A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach

This study presents a strategy-aligned fuzzy simple multiattribute rating technique (SMART) approach for solving the supplier/vendor selection problem from the perspective of strategic management of the supply chain (SC). The majority of supplier rating systems obtained their optimal solutions without considering firm operations management (OM)/SC strategy. The proposed system utilizes OM/SC strategy to identify supplier selection criteria. A fuzzy SMART is applied to evaluate the alternative suppliers, and deals with the ratings of both qualitative and quantitative criteria. The final decision-maker incorporates the supply risks of individual suppliers into final decision making. Finally, an empirical study is conducted to demonstrate the procedure of the proposed system and identify the suitable supplier(s).     

A decision support system for engineering design based on an enhanced fuzzy MCDM approach

Design concept is an important wealth-creating activity in companies and infrastructure. However, the process of designing is very complex. Besides, the information required during the conceptual stage is incomplete, imprecise, and fuzzy. Hence, fuzzy set theory should be used to handle linguistic problem at this stage. This paper presents a fuzzy integrated approach to assess the performance of design concepts. And those criteria rating, relative weights and performance levels are captured by fuzzy numbers, and the overall performance of each alternative is calculated through an enhanced fuzzy weighted average (FWA) approach. A practical numerical example is provided to demonstrate the usefulness of this study. In addition, this paper, in order to make computing and ranking results easier to increase the recruiting productivity, develops a computer-based decision support system to help make decisions more efficiently.     

小波分析在基于内容的图像检索技术中的应用

简要介绍了小波分析的基本理论及基于内容的图像检索技术,重点阐述了小波分析在图像的特征提取(纹理、目标形状等)上的应用,并展望了基于内容的图像检索技术今后的主要研究方向。     

A decision support system for coating selection based on fuzzy logic and multi-criteria decision making

Wear and corrosion are the most important factors that the surface of the engineering parts must confront. The need for protection and improvement of the mechanical characteristics of the surface of engineering parts can be to some extent satisfied by coatings. Coatings are considered as an excellent solution when resistance to corrosion, oxidation or low friction is demanded, but due the complexity of selecting the appropriate one, engineers often avoid them. The need for simultaneous consideration of qualitative and quantitative properties, render the use of classic material selection theories inadequate. An expert system for coating selection is presented in this paper, which can handle both qualitative and quantitative variables. The mathematical model used combines the multi-criteria decision making theories (MCDM) together with the fuzzy sets theory. The “Max-Min set” method is applied to calculate the ordering value of the alternatives while the TOPSIS method is used to rank them. A numerical example is provided to illustrate the method. Finally, the process presented can be easily computerized, to create the relative software.     

基于内容的图像检索技术研究

随着数字图像在多媒体领域的广泛应用,对基于内容的图像检索技术的需求也不断增加.基于内容的图像检索技术总体上可以分为两部分:图像特征提取、图像特征的索引与匹配.图像特征提取主要解决如何在数学上有效地描述一幅图像.文中分别介绍了颜色、形状和纹理特征提取算法近年来的研究成果.图像特征索引与匹配,主要解决如何根据特征描述判断图像间的相似程度,并准确、快速列出图像库中与检索图像相似的图像,分别介绍了相似度测量方法、聚类与分类技术、相关反馈技术三类技术的主要研究成果.最后对基于内容的图像检索技术的研究难点进行了讨论,对未来可能的研究方向进行了展望.     

基于内容的医学图像检索技术

建立一个高效、准确的医学图像检索系统是目前具有挑战性的任务.文中在简述基于内容的医学图像检索模型后,着重探讨和分析了检索模型中图像特征提取、特征选择与融合、相似度匹配、图像预过滤、相关反馈等核心技术和相关算法,以及一些最新的应用.最后对基于内容的医学图像检索技术进行了展望.     

A fuzzy decision support system for credit scoring

Neural Computing and Applications - Credit score is a creditworthiness index, which enables the lender (bank and credit card companies) to evaluate its own risk exposure toward a particular...     

A fuzzy decision support system for digital camera selection based on user preferences

Mobile phones have been the most rapidly spreading development in the field of communication and information technologies over the past decades. Nowadays, digital cameras have taken their place. The wide product range in the market, each with numerous heterogeneous technical attributes, complicates the selection of the most convenient camera for end-users. The aim of this work is to provide end-users with a decision support framework for selecting the best digital camera according to their preferences. End-users and photography experts use subjective assessments when determining their requirements and making their evaluations. The proposed decision support tool is built on the basis of fuzzy set theory. The imprecision of the subjective assessments are transformed to fuzzy triangular numbers. The fuzzy analytic hierarchy process (FAHP) and fuzzy compromise programming methodologies are applied in order to determine the relative weights of sub-criteria and criteria and to rank the digital camera alternatives, respectively.     

