神经网络多源数据融合磨机料位检测

针对火电厂磨煤机储煤量难与直接精准测量,造成磨机长期处于保守工况运行,制粉系统能耗损失巨大,效率低下的现实问题,,提出了基于神经网络多传感器信息融合的磨机料位智能软测量方法,仿真实验的数据融合结果表明了该方法的可行性和有效性,为进一步开展制粉系统的优化控制奠定了基础.     

无损检测中基于模糊逻辑的多传感器数据融合

模糊逻辑在多传感器数据融合中得到广泛的应用，但是基于模糊逻辑的多传感器数据融合在无损检测中的应用还是一个崭新的课题，本文给出了一种新的用于无损检测数据融合的模糊逻辑结构，并且给出了隶度函数以及运算符的定义，最后给出了例子阐明了这种结构在无损检测中的应用。     

基于多源数据融合的发电厂磨煤机煤种实时监测软件研究

目前,受燃煤市场供应和发电成本的影响,国内许多发电厂采用不同磨煤机分仓运行不同煤种的方式,而此类运行方式会使所燃用煤质特性发生大幅波动,对机组的正常运行会造成较大影响。目前,发电厂运行人员需要根据日常人工生成的配煤单信息来推算不同磨煤机中的煤种信息。而该方法无法精确控制过程数据,并且所得到结果也仅仅是经验数据,缺乏准确性和时效性。因此,本文基于多源数据融合设计了发电厂磨煤机煤种实时监测软件。该软件在电子化配煤单生成的条件下,结合发电厂实时数据中磨煤机煤仓的料位、煤量等信息,通过基于多源数据融合的方式来根据上煤时间和磨煤机煤量消耗度来计算出各台磨煤机不同煤种实时的高度和耗尽时间,并通过开发相应的监测页面进行展示,将掺配方案中制定的上煤方案以虚拟上煤的方式展现,并实现了磨煤机煤种的实时监测功能,对发电厂运行人员运行控制起到了指导作用。     

基于多传感器数据融合技术的短时交通流检测

在阐明智能交通控制系统（ITS）数据融合的意义和层次性的基础上,分析了数据层多源数据融合和神经网络的特点,根据遗传算法与BP算法各自的优缺点,设计了将遗传算法与改进的BP算法相结合的方法应用于融合计算,并提出了该方法的实现步骤。利用这种方法,对交叉路口的多源传感器数据进行融合计算后,仿真结果证明：该方法大大减少训练时间,能够有效地进行数据质量控制,提高数据的精度。     

基于神经网络的多传感器数据融合的分散型网络结构系统

多传感器数据融合在日益复杂的工业、军事等领域变得越来越重要,在实现方法上,神经网络由于其自身特点在该领域显示出广阔的应用前景。针对以往解决方案的不足,提出分散式的网络结构模型,详细描述了层次模型及各层次组成模块的工作原理及实现方法,然后提出高怪规划层的概念,用于实现分散型的网络结构。最后,进行了仿真实验,用实际数据论述该算法。     

基于模糊神经网络的信息融合技术研究

针对信息融合技术中目标融合识别的问题,根据人工神经网络和模糊系统的各自特点,形成一种模糊神经网络模型。首先将模糊系统用神经网络的结构表示,并采用相应的学习算法训练模糊神经网络实现模糊推理功能。最后对模糊神经网络模型进行仿真实验和结果分析。     

管道缺陷多超声传感器检测数据的神经网络融合

针对管道缺陷检测的现状,设计了超声传感器阵列检测系统,将神经网络技术应用于数据融合领域,采用改进的BP-LM算法对多个超声传感器测得的管道缺陷数据进行了融合处理.实验室检验结果表明,基于神经网络的数据融合大大提高了信号的质量,改进的BP-LM算法比标准BP算法融合效果更好,收敛速度更快.     

