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Dissertations / Theses on the topic 'Fuzzy Weighted'

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Published: 3 June 2025
Last updated: 31 July 2025

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1

Cai, Chun Hing. "Mining association rules with weighted items." Hong Kong : Chinese University of Hong Kong, 1998. http://www.cse.cuhk.edu.hk/%7Ekdd/assoc%5Frule/thesis%5Fchcai.pdf.

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Thesis (M. Phil.)--Chinese University of Hong Kong, 1998.<br>Description based on contents viewed Mar. 13, 2007; title from title screen. Includes bibliographical references (p. 99-103). Also available in print.
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Li, XuQin. "Data mining using intelligent systems : an optimized weighted fuzzy decision tree approach." Thesis, University of Warwick, 2010. http://wrap.warwick.ac.uk/38159/.

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Data mining can be said to have the aim to analyze the observational datasets to find relationships and to present the data in ways that are both understandable and useful. In this thesis, some existing intelligent systems techniques such as Self-Organizing Map, Fuzzy C-means and decision tree are used to analyze several datasets. The techniques are used to provide flexible information processing capability for handling real-life situations. This thesis is concerned with the design, implementation, testing and application of these techniques to those datasets. The thesis also introduces a hybr
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Kishk, Mohammed El-Said. "An integrated fuzzy approach to whole life costing based decision making." Thesis, Robert Gordon University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369051.

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Tang, Zongpei. "Selecting Optimal Residential Locations Using Fuzzy GIS Modeling." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5396/.

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Integrating decision analytical techniques in geographic information systems (GIS) can help remove the two primary obstacles in spatial decision making: inaccessibility to required geographic data and difficulties in synthesizing various criteria. I developed a GIS model to assist people seeking optimal residential locations. Fuzzy set theory was used to codify criteria for each factor used in evaluating residential locations, and weighted linear combination (WLC) was employed to simulate users' preferences in decision making. Three examples were used to demonstrate the applications in the stu
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Cunningham, Joanne Marie. "A Comparison of Methods to Construct an Optimal Membership Function in a Fuzzy Database System." VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/877.

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A fuzzy set is one in which membership in a category is not Boolean, rather items have a degree of membership. Fuzzy databases expand on this idea by storing fuzzy data and allowing data to be retrieved based on its degree of membership. Determining the degree of membership that satisfies the largest number of users is difficult. Five different methods of determining the membership function: the Direct Rating Method, the Random Method with step sizes of .02 and .03, the Steplock Method, and the Weighted Average Method, were compared on the basis of convergence and user satisfaction. The re
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Dixon, Walter L. "The Geometric Mean as a Generator of Truth-Value in Heuristic Expert Systems: An Improvement over the Fuzzy Weighted Arithmetic Mean." NSUWorks, 2002. http://nsuworks.nova.edu/gscis_etd/489.

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Many earlier expert systems that were modeled after MYCIN, the first expert system, employed truth-value factors for their rule antecedents (premises) and consequents (conclusions). These crisp truth-value factors were usually called certainty factors and attempted to provide a measure of confidence and computational capability to the analysis of rule uncertainty (Shortliffe, 1977; Kandel, 1994). However, in the literature criticism has been often expressed concerning the lack of precision a crisp truth/certainty factor value conveys (Zadeh, 1983; Turban, 1993). Zadeh (1973) and Xingui (1988)
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Gedda, Magnus. "Contributions to 3D Image Analysis using Discrete Methods and Fuzzy Techniques : With Focus on Images from Cryo-Electron Tomography." Doctoral thesis, Uppsala universitet, Centrum för bildanalys, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121579.

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With the emergence of new imaging techniques, researchers are always eager to push the boundaries by examining objects either smaller or further away than what was previously possible. The development of image analysis techniques has greatly helped to introduce objectivity and coherence in measurements and decision making. It has become an essential tool for facilitating both large-scale quantitative studies and qualitative research. In this Thesis, methods were developed for analysis of low-resolution (in respect to the size of the imaged objects) three-dimensional (3D) images with low signal
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Demircioglu, Ersan. "A Novel Refinement Method For Automatic Image Annotation Systems." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613346/index.pdf.

