基于减法聚类模糊推理系统的短期负荷预测

采用减法聚类辅助模糊推理系统进行电力系统短期负荷预测。首先用减法聚类建立T-S模糊模型,然后通过调整聚类半径优选模糊规则数,以取得具有良好泛化性能的模型,最后利用梯度下降混合最小二乘算法精调参数。利用某局网负荷数据对ANFIS网络模型进行训练和检测,然后用于负荷预测,所得结果表明该算法鲁棒性好,抗干扰能力强,并且预测时间较ANFIS大大减少。     

Application of Fuzzy Logic for the Solution of Inverse Kinematics and Hierarchical Controls of Robotic Manipulators

In this paper, hierarchical control techniques is used for controlling a robotic manipulator. The proposed method is based on the establishment of a non-linear mapping between Cartesian and joint coordinates using fuzzy logic in order to direct each individual joint. The hierarchical control will be implemented with fuzzy logic to improve the robustness and reduce the run time computational requirements. Hierarchical control consists of solving the inverse kinematic equations using fuzzy logic to direct each individual joint. A commercial Microbot with three degrees of freedom is utilized to evaluate this methodology. A decentralized fuzzy controller is used for each joint, with a Fuzzy Associative Memories (FAM) performing the inverse kinematic mapping in a supervisory mode. The FAM determines the inverse kinematic mapping which maps the desired Cartesian coordinates to the individual joint angles. The individual fuzzy controller for each joint generates the required control signal to a DC motor to move the associated link to the new position. The proposed hierarchical fuzzy controller is compared to a conventional controller. The simulation experiments indeed demonstate the effectiveness of the proposed method.     

单目标跟踪中基于RSSI的模糊测距技术

针对基于接收信号强度因子（RSSI）测距中存在的问题提出一种新的测距技术,由白适应模糊神经推理系统训练的模糊推理系统建立一个模型,利用这个模型将RSSI映射为相应的收发节点的距离。将此模糊测距技术应用到基于三点定位的单目标跟踪中,仿真实验证明了该测距技术是切实可行的。     

An efficient soft-computing technique for extraction of EEG signal from tainted EEG signal

Electroencephalography (EEG) is the recording of electrical activity of neurons within the brain and is used for the evaluation of brain disorders. But, EEG signals are contaminated with various artifacts which make interpretation of EEGs clinically difficult. In this research paper, we use a soft-computing technique called ANFIS (Adaptive Neuro-Fuzzy Inference System) for the removal of EOG artifact, combined EOG and EMG artifact. Improvement in the output signal to noise ratio and minimum mean square error are used as the performance measures. The outputs of the proposed technique are compared with the outputs of techniques such as neural network, based on ADALINE (Adaptive Linear Neuron) and adaptive filtering method, which makes use of RLS (Recursive Least Squares) algorithm through wavelet transform (RLS-Wavelet). The obtained results show that the proposed method could significantly detect and suppress the artifacts.     

基于雾计算的智能医疗三方认证与密钥协商协议

在智能医疗中,将云计算技术与物联网技术结合,可有效解决大规模医疗数据的实时访问问题.然而,数据上传到远程云服务器,将带来额外的通信开销与传输时延.借助雾计算技术,以终端设备作为雾节点,辅助云服务器在本地完成数据存储与访问,能够实现数据访问的低延迟与高移动性.如何保障基于雾计算的智能医疗环境的安全性成为近期研究热点.面向基于雾计算的智能医疗场景,设计认证协议的挑战在于:一方面,医疗数据是高度敏感的隐私数据,与病人身体健康密切相关,若用户身份泄漏或者数据遭到非法篡改将导致严重后果;另一方面,用户设备和雾节点往往资源受限,认证协议在保护用户隐私的同时,需要实现用户、雾节点、云服务器之间的三方数据安全传输.对智能医疗领域两个具有代表性的认证方案进行安全分析,指出Hajian等人的协议无法抵抗验证表丢失攻击、拒绝服务攻击、仿冒攻击、设备捕获攻击、会话密钥泄漏攻击;指出Wu等人的协议无法抵抗离线口令猜测攻击、仿冒攻击.提出一个基于雾计算的智能医疗三方认证与密钥协商协议,采用随机预言机模型下安全归约、BAN逻辑证明和启发式分析,证明所提方案能实现双向认证与会话密钥协商,并且对已知攻击是安全的;与同类...     