A New Indexing Scheme for Content-Based Image Retrieval

We propose a new efficient indexing scheme, called the HG-tree, to support content-based retrieval in image databases. Image content is represented by a point in a multidimensional feature space. The types of queries considered are the range query and the nearest-neighbor query, both in a multidimensional space. Our goals are twofold: increasing the storage utilization and decreasing the area covered by the directory regions of the index tree. The high storage utilization and the small directory area reduce the number of nodes that have to be touched during the query processing. The first goal is achieved by suppressing node splitting if possible, and when splitting is necessary, converting two nodes into three. This is done by proposing a good ordering on the directory nodes. The second goal is achieved by maintaining the area occupied by the directory region as small as possible. This is done by introducing the smallest interval that encloses all regions of the lower nodes. We note that there is a trade-off between the two design goals, but the HG-tree is so flexible that it can control the trade-off to some extent. We present the design of our indexing scheme and associated algorithms. In addition, we report the results of a series of tests, comparing the proposed index tree with the buddy-tree, which is one of the most successful point indexing schemes for a multidimensional space. The results show the superiority of our method.     

基于快速小波变换的高适应性图像检索技术研究

在目前已有的研究工作中,基于自适应小波的图像特征在基于内容的图 像检索领域获得了广泛的应用。但这些方法存在一个共同问题,即采用相同的小波基描述不 同的查询图像。为了提高图像检索技术的自适应能力,本文对不同的查询图像设计不同的小 波基表示,从而实现用可调整的距离测度表征不同类别图像的特征改变。为了进一步降低表 征图和表征导数图的求取时间,该文使用了近似泰勒展开。实验结果表明,这种新的图像检 索技术具有高度的自适应能力,检索性能也大幅度提高。     

A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell

The selection process of a suitable machine tool among the increased number of alternatives has been an important issue for manufacturing companies for years. This is because the improper selection of a machine tool may cause many problems that will affect the overall performance. In this paper, a decision support system (DSS) is presented to select the best alternative machine using a hybrid approach of fuzzy analytic hierarchy process (fuzzy AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE). A MATLAB- based fuzzy AHP is used to determine the weights of the criteria and it is called program for Priority Weights of the Evaluation Criteria (PWEC), and the PROMETHEE method is applied for the final ranking. The proposed model is structured to select the most suitable computer numerical controlled (CNC) turning centre machine for a flexible manufacturing cell (FMC) among the alternatives which are assigned from a database (DB) created for this purpose. A numerical example is presented to show the applicability of the model. It is concluded that the proposed model has the capability of dealing with a wide range of desired criteria and to select any type of machine tool required for building an FMC.     

Regions-of-Interest and Spatial Layout for Content-Based Image Retrieval

To date most content-based image retrieval (CBIR) techniques rely on global attributes such as color or texture histograms which tend to ignore the spatial composition of the image. In this paper, we present an alternative image retrieval system based on the principle that it is the user who is most qualified to specify the query content and not the computer. With our system, the user can select multiple regions-of-interest and can specify the relevance of their spatial layout in the retrieval process. We also derive similarity bounds on histogram distances for pruning the database search. This experimental system was found to be superior to global indexing techniques as measured by statistical sampling of multiple users' satisfaction ratings.     

基于快速小波包直方图技术的图像检索算法

提出了一种基于快速小波包直方图技术的图像检索新算法。此方法主要有图像的小波包分解,最主要能量频带的选择和小波包直方图的抽取及相似性度量三个步骤。首先,用一族正交小波基分解一幅图像并用小波包系数计算各个频带的能量;其次,选择几个最主要能量频带进行阈值化和非线性滤波;最后,抽取小波包直方图作为特征表示并应用直方图相交距离从图像数据库中检索被查询图像。由于该方法在特征抽取中应用较小的特征空间,因此需要较小的计算复杂性。实验结果表明,这些技术在图像检索中可以获得更好的性能。     

A hybrid fuzzy group decision support framework for advanced-technology prioritization at NASA

The prioritization of advanced-technology projects at the National Aeronautic and Space Administration (NASA) is a difficult task. This difficulty is due to the multiple and often conflicting objectives in addition to the inherent technical complexities and valuation uncertainties involved in the assessment process. As such, a systematic and transparent decision support framework is needed to guide the assessment process, shape the decision outcomes and enable confident choices to be made. Methods for solving Multi-Criteria Decision Making (MCDM) problems have been widely used to select a finite number of alternatives generally characterized by multiple conflicting criteria. However, applying these methods is becoming increasingly difficult for technology assessment in the space industry because there are many emerging risks for which information is not available and decisions are made under significant uncertainty. In this paper, we propose a hybrid fuzzy group decision support framework for technology assessment at NASA. The proposed objective framework is comprised of two modules. In the first module, the complicated structure of the assessment criteria and alternatives are represented and evaluated with the Analytic Network Process (ANP). In the second module, the alternative advanced-technology projects are ranked using a customized fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We demonstrate the applicability of the proposed framework through a case study at the Kennedy Space Center.     