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Image annotation could be defined as the process of assigning a set of content related words to the image. An automatic image annotation system constructs the relationship between words and low level visual descriptors, which are extracted from images and by using these relationships annotates a newly seen image. The high demand on image annotation requirement increases the need to automatic image annotation systems. However, performances of current annotation methods are far from practical usage. The most common problem of current methods is the gap between semantic words and low level visual
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Kabnurkar, Amit. "Mathematical Modeling for Data Envelopment Analysis with Fuzzy Restrictions on Weights." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/31992.

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Data envelopment analysis (DEA) is a relative technical efficiency measurement tool, which uses operations research techniques to automatically calculate the weights assigned to the inputs and outputs of the production units being assessed. The actual input/output data values are then multiplied with the calculated weights to determine the efficiency scores. Recent variants of the DEA model impose upper and lower bounds on the weights to eliminate certain drawbacks associated with unrestricted weights. These variants are called weight restriction DEA models. Most weight restriction DEA models
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Chao, Chien-Shiung, and 趙建雄. "Weighted Fuzzy-PID Controllers." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/59758698469808879581.

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碩士<br>國立中央大學<br>電機工程研究所<br>92<br>This thesis investigates the technique of the weighted fuzzy-PID controllers by means of genetic algorithms. First, we propose a weighted function to tune the weights of the system error into the fuzzy controller. Then, output of the fuzzy controller is transmitted into a PID controller to control plant. The controllers can stabilize a process with a minimal amount of prior knowledge and improve rise time, settling time and overshoot effectively. Some illustrative examples demonstrate that satisfactory performance is achieved. By means of genetic algorithms, th
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Ensafi, Pegah. "Weighted Opposition-Based Fuzzy Thresholding." Thesis, 2011. http://hdl.handle.net/10012/5796.

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With the rapid growth of the digital imaging, image processing techniques are widely involved in many industrial and medical applications. Image thresholding plays an essential role in image processing and computer vision applications. It has a vast domain of usage. Areas such document image analysis, scene or map processing, satellite imaging and material inspection in quality control tasks are examples of applications that employ image thresholding or segmentation to extract useful information from images. Medical image processing is another area that has extensively used image threshold
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Tian, Yi-Cheng, and 田益誠. "Cluster-Weighted Fuzzy Clustering Algorithms." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/66377500446890557129.

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博士<br>中原大學<br>應用數學研究所<br>103<br>Fuzzy clustering is generally extended from hard clustering based on fuzzy membership partitions. In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the most well-known clustering method. Up to now, there are various generalizations of FCM. However, the FCM algorithm and its generalizations are always affected by initializations. In this paper, we consider a cluster-weighted term with an updating equation to adjust the effects of initializations to fuzzy clustering algorithms. We first propose the so-called cluster-weighted fuzzy clustering of the general
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Jeng, Ya-Ju, and 鄭亞竹. "Attribute-Weighted fuzzy clustering methods." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/54336872793242199475.

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碩士<br>中原大學<br>應用數學研究所<br>95<br>Since Zadeh proposed fuzzy set theory, fuzzy clustering has been widely studied and applied in a variety of substantive areas. The clustering applications in various areas such as taxonomy, feature analysis, image processing, medicine, neural networks, geology, engineering systems and business, etc. Fuzzy c-means (FCM) are extensions of hard c-means (HCM). FCM has been become the most well-known and powerful method in cluster analysis. In the fuzzy clustering literature, the fuzzy c-means algorithm first proposed by Dunn and then generalized by Bezdek is one of t
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CHIANG, PING-HUNG, and 蔣秉翃. "Fuzzy Utility Mining with Weighted Items." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/zxb2qh.

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Chen, Yi-Chih, and 陳一志. "The Study of Fuzzy Connective Problem in Fuzzy Weighted Average." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/57633212019808790393.

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碩士<br>元智大學<br>工業工程研究所<br>87<br>Because of the decision making condition is usually not defined and the decision making process also contains many uncertainties. So the performance evaluation always carries out in different risk condition. It correlates evaluative value is different from the traditional performance evaluation expressed by certain evaluative value. It utilizes uncertain interval value instead of crisp number. Although Fuzzy Weighted Average (FWA) has already improved the defect of the traditional performance evaluation. But FWA assumes the connective between weighted rating is l
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Hung, Kuo-Chen, and 洪國禎. "alpha Cut Fuzzy Arithmetic Simplifying Rules, Fuzzy Weighted Average and Fuzzy Function Optimization." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/36542834489043779403.

