调查,可以发现在酒店方面实行节能减排还具有很大的潜能,文章提出了一些低碳酒店发展策略,以期为国内酒店的低碳发展提供参考。     

PSO的向量整体修订策略和局部跳出策略

针对传统PSO方法对CEC2005(The 2005 IEEE Congress on evolutionary computation)中的25个benchmark函数搜索效果较差的问题,提出了"向量整体修订"和"局部跳出"两种改进策略。改变PSO方法中粒子在每一维上的修订相互独立的传统机制,按某一概率将粒子作为整体进行修正,当群体最优长时间不变或变化值小于一定阈值时,为跳出局部最优,按某一概率重新定义群体最优或初始化群体。通过实验证明了改进后的PSO方法对CEC2005中的测试问题的有效性。     

无线传感器网络节点移动路径优化方法

为解决移动传感器修复网络覆盖空洞时最优级联移动路径的选择问题,综合考虑中间级联节点的个数和能量,提出了选择级联移动路径的优化方法.该方法通过计算中间级联节点的能量可用率,进一步得出各路径的能量可用率和决定性能量,从多目标优化的角度来选择最优的级联移动路径,有效均衡了各移动传感器的能耗,充分利用了整个网络的能量,从而延长了网络的生存时间.仿真结果表明,该优化方法比标准的级联移动方法有更高的网络能量使用效率.     

Growth Behavior of α Phase in Ti-5.6Al-4.8Sn-2.0Zr-1.0Mo-0.35Si-0.7Nd Titanium Alloy

The thermal stability of the microstructure of a near-α titanium alloy after aging at 750℃ was investigated using optical microscope and transmission electron microscope as well as composition analysis. Aging treatment brings about significant coarsening of grain boundary α and α platelets within the colonies for martensitic microstructure. The observed changes are related to the growth steps or ledges of the interface and lamellar termination presented in the microstructure. The composition analysis of the coarsened α plate is consistent with the growth kinetics. The α Widmanstaetten plates were coarsened due to the movement of α /β interface for Widmanstaetten microstructure, and the phase boundaries of primary α（αp） phase directly moved into the transformed β for bimodal microstructure.