基于多传感器数据融合的智能小车避障的研究

针对智能小车避障问题,提出了一种将模糊逻辑和神经网络相结合的融合方法—Takagi-Sugeno(T-S)模糊神经网络方法。基于此方法的数据融合算法应用在智能小车避障运动中,采用多只超声波传感器和红外线传感器探测障碍物的距离和方向,采集的各种数据利用T-S模糊神经网络进行融合。通过实验仿真表明:此方法能够使智能小车对障碍物的灵活避障和导航行进。     

基于多传感器数据融合的无人机GPS欺骗检测研究

本文针对实际过程中可能存在的无人机GPS欺骗情况,提出了基于多传感器数据融合的GPS欺骗检测方法。该方法通过比较多传感器惯性导航系统加上Elman神经网络修正得到的位置信息与GPS输出位置信息,从而判断无人机GPS是否受到欺骗。该方法有两个创新点,第一个是使用Elman神经网络,在不增加传感器成本的基础上其有助于提高惯导系统输出位置信息的精度;第二个创新点是使用带延迟的扩展卡尔曼滤波器,用于解决多传感器数据不同步的问题。实验结果表明,本文提出的方法能有效的检测出GPS欺骗,从而保证无人机的安全飞行。     

基于数据融合智能检测的家居安全报警系统的设计

文章介绍了多传感器数据融合技术、智能检测系统的特点及智能家居安全报警系统软件的设计方法。文章采用PC机不同键盘信号来代替各传感器实时采集家庭的水、煤气、电、火情、偷盗、健康、抢劫、空气质量等报警信号。从键盘上直接输入信号，通过PC板卡型处理器，并进行数据融合后，做出正确的判断，从而根据不同的信号发出不同的报警响声。这种家用智能安全报警软件除可用于家庭外，也可用于大型室外设施场所。     

二型模糊相似度及其应用

二型模糊集可以直接处理高度不确定性,并且具有很强的实际应用背景。基于二型模糊相似度的公理化定义,给出了新的二型模糊相似度计算公式。进一步,将二型模糊相似度与Yang-Shih方法相结合,用于二型模糊数据的聚类分析,聚类结果与Yang-Lin的结果进行了比较,实例表明新的相似度更合理。此外,基于二型模糊相似度,讨论了二型模糊信息系统的属性约简问题,给出了相应约简的分辨函数法,并通过实例说明了该方法的具体计算步骤。     

二型模糊集的模糊熵研究

研究基于质心的二型模糊集的模糊熵和加权模糊熵,构造了两个二型模糊集的模糊熵度量.针对二型模糊集的特殊情形,提出一种新的区间值模糊集的模糊熵度量,既弥补了现有区间值模糊集退化为普通模糊集时熵为零的不足,又克服了两个明显不同的区间值模糊集熵相等的缺点.数值实例和仿真实验表明了所提出模糊熵的合理性和实用性.     

Some new distance measures for type-2 fuzzy sets and distance measure based ranking for group decision making problems

In this paper, we propose some distance measures between type-2 fuzzy sets, and also a new family of utmost distance measures are presented. Several properties of differ- ent proposed distance measures have been introduced. Also, we have introduced a new ranking method for the ordering of type-2 fuzzy sets based on the proposed distance measure. The proposed ranking method satisfies the reasonable prop- erties for the ordering of fuzzy quantities. Some properties such as robustness, order relation have been presented. Lim- itations of existing ranking methods have been studied. Fur- ther for practical use, a new method for selecting the best alternative, for group decision making problems is proposed. This method is illustrated with a numerical example.     

Some new distance measures for type-2 fuzzy sets and distance measure based ranking for group decision making problems

In this paper, we propose some distance measures between type-2 fuzzy sets, and also a new family of utmost distance measures are presented. Several properties of different proposed distance measures have been introduced. Also, we have introduced a new ranking method for the ordering of type-2 fuzzy sets based on the proposed distance measure. The proposed ranking method satisfies the reasonable properties for the ordering of fuzzy quantities. Some properties such as robustness, order relation have been presented. Limitations of existing ranking methods have been studied. Further for practical use, a new method for selecting the best alternative, for group decision making problems is proposed. This method is illustrated with a numerical example.     

Distinguishability of interval type-2 fuzzy sets data by analyzing upper and lower membership functions

In this paper, we deal with the problem of classification of interval type-2 fuzzy sets through evaluating their distinguishability. To this end, we exploit a general matching algorithm to compute their similarity measure. The algorithm is based on the aggregation of two core similarity measures applied independently on the upper and lower membership functions of the given pair of interval type-2 fuzzy sets that are to be compared. Based on the proposed matching procedure, we develop an experimental methodology for evaluating the distinguishability of collections of interval type-2 fuzzy sets. Experimental results on evaluating the proposed methodology are carried out in the context of classification by considering interval type-2 fuzzy sets as patterns of suitable classification problem instances. We show that considering only the upper and lower membership functions of interval type-2 fuzzy sets is sufficient to (i) accurately discriminate between them and (ii) judge and quantify their distinguishability.     