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博士<br>東海大學<br>工業工程與經營資訊學系<br>94<br>The fuzzy theory has been used to solve various problems in management science and engineering. Hence, it becomes important to use fuzzy arithmetic operations. The main purpose of this dissertation is to investigate the procedures of fuzzy arithmetic operation. Furthermore, it provides simplifying rules of fuzzy arithmetic to save required time of arithmetic operation efficiently. We divided this article into three parts to investigate: simplifying rules, fuzzy weighted average (FWA) and fuzzy function optimization. First, the problems of Alpha-cut fuzzy arit
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"Mining association rules with weighted items." 1998. http://library.cuhk.edu.hk/record=b5889513.

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by Cai, Chun Hing.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.<br>Includes bibliographical references (leaves 109-114).<br>Abstract also in Chinese.<br>Acknowledgments --- p.ii<br>Abstract --- p.iii<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Main Categories in Data Mining --- p.1<br>Chapter 1.2 --- Motivation --- p.3<br>Chapter 1.3 --- Problem Definition --- p.4<br>Chapter 1.4 --- Experimental Setup --- p.5<br>Chapter 1.5 --- Outline of the thesis --- p.6<br>Chapter 2 --- Literature Survey on Data Mining --- p.8<br>Chapter 2.1 --- Statistical Approach ---
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You, Shan Han, and 游善涵. "An nonparametric Fuzzy Relative Weight Exponentially Weighted Moving Average control chart design." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/hxrgq2.

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Lin, Hao-Lin, and 林皓琳. "Generating Weighted Fuzzy Rules from Training Data for Handling Fuzzy Classification Problems." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/22523933145504773247.

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碩士<br>國立臺灣科技大學<br>電子工程系<br>89<br>In recent years, many methods have been proposed to generate fuzzy rules from training data. In this thesis, we present a new algorithm (FRG) to generate weighted fuzzy rules from a set of training data, where the attributes appearing in the antecedent parts of the generated fuzzy rules may have different weights. We apply the generated weighted fuzzy rules to deal with the “Saturday Morning Problem”, where the proposed FRG algorithm can get a higher average classification accuracy rate and generate less fuzzy rules than the existing methods. Then, based on the
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Huang, Yu-Jie, and 黃煜傑. "Multivariate High-Order Weighted Fuzzy Time Series Based on Fuzzy Neural Networks." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/33520562389555656153.

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碩士<br>朝陽科技大學<br>資訊管理系碩士班<br>100<br>There are many uncertainty problems in the Human society, such as the forecasting of economic growth rate, financial crisis, etc. Since Song and Chissom proposed the concept of fuzzy time series in 1993, many scholars have proposed different models to deal with these problems. However, previous studies usually do not consider the factor selection and transfer original data to the fuzzy linguistic value by the subjective opinions in fuzzy process, which cannot objectively show the characteristics of the data. In addition, the fuzzy rules usually assign equal
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Jou, Iu-ru, and 周育如. "Exchange Rate Forecasting Using Weighted Fuzzy Time Series." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/94jbeb.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>95<br>Due to the liberalization of the financial market and the diminishment of the government’s intervention on the foreign exchange market, we have witnessed severe fluctuations of the exchange rates of the NT Dollars against different foreign currencies. Since the exchange rates of the NT Dollars against other foreign currencies have significant effects on the international trade of Taiwan, how to forecast the exchange rate variations becomes an important issue for Taiwan. If the government, an enterprise or an individual can accurately predict the exchange rate v
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Kau, Chin-Fong, and 高群峰. "Weighted Fuzzy Linear Programming in Multiobjectives Transportation Problem." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/83206871394061981451.

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Adam, Stenly Ibrahim, and Stenly Ibrahim Adam. "New Methods for Weighted Fuzzy Interpolated Reasoning and Adaptive Fuzzy Interpolation for Sparse Fuzzy Rule-Based Systems." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/76982182357165874513.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>105<br>Fuzzy interpolative reasoning is a very important research topic in sparse fuzzy rule-based systems. In this thesis, we propose two new fuzzy interpolative reasoning methods for sparse fuzzy rule-based systems. In the first method, we propose a new transformation-based weighted fuzzy interpolative reasoning method based on the ranking values of polygonal fuzzy sets and the proposed scale and move transformation techniques. The proposed weighted fuzzy interpolative reasoning method is based on the multiple fuzzy rules and multiple antecedent variables fuzzy int
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鄭淙仁. "Forecasting Taiwan Weighted Stock Index with Fuzzy Time Series." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/81625593557966548327.

