Weighted dynamic time warping for time series classification

Dynamic time warping (DTW), which finds the minimum path by providing non-linear alignments between two time series, has been widely used as a distance measure for time series classification and clustering. However, DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point. This may lead to misclassification especially in applications where the shape similarity between two sequences is a major consideration for an accurate recognition. Therefore, we propose a novel distance measure, called a weighted DTW (WDTW), which is a penalty-based DTW. Our approach penalizes points with higher phase difference between a reference point and a testing point in order to prevent minimum distance distortion caused by outliers. The rationale underlying the proposed distance measure is demonstrated with some illustrative examples. A new weight function, called the modified logistic weight function (MLWF), is also proposed to systematically assign weights as a function of the phase difference between a reference point and a testing point. By applying different weights to adjacent points, the proposed algorithm can enhance the detection of similarity between two time series. We show that some popular distance measures such as DTW and Euclidean distance are special cases of our proposed WDTW measure. We extend the proposed idea to other variants of DTW such as derivative dynamic time warping (DDTW) and propose the weighted version of DDTW. We have compared the performances of our proposed procedures with other popular approaches using public data sets available through the UCR Time Series Data Mining Archive for both time series classification and clustering problems. The experimental results indicate that the proposed approaches can achieve improved accuracy for time series classification and clustering problems.     

A set of new Chebyshev kernel functions for support vector machine pattern classification

In this study, we introduce a set of new kernel functions derived from the generalized Chebyshev polynomials. The proposed generalized Chebyshev polynomials allow us to derive different kernel functions. By using these polynomial functions, we generalize recently introduced Chebyshev kernel function for vector inputs and, as a result, we obtain a robust set of kernel functions for Support Vector Machine (SVM) classification. Thus in this study, besides clarifying how to apply the Chebyshev kernel functions on vector inputs, we also increase the generalization capability of the previously proposed Chebyshev kernels and show how to derive new kernel functions by using the generalized Chebyshev polynomials. The proposed set of kernel functions provides competitive performance when compared to all other common kernel functions on average for the simulation datasets. The results indicate that they can be used as a good alternative to other common kernel functions for SVM classification in order to obtain better accuracy. Moreover, test results show that the generalized Chebyshev kernel approaches to the minimum support vector number for classification in general.     

制取木薯淀粉粘合剂新工艺

研究木薯淀粉粘合剂的制备工艺,讨论了各因素对淀粉粘合剂的影响,给出较佳配方和工艺条件并可用于实际生产,同时介绍了在瓦楞纸箱生产上的应用效果。     

阿尔夏提水库浇筑式沥青混凝土心墙施工技术与质量控制

【摘要】本文针对新疆阿尔夏提水库库区气候及材料特点,结合大坝沥青混凝土心墙施工配合比、拌和站布置、施工方法、施工工艺及质量控制等要求,探索总结出适用于小型工程沥青混凝土心墙施工及质量控制的方法。     

阳离子乳化沥青混凝土配合比设计的优选方法研究

采用均匀正交试验对水泥掺量、乳液用量、拌合用水量三个因素进行优选,得到阳离子乳化沥青混凝土的基础配合比参数。通过测定每组沥青混凝土试件的稳定度和流值,并采用投影寻踪回归分析法(PPR)研究了水泥掺量、乳液用量和拌合用水量对稳定度和流值的影响规律,研究发现,对于稳定度和流值影响最大的因素是水泥掺量,其次是乳液用量的影响,而拌合用水量对稳定度和流值影响较小。     

库什塔依水电站沥青心墙坝坝基快速高效灌浆施工技术

库什塔依水电站沥青心墙坝坝基灌浆帷幕沿坝轴线上、下游布置,在基座混凝土上进行灌浆。灌浆与沥青心墙施工形成不间断施工,制约了沥青心墙的浇筑和大坝的填筑进度。结合库什塔依水电站的施工实际,对提高沥青心墙坝坝基灌浆效率进行了分析。     

碾压式沥青混凝土防渗技术应用与探讨

KZJ大坝是在新疆寒冷地区建成的首座碾压式沥青混凝土心墙砂砾石坝。结合其设计和施工
过程,介绍了该坝体结构与防渗体布置,心墙与坝基防渗体的连接和坝基处理。基于大坝完建期观测
资料和坝体三维有限元应力应变静力计算结论,分析了大坝施工对运行状态的影响,并研究了沥青混
凝土心墙坝在寒冷地区的施工可行性,旨在为新疆水利水电工程推广应用碾压式沥青混凝土心墙防渗
技术积累经验。     

Application of the modified Taylor approximation

In this paper we introduce and describe a new scheme for the numerical integration of smooth functions. The scheme is based on the modified Taylor expansion and is suitable for functions that exhibit near-sinusoidal or repetitive behaviour. We discuss the method and its rate of convergence, then implement it for the approximation of certain integrals. Examples include integrands involving Airy wave, Bessel, Gamma, and elliptic functions. The results, from the data in the tables, demonstrate that the method converges rapidly and approximates the integral as well as some well-known numerical integration methods used with sufficiently small step sizes.     

基于抗裂的沥青路面合理结构研究

利用专门的道路设计程序,对半刚性基层沥青路面进行结构力学计算。通过沥青路面内的应力大小和分布分析,得到层底拉应力随结构力学参数(各材料层厚度、模量及结构形式)变化规律,据此提出避免沥青面层疲劳开裂和半刚性基层反射裂缝的沥青路面合理结构,并指出基于抗裂的沥青路面材料组合设计方向。研究结果对半刚性基层沥青路面结构组合设计具有理论参考价值。     

基于改进的自适应遗传算法的GIS服务组合研究

摘要针对当前GIS系统中集成应用模型时存在的数据和功能冗余、模型难以复用等问题,将GIS应用模型分解为子模型,与GIS功能一起,以服务的方式提供给用户,并对这些GIS服务定义服务质量(QoS);最后,提出了一种基于改进的自适应遗传算法(MAGA)的服务组合方法,以实现GIS服务组合的全局优化。