一种基于内容和图象检索方法的实现

本文在直方图技术的基础上引入了颜色对方法，将图象的空间特性反映出来，因而能检索具有清晰边界的图象，并且图象的大小变化和旋转以及轻微的光照变化不影响检索结果。     

基于内容的图像检索系统的设计与实现

本文描述了基于内容的图像检索系统@IMAGE的设计和实现。该系统综合运用了多媒体、媒体存储、数据组织和表示方法、图像检索技术等。也介绍了基于图像颜色、形状和纹理的检索算法。给出了@IMAGER系统结构、实现技术和功能。     

图像检索中一种新的相关反馈机制

1.引言近年来,随着图像数据的大量增加,对图像进行智能化、基于内容的处理愈来愈引起人们的极大兴趣。除了使用手工输入的关键字外(基于文本的方法),其于内容的图像检索(Content-Based Image Retrieval,CBIR)系统也使用图像的视觉特征来建立图像索引,所使用的图像低层特征包括:颜色、纹理和形状等。在CBIR系统中,最常用的检索模式是“例子查询”(Query By Example,QBE),即首先由用户选取一个或多个例子图像(Query Images),然后,系统自动地从图像库中检索出与其相似的数据库图像。在这种检索模式中,系统的检索能力完全依赖于图像特征的性质以及用户所选取的例子图像的质量。到目前为止,大多数研究均侧重于寻找一种最好的图像表示方法,而对于人在CBIR系统中的作用以及检索过     

RETIN: A Content-Based Image Indexing and Retrieval System

This paper presents RETIN, a new system for automatic image indexing and interactive content-based image retrieval. The most original aspect of our work rests on the distance computation and its adjustment by relevance feedback. First, during an offline stage, the indexes are computed from attribute vectors associated with image pixels. The feature spaces are partitioned through an unsupervised classification, and then, thanks to these partitions, statistical distributions are processed for each image. During the online use of the system, the user makes an iconic request, i.e. he brings an example of the type of image he is looking for. The query may be global or partial, since the user can reduce his request to a region of interest. The comparison between the query distribution and that of every image in the collection is carried out by using a weighted dissimilarity function which manages the use of several attributes. The results of the search are then refined by means of relevance feedback, which tunes the weights of the dissimilarity measure via user interaction. Experiments are then performed on large databases and statistical quality assessment shows the good properties of RETIN for digital image retrieval. The evaluation also shows that relevance feedback brings flexibility and robustness to the search.     

Developing a group decision support system based on fuzzy information axiom

Information axiom, one of two axioms of axiomatic design methodology which is proposed to improve a design, is used to select the best design among proposed designs. In the literature, there are a lot of studies related to using of information axiom for the solution of decision making problems. Moreover, applications of information axiom have been increasing day by day. However, calculation procedure of information axiom is not only incommodious but also difficult for decision makers. In this paper, a decision support system (DSS) based on fuzzy information axiom (FIA) is developed in order to make this decision procedure easy. The developed system consists of a knowledge base module including facts and rules, inference engine module including FIA and aggregation method, and a user interface module including entrance windows. The main aim of this study is to present a DSS tool to help the decision makers to solve their decision problems by modifying data-base of the program. In this paper, an application procedure will be presented based on the optimal selection of location for emergency service to illustrate the implementation procedure of the proposed model.     

A predictive maintenance system for multi-granularity faults based on AdaBelief-BP neural network and fuzzy decision making

Predictive maintenance of production equipment is a prerequisite to ensure safe and reliable manufacturing operations. To avoid unexpected shutdown and even casualties caused by faults during production, it is paramount to design an effective predictive maintenance decision system for production equipment. Most of the related research works concentrate on early warn of specific faults but neglect the differentiations of the fault severity. To address the issue, this paper presents an intelligent predictive maintenance system for multi-granularity faults of production equipment based on the AdaBelief-BP (back propagation) neural network and the fuzzy decision making. The characteristics of the system presented in this paper include: (1) The proposed system implements a two-stage framework, integrating the functions of fault type prediction and fault degree prediction, which can provide comprehensive fault information throughout production lifecycles; (2) On the maintenance solution identification stage, fuzzy logic-based decision making is carried out to determine appropriate maintenance solutions based on the practical vague boundary of fault severity. In the system, the design of the AdaBelief-BP neural network can achieve a higher convergence rate and a better generalization capability as well. Meanwhile, to the best of our knowledge, in this research, it is the first time to use the migration of the fuzzy membership degree as the indicator of the changing condition of fault severity to facilitate more accurate maintenance solution identification. To verify the effectiveness of the system, comparison experiments with some popular algorithms are conducted. Benchmarking results show that the developed system can achieve higher prediction accuracy as well as higher efficiency than the comparative methods.