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碩士<br>國立海洋大學<br>航運管理學系碩士在職專班<br>90<br>This study contributes to forecast Taiwan Weighted Stock Index with fuzzy time series. In consideration about applying some traditional time series model to forecast is so much on complicated computation even if it is well accomplished by the electronic computers. It is a hard job to do so. However, forecasting with fuzzy time series model is easier and simpler in mathematical operation and the result keeps better. Therefore, it is worthy to promote this way for forecasting. In 1996, Chen proposed a new simplified fuzzy time series model that co
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Ma, Yen-Ting, and 馬嬿婷. "Sample and cluster weighted fuzzy c-means clustering algorithms." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/tpkev7.

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碩士<br>中原大學<br>應用數學研究所<br>102<br>In fuzzy cluster analysis﹐the fuzzy c-means (FCM) clustering algorithm is the most well-known and used method. Up to now﹐there are various generalizations of FCM. In order to reduce the influences of the clustering results by outliers and noisy points﹐Yu, Yang and Lee (2011) proposed sample-weighted clustering methods that apply the maximum entropy principle to automatically calculate these sample weights so as to increase the robustness of the algorithm. The purpose of this thesis is to give a cluster-weighted version of sample-weighted FCM﹐called the sample an
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Chiang, Chen-Han, and 江承翰. "Trend weighted fuzzy time series model for TAIEX forecasting." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/52122715375400620133.

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碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>94<br>Trend forecasting plays an important role in decision making, and time series models are usually used to forecast future trend. Throughout the years, there have been various fuzzy methods proposed to solve traditional time series problems. Song and Chissom (1993a) defined fuzzy time series and proposed their methods to model fuzzy relationships among observations. On the other hand, different fuzzy time-series models have been proposed for various domain problems, such as enrollment forecasting, temperature forecasting the stock index forecasting, etc. It is
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Huang, Wen-Chun, and 黃文俊. "A Novel Fuzzy Weighted C-Means Method for Classification." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/93482846165969876602.

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碩士<br>國立臺中教育大學<br>教育測驗統計研究所<br>97<br>Many researches show the fuzzy c-means clustering is a powerful tool for partitioning samples into different categories. However, the cost function of the classical fuzzy c-means (FCM) is defined by the distances from data to the cluster centers with their fuzzy memberships. In this study, a new fuzzy clustering algorithm, namely the fuzzy weighted c-means (FWCM), is proposed. In this proposed FWCM, the concept of weighted means used in nonparametric weighted feature extraction (NWFE) is employed for replacing the cluster centers in the FCM. The experiments
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Pan, Yi-Shan, and 潘儀珊. "A Study on Sample-Weighted Fuzzy Clustering with Regularizations." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/13195164117420389424.

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碩士<br>中原大學<br>應用數學研究所<br>100<br>Abstract In fuzzy cluster analysis, the fuzzy c-means (FCM) clustering algorithm is the most well-known and used method. Up to date, there have been many researches on generalized types of FCM. In 2007, Yu and Yang [25] proposed a generalized fuzzy clustering regularization (GFCR) that adding a regularization with membership functions on an objective function. Besides, some authors tried to solve the affects of the clustering results by outliers and noises. Recently, Yu et al. [4] proposed sample-weighted clustering methods that apply the maximum entropy pri
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Barman, Dipto, and Dipto Barman. "Adaptive Fuzzy Interpolative Reasoning Based on Polygonal Fuzzy Sets and Adaptive Weighted Fuzzy Interpolative Reasoning Based on Interval Type-2 Fuzzy Sets." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/kj8gm2.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>107<br>Fuzzy interpolative reasoning is a very important research topic for sparse fuzzy rule-based systems. In this thesis, we propose two new adaptive fuzzy interpolative reasoning methods for sparse fuzzy rule-based systems based on polygonal fuzzy sets and interval type-2 fuzzy sets, respectively. In the first method of our thesis, we propose a new adaptive fuzzy interpolative reasoning method based on contradiction measures between polygonal fuzzy sets and novel move and transformation techniques. The proposed adaptive fuzzy interpolative reasoning method perfor
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Yeh, Fang-Yu, and 葉芳宇. "Multiple Weighted-Based K-Nearest Neighbor Fusion Using Fuzzy Integral." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/5ffp24.