图像分割质量评价的二型模糊集方法

图像分割质量的评价是图像分割技术和算法研究的重要环节,在图像分析和计算机视觉中有着重要应用。依据二型模糊集在不精确性描述方面的独特优势,提出一种图像分割评判指标的二型模糊集表示方法,引入两种二型模糊集的模糊性度量作为图像分割质量的评判标准,构建图像分割质量评价模型。模拟实验验证了该模型的有效性和实用性。     

Finishing mill strip gage setup and control by interval type-1 non-singleton type-2 fuzzy logic systems

The setup and control of the finishing mill roll gap positions required to achieve the desired strip head thickness as measured by the finish mill exit X-ray gauge sensor is made by an intelligent controller based on an interval type-2 fuzzy logic system. The controller calculates the finishing mill stand screw positions required to achieve the strip finishing mill exit target thickness. The interval type-2 fuzzy head gage controller uses as inputs the transfer bar thickness, the width and the temperature at finishing mill entry, the strip target thickness, the width and the temperature at finishing mill exit, the stand work roll diameter, the stand work roll speed, the stand entry thickness, the stand exit thickness, the stand rolling force, and the %C of the strip. Taking into account that the measurements and inputs to the proposed system are modeled as type-1 non-singleton fuzzy numbers, we present the so called interval type-1 non-singleton type-2 fuzzy logic roll gap controller. As reported in the literature, interval type-2 fuzzy logic systems have greater non-linear approximation capacity than that of its type-1 counterpart and it has the advantage to develop more robust and reliable solutions than the latter. The experiments of these applications were carried out for three different types of coils, from a real hot strip mill. The results proved the feasibility of the developed system for roll gap control. Comparison against the mathematical based model shows that the proposed interval type-2 fuzzy logic system equalizes the performance in finishing mill stand screw positions setup and enhances the achieved strip thickness under the tested conditions characterized by high uncertainty levels.     

Supplier selection using a clustering method based on a new distance for interval type-2 fuzzy sets: A case study

Supplier selection is a decision-making process to identify and evaluate suppliers for making contracts. Here, we use interval type-2 fuzzy values to show the decision makers’ preferences and also introduce a new formula to compute the distance between two interval type-2 fuzzy sets. The performance of the proposed distance formula in comparison with the normalized Hamming, normalized Hamming based on the Hausdorff metric, normalized Euclidean and the signed distances is evaluated. The results show that the signed distance has the same trend as our method, but the other three methods are not appropriate for interval type-2 fuzzy sets. Using this approach, we propose a hierarchical clustering-based method to solve a supplier selection problem and find the proximity of the suppliers. To illustrate the applicability of the proposed method, first a case study of supplier selection problem with 8 criteria and 8 suppliers are illustrated and next, an example taken from the literature is worked through. Then, to test the hierarchical clustering-based method and compare with the obtained results by two other methods, a comparative study using experimental analysis is designed. The results show that while the proposed hierarchical clustering algorithm provides acceptable results, it is also conveniently appropriate for using interval type-2 fuzzy sets and obtaining proximity of suppliers.     

基于区间二型模糊粗糙集的连续属性约简算法

一型模糊粗糙集可以直接处理连续属性集,但不能处理高度不确定性数据,而区间二型模糊集可以增强系统处理不确定性的能力。为了提高处理噪声数据的精确度,在一型模糊粗糙集的基础上,定义区间二型模糊粗糙集。基于区间二型模糊粗糙集模型研究了连续域决策信息系统的属性约简,通过紧计算域给出了新的约简算法。由于拒绝变量集合的存在,提出的约简算法可在有限时间内收敛,并且得到了更加合理的结果。数值仿真验证了约简算法的可行性与有效性。     

Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets

In this paper, we present a new method to deal with fuzzy multiple attributes group decision-making problems based on ranking interval type-2 fuzzy sets. First, we propose a new method for ranking interval type-2 fuzzy sets. Then, we propose a new method for fuzzy multiple attributes group decision-making based on the proposed ranking method of interval type-2 fuzzy sets. We also use some examples to illustrate the fuzzy multiple attributes group decision-making process of the proposed method. The proposed method is simpler than the methods presented in [Chen and Lee, 2010a] and [Lee and Chen, 2010b] for fuzzy multiple attributes group decision-making based on interval type-2 fuzzy sets. It provides us with a useful way for dealing with fuzzy multiple attributes group decision-making problems based on interval type-2 fuzzy sets.