面向领域的关联规则评价方法及其应用

针对关联规则挖掘中,基于支持度-置信度框架的关联规则评价标准存在缺乏具体应用领域的分析,挖掘结果很难用于用户决策等问题,提出一种面向领域关联规则评价方法。该方法以领域知识为基准,发现满足技术兴趣度和商业兴趣度的规则,以国家住宅工程中心40个健康住宅试点项目的实际调查数据为例,进行试验和分析。在此基础上,设计并开发了居住健康领域挖掘系统,该系统采用多层次软件架构,包括知识库管理、挖掘数据选择、数据预处理、领域挖掘和结果评价等功能。实验结果和系统应用结果表明了面向领域关联规则评价方法的有效性。     

A comprehensive solution for application‐level adaptation

Driven by the emergence of mobile and pervasive computing there is a growing demand for context‐aware software systems that can dynamically adapt to their run‐time environment. We present the results of project MADAM that has delivered a comprehensive solution for the development and operation of context‐aware, self‐adaptive applications. The main contributions of MADAM are (a) a sophisticated middleware that supports the dynamic adaptation of component‐based applications, and (b) an innovative model‐driven development methodology that is based on abstract adaptation models and corresponding model‐to‐code transformations. MADAM has demonstrated the viability of a general, integrated approach to application‐level adaptation. We discuss our experiences with two real‐world case studies that were built using the MADAM approach. Copyright © 2008 John Wiley & Sons, Ltd.     

无线传感器网络的元胞自动机自组织算法

提出一种分布式、自适应的无线传感器网络元胞自动机(CA)自组织算法,将网络中的每个节点映射成CA中的元胞,通过控制节点在不同时间的状态转换(活跃/睡眠),消除与邻居节点间的频繁通信,从而降低能源消耗。仿真实验结果表明,该算法具有较强的目标检测能力。     

一种基于XML的任务驱动型数据传输与同步方法

出于信息安全和业务需要,人们在彼此逻辑或物理隔离的局域网环境中浏览和处理信息,但是又不想丧失网络互联带来的便利和强大的信息处理能力。通过数据传输与同步机制,模拟广域网环境、避免信息孤岛是一种现实可行的选择。给出了一种基于XML的任务驱动的数据传输与同步方法,通过分析数据传输场景,设定了基于XML的任务数据模板和任务结果数据模板,借助于具体的信息化系统,基于相应的模板,自动生成任务数据包及任务数据结果包,以数据光盘进行信息传输,通过数据寻址、定位及导入操作实现了数据同步功能。通过该数据通路,实现了各级彼此独立的信息系统的互联,用户犹如在一个互联的广域网环境中进行数据处理。该方法大大提升了信息系统的安全性,降低了铺设或租用线路的成本,解决了各级网络之间不连通导致的信息壁垒,更符合现阶段特殊行业使用网络环境的要求。     

基于数据驱动的微小故障诊断方法综述

能否及时诊断出微小故障是保障系统安全运行并抑制故障恶化的关键,本文针对微小故障幅值低、易被系统扰动和噪声掩盖等特点,从数据驱动的角度对现有研究进行综述.并将其分为三大类: 基于统计分析的微小故障诊断技术、基于信号处理的微小故障诊断技术和基于人工智能的微小故障诊断技术,进而对不同方法的基本研究思想、研究进展、应用以及局限性予以介绍.最后不仅指出复杂系统微小故障诊断研究中的现存问题,而且从增加新的信息、挖掘未利用的隐含信息和采用新的数学工具三个角度进行展望,提出基于关联性分析、基于多源信息融合、基于机器学习和基于时频分析四个值得探究的微小故障诊断思想.     