SG-Edge: 电力物联网可信边缘计算框架关键技术

随着国家电网电力物联网的逐步推进,作为其核心支撑技术的边缘计算框架逐渐成为研究热点.首先,总结了物联网和边缘计算框架方面的已有研究工作;其次,通过分析电力物联网在业务场景、边缘计算、信息安全等方面的关键技术难题,提出了一种适应于电力物联网的可信边缘计算框架SG-Edge;随后,结合边缘框架的可信防护关键难题,给出了硬件可信引导、软件行为动态度量等关键技术方法;最后,从业务适应性、安全性以及性能等方面对SG-Edge进行了全面评估,并对未来研究可能面临的挑战进行了展望.     

混沌时间序列的自适应变异差分进化ANFIS预测

提出了一种基于自适应变异差分进化（AMDE）算法的ANFIS模型对混沌时间序列进行预测的方法;该方法采用自适应变异差分进化算法和最小二乘法相结合的混合学习算法对ANFIS网络结构参数进行优化设计;利用差分进化算法的全局寻优能力对ANFIS网络前件参数进行优化;而网络的结论参数采用最小二乘法优化;混合学习算法提高了网络参数辨识的收敛速度和系统的全局收敛性;仿真实验结果表明了该方法的有效性。     

物联网技术在信息化建设中的应用

物联网作为当前迅猛发展的新技术,势必带来一场深刻的科技变革.但是,作为一种新兴的信息产业,发展物联网存在各个方面的问题.对物联网的技术及应用进行了研究,分析了物联网的发展及应用现状,指出了影响物联网发展的因素,以及对物联网发展的探索.     

使用新混合模糊聚类算法的模糊系统建模方法

为了进一步提高模糊系统建立模型的精度,提出一种新的模糊系统算法ANFIS-HC-QPSO：采用一种混合型模糊聚类算法来对模糊系统的输入空间进行划分,每一个聚类通过高斯函数的拟合产生一个隶属度函数,即完成ANFIS系统的前件参数--隶属度函数参数的初始识别,通过具有量子行为的粒子群算法QPSO与最小二乘法优化前件参数,直至达到停机条件,最终得到ANFIS的前件及后件参数,从而得到满意的模糊系统模型。实验表明,AN-FIS-HC-QPSO算法与传统算法相比,能在只需较少模糊规则的前提下就使模糊系统达到更高的精度。     

物联网与绿色智能建筑

针对智能建筑的发展模式,结合智慧地球与物联网,本文阐述了物联网与视联网的相关技术,并分析了物联网在智能建筑中的应用,最后指出物联网、视联网是实现智能城市建筑的关键技术,而建筑智能化系统工程是物联网、视联网的应用基础。     

SmartHerd management: A microservices-based fog computing–assisted IoT platform towards data-driven smart dairy farming

Internet of Things (IoT), fog computing, cloud computing, and data-driven techniques together offer a great opportunity for verticals such as dairy industry to increase productivity by getting actionable insights to improve farming practices, thereby increasing efficiency and yield. In this paper, we present SmartHerd, a fog computing–assisted end-to-end IoT platform for animal behavior analysis and health monitoring in a dairy farming scenario. The platform follows a microservices-oriented design to assist the distributed computing paradigm and addresses the major issue of constrained Internet connectivity in remote farm locations. We present the implementation of the designed software system in a 6-month mature real-world deployment, wherein the data from wearables on cows is sent to a fog-based platform for data classification and analysis, which includes decision-making capabilities and provides actionable insights to farmer towards the welfare of animals. With fog-based computational assistance in the SmartHerd setup, we see an 84% reduction in amount of data transferred to the cloud as compared with the conventional cloud-based approach.     