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碩士<br>朝陽科技大學<br>資訊工程系碩士班<br>96<br>This thesis presents a novel method for combining multiple weighted-based K-nearest neighbor (W-KNN) using fuzzy integral. The fusion of multiple classifiers can overcome the limitations of a single classifier since the classifiers complement each other. A fuzzy integral is a better combination scheme than majority voting method that uses the subjectively defined relevance of classifiers. A combination of multiple W-KNN classifiers with fuzzy integral (FI) is proposed to achieve data classification with higher accuracy than existing traditional methods. We fir
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Liu, Yu-Ting, and 劉宇庭. "Weighted Fuzzy Dempster-Shafer Framework for Multi-Modal Information Integration." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/z9rtbh.

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Hsiao, Ying-Chuan, and 蕭瑩銓. "On the Optimal Design of Fuzzy Weighted Order Statistic Filtering." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/61180538970710298218.

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碩士<br>國立中正大學<br>資訊工程研究所<br>83<br>In this thesis, a new fuzzy filter, called fuzzy weighted order statistic filter (FWOS filter) is proposed to extend the filtering capability of conventional weighted order statistic filter (WOS filter). It is based on the threshold logic with a corresponding positive Boolean function (PBF) as its window operator. A new kind of fuzzy positive Boolean function (FPBF) is proposed to fuzzify a conventional wos filter to become more flexible. Also, the new defined FPBF is associated with a set of control parameters which are adjustable. 　　Since some control paramet
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LU, YAN-LONG, and 呂彥龍. "The use of weighted fuzzy sets in rock mass classification." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/12071716026897141752.

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Santiwatthana, Charindech, and 陳正德. "Project Manager Performance Evaluation Using a Fuzzy Weighted Average Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/51319160136693163431.

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碩士<br>南台科技大學<br>企業管理系<br>98<br>Naturally, project managers are responsible for making the project finish on time, on budget, thus they always be evaluated on the same perspective. But due to the different content of each project, this could be inappropriate to judge their performance form the project performance. Compare to the traditional studies, the proposed model developed under the more multi-dimensional perspective, the schedule basis cannot stand alone without the qualitative perspective. The qualitative perspective such as attitude or some specific behavior much is taken in to account
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Lin, Kun-ye, and 林坤燁. "Weighted (ƒ,g)-Trapezoidal Approximation Preserving Cores of Fuzzy Numbers." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/23709427913752060241.

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碩士<br>國立臺南大學<br>應用數學研究所碩士班<br>99<br>Trapezoidal approximation and triangular approximation have been researched by most scholars in recently years. In 2010, Abbasbandy and Hajjari provided weighted trapezoidal approximation preserving cores of a fuzzy number. They proved that the weighted trapezoidal approximation-preserving core is always a fuzzy number. In this paper, we propose another approach. We use weighted (ƒ,g)-trapezoidal approximation fuzzy number to approximate a fuzzy number, which preserves its core.
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Peng, Yu-Bin, and 彭玉彬. "An Adaptive Weighted Fuzzy C-means Algorithm for Brain MRI Segmentation." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/ea29xx.

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碩士<br>國立交通大學<br>電控工程研究所<br>103<br>Magnetic Resonance Imaging is safe and non-radiation. There is good contrast in MRI. Therefore, it plays a very important role in the medical diagnosis. There are many ununiform noise in medical images. Thus the quality of images are poor. The noise in images interfere the determine of doctor cause doctor is inconvenient. The image segmentation is to segment the tissue of brain by suppress the influence of noise. We gain the image which is clearly and visible to help doctor to diagnose. This paper have proposed an algorithm which is low-interference with n
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Lee, Ya-ting, and 李雅婷. "Multiple Periods Weighted Fuzzy Rules Time Series for Forecasting Gold Price." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/79311399067116117884.

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碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>94<br>Forecasting activities are frequent and widespread in our life. The traditional time series methods can predict future problems based on historical data, but fail to deal with the problem with linguistic historical data. Therefore, Song and Chissom (1993) proposed the fuzzy time series to solve the problem of the traditional time series methods. So far, many previous studies have proposed variant fuzzy time series models to deal with uncertain and vague data. A drawback of these models is that they do not consider appropriately the weights of fuzzy relations
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Liang, Ching-Ping, and 梁景評. "Intron Identification Approaches Based on Weighted Features and Fuzzy Decision Trees." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/76985012014632543838.