基于自适应动态规划的矿渣微粉生产过程跟踪控制

矿渣微粉是一种新型绿色环保型建材,可以大大提高水泥混凝土的力学性能.本文以矿渣微粉生产过程为研究对象,针对该过程难以通过机理建模进行辨识和控制的特点,利用数据驱动的思想,建立矿渣微粉生产过程的递归神经网络模型.在此基础上,利用自适应动态规划,设计具有控制约束的跟踪控制器,并将其应用到矿渣微粉生产过程中.仿真分析表明,建立的数据驱动模型能够有效地辨识矿渣微粉生产过程,同时,本文提出的控制方法能够实现输入受限的微粉比表面积及磨内压差的最优跟踪控制.     

Robust state estimation for wireless sensor networks with data‐driven communication

Robust state estimation problem for wireless sensor networks composed of multiple remote sensor nodes and a fusion node is investigated subject to a limitation on the communication rate. An analytical robust fusion estimator based on a data‐driven transmission strategy is derived to save the sensor energy consumption and reduce the network traffic congestion. The conditions guaranteeing the uniform boundedness of estimation errors of the robust fusion estimator are investigated. Numerical simulations are provided to show the effectiveness of the proposed approach. Copyright © 2017 John Wiley & Sons, Ltd.     

Expedited simulation‐driven design optimization of UWB antennas by means of response features

In this work, a method for fast design optimization of broadband antennas is considered. The approach is based on a feature‐based optimization (FBO) concept where reflection characteristics of the structure at hand are formulated in terms of suitably defined feature points. Redefinition of the design problem allows for reducing the design optimization cost, because the dependence of feature point coordinates on antenna dimensions is less nonlinear than for the original frequency characteristics (here, S‐parameters). This results in faster convergence of the optimization algorithm. The cost of the design process is further reduced using variable‐fidelity electromagnetic (EM) simulation models. In case of UWB antennas, the feature points are defined, among others, as the levels of the reflection characteristic at its local in‐band maxima, as well as location of the frequency point which corresponds to acceptable reflection around the lower corner frequency within the UWB band. Also, the number of characteristic points depends on antenna topology and its dimensions. Performance of FBO‐based design optimization is demonstrated using two examples of planar UWB antennas. Moreover, the computational cost of the approach is compared with conventional optimization driven by a pattern search algorithm. Experimental validation of the numerical results is also provided.     

A Novel Framework for Human Activity Recognition with Time Labelled Real Time Sensor Data

Human activity recognition is an effective approach for identifying the characteristics of historical data. In the past decades, different shallow classifiers and handcrafted features were used to identify the activities from the sensor data. These approaches are configured for offline processing and are not suitable for sequential data. This article proposes an adaptive framework for human activity recognition using a deep learning mechanism. This deep learning approach forms the deep belief network (DBN), which contains a visible layer and hidden layers. The processing of raw sensor data is performed by these layers and the activity is identified at the top most layers. The DBN is tested using the real time environment with the help of mobile devices that contain an accelerometer, a magnetometer, and a gyroscope. The results are analyzed with the metrics of precision, recall, and the F1-score. The results proved that the proposed method has a higher F1_score when compared to the existing approach.     

基于数据驱动的航天器三维可视化系统设计

航天器数据庞大繁杂,为了给设计人员提供快速检验设计思想的便捷工具,对基于数据驱动的航天器三维可视化系统进行了研究。在分析航天器可视化系统特点的基础上,提出系统功能要求,继而提出了基于数据驱动的三维可视化系统构建方案,介绍了可视化系统组成、核心模块关系。在基于MFC框架及Vega Prime为主的开发的前提下,对系统模块划分进行了研究,给出模块功能和实现方案。为了提升系统展示效果,对消息缓冲与插值延迟、特效集成与驱动机制、相机管理和场景切换等关键技术提出了优化设计方案,使之更加适应航天器可视化展示需求。设计系统较传统可视化系统展示更为流畅,场景视角切换更为智能。系统已应用于多个航天器研发工作中,应用效果证明系统具有良好的通用性和实用性,具有一定的推广价值。