软件定义的无线电提供IoT远程联接

如果不联接,物联网(IoT)和工业物联网(IIoT)就会成为数十亿台设备的集合,其功能和用途有限。互联和联接到云的能力使得这些节点成为我们现在家庭、办公室、工厂和公共场所非常依赖的有用设备。虽然使用有线联接,但在许多情况下,无线技术是首选技术,但各种不同的节点类型和应用意味着没有单一的普遍方案.事实上,方案的数量在增加,包括以标准为导向的技术和在许可和无许可证频谱中运行的协议,以及专有技术。即使如此,情况也在发生变化,因为软件无线电(SDR)提供灵活性,而这种灵活性是纯硬件方案不可能做到的。     

基于HBase的大规模无线传感网络数据存储系统

无线传感网络(WSN)存在分布的跨区域性,随着无线传感网络的扩张,传感器数目增多,将产生大规模的传感数据。针对存储大规模无线传感网络数据的问题,提出了一个两层分布式存储架构,使用分布式数据库HBase存储跨区域的无线传感网络数据和全局数据存储管理目录,实现一个近实时的存储系统。实验结果证明,该系统有良好的扩展性、存储和查询效率。     

Integration of Adaptive Neuro Fuzzy Inference Systems and principal component analysis for the control of tertiary scale formation on tinplate at a hot mill

Scale is highly detrimental to surface quality for tinplate products. There are a large number of process variables at a typical hot mill and principal component analysis is a well-known technique for reducing the number of process variables. This paper estimates the principal components associated with the hot mill process variables and puts these through an Adaptive Neuro Fuzzy Inference System (ANFIS) to find those hot mill running conditions that will minimise the amount of scale observed on the bottom of the rolled strip. It was found that the variation observed in all the hot mill process variables could be captured through the use of just six principal components, and that using just three of these in an ANFIS was sufficient to identify those operating conditions leading to coils being produced with a consistently low scale count. Specifically, it was found that the best operating conditions for the hot mill were when the first component was lower than −0.098 the second lower than 0.8058 and the third higher than −0.482. These ranges in turn corresponded to certain hot mill temperatures that depended to some extent on the base chemistry of the incoming slab.     

基于区块链的物联网认证机制综述

随着物联网(Internet of Things, IoT)技术的高速发展,各类智能设备数量激增,身份认证成为保障IoT安全的首要需求.区块链作为一种分布式账本技术,提供了去信任的协作环境和安全的数据管理平台,使用区块链技术驱动IoT认证成为学术界和工业界关注的热点.基于云计算和云边协同两种架构分析IoT身份认证机制设计的主要需求,总结区块链技术应用于IoT场景面临的挑战;梳理现有IoT身份认证机制的工作,并将其归结为基于密钥的认证、基于证书的认证和基于身份的认证;分析应用区块链技术的IoT认证工作,并根据认证对象和附加属性对相关文献进行归纳和总结.从形式化和非形式化两个方向总结基于区块链的IoT认证机制的安全性分析方法.最后展望了未来研究方向.     

车联网：物联网在城市交通网络中的应用

阐述了“物联网”和“车辆网”这两个热门概念的内涵和外延。通过分析两者的发展历程、历史沿革和相互关系,比较它们在实际生活中的应用, 认为车联网可以看作物联网在城市交通网络中的典型应用,展望了车联网在服务与应用方面的美好愿景。以此为基础,讨论了车联网实现的关键技术,并介绍了一个过渡型构建方案。最后,详细讨论了在物联网和车联网领域里国内外学术研究现状。     

基于实体-数据的物联网服务建模

物联网服务作为信息世界软件服务通过物联网向现实世界的延伸,其在物联网系统具有重要的作用.然而,不同于传统Web服务,物联网服务具有现实感知、数据驱动、异构分布、时空相关等新特点,使得现有的服务模型不足以对物联网服务有效刻画,进而也不能满足物联网应用中的后续服务发现、服务卸载、服务组合等需求.在凝练分析物联网服务建模需求和已有物联网服务模型的基础上,提出了一种基于实体-数据的物联网服务建模框架,该框架提出了服务、实体、数据三元信息融合的物联网服务模型概念及概念关系,重点定义了服务、实体、数据的时空属性及时空依赖关系,以支持基于时空相关性的物联网服务关联表示与分析,并通过扩展OWL-S(ontology Web language for services)给出了基于实体-数据的物联网服务描述方式.最后,结合一个高速公路物联网应用案例对模型的使用方式和效果进行了讨论.