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碩士<br>國立雲林科技大學<br>資訊工程研究所<br>97<br>Current computational predictions of splice sites largely depend on the sequence patterns of known intronic sequence features (ISFs) described in the classical intron definition model (IDM). The computation-oriented IDM (CO-IDM) clearly provides more specific and concrete information for describing intron flanks of splice sites (IFSSs). In the thesis, we proposed a novel approach of fuzzy decision trees (FDTs) which utilize 1) weighted ISFs of twelve uni-frame patterns (UFPs) and forty-five multi-frame patterns (MFPs) and 2) gain ratios to improve the perform
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Liu, Chung-Chi, and 劉仲琦. "High-Order Weighted Fuzzy Time Series Based on Different Discretization Approach." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/20646934805818173430.

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碩士<br>朝陽科技大學<br>資訊管理系碩士班<br>101<br>There are many uncertainty problems in the Human society, such as the forecasting of economic growth rate, financial crisis, etc. Since Song and Chissom proposed the concept of fuzzy time series in 1993, many scholars have proposed different models to deal with these problems. However, previous studies usually did not consider the transfer original data to the fuzzy linguistic value by the subjective opinions in fuzzy process, which cannot objectively show the characteristics of the data. Based on above concepts, the purpose of this study is to explore ways o
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Han, Wen-Hsin, and 韓文欣. "Fuzzy Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Values, Interval-Valued Intuitionistic Fuzzy Weighted Averaging Operator, and Nonlinear Programming Methodology." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/y8vcyj.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>106<br>In this thesis, we propose a new fuzzy multiattribute decision making method based on interval-valued intuitionistic fuzzy values, the interval-valued intuitionistic fuzzy weighted averaging operator, and the nonlinear programming methodology. Firstly, the proposed method calculates the largest ranges of interval-valued intuitionistic fuzzy weights of attributes and modifies unreasonable ranges of interval-valued intuitionistic fuzzy weights. Then, it gets the transformed decision matrix based on the score function of interval-valued intuitionistic fuzzy value
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Wu, Jerry Chun-Teh, and 吳俊德. "A Comparison Study between Weighted and Fuzzy Algorithm on Organizational Performance Assessment." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/e63tax.

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博士<br>國立中山大學<br>企業管理學系研究所<br>96<br>Nowadays, the administration environment is changing rapidly. Since International Institute for Management Development（IMD）selects “government efficiency” and “business efficiency” as the major factors and criteria to compute the rankings of world competitiveness in the World Competitiveness Yearbook. Both governments and enterprises force to innovate and need to strengthen organizational performance to promote work efficiency, and to improve the strategic management system. This research applies the organizational performance theme in public institutions as
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hung, Guo-Chih, and 洪國智. "Construct A Weighted Evolving Fuzzy Neural Network For PCB Sales Forecasting Problem." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/52948508168697789773.

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碩士<br>元智大學<br>工業工程與管理學系<br>93<br>Printed Circuit Board (PCB) brings a bright and considerable economic contribution to our country every year. Businessmen keep expanding the capacity; however, they cannot keep up with the fast change of demands. Consequently, it causes the imbalance of the supply and demand and it is common to have the problems of severe inventory stacking and material-lacking. Therefore, through an set of accurate production-forecasting model, it can provide a trend of demands in the near future to reach the following material-preparation and production-schedule, etc. It can
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Chiu, Tzu-i., and 邱紫怡. "Stock Investment Strategy Portfolio using Genetic Algorithms and Weighted Fuzzy Time Series." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/kpkf2p.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>99<br>Investments in a financial market may incur risk. To reduce the risk in an investment, many portfolio selection methods have been introduced. By buying a set of financial assets, portfolio selection aims at maximizing the return of the investment for a given level of risk. To build an optimal portfolio, one needs to select proper assets and to decide the proportion of the investment for each selected asset. On the other hand, prices of assets vary as time goes by. As a result, the return of the portfolio is also varies with time. Thus, besides the portfolio
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Hsu, Jui-hua, and 許睿華. "Stock trading point prediction using Technical Indicators and Weighted Fuzzy Time Series." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/z59mu7.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>100<br>Investments in a financial market may incur risk. According to the Capital Asset Pricing Model (CAPM), a stock with higher return rate usually exhibits higher risk. The risk of a stock is expressed in terms of the volatility of the stock price. Traditionally, the investors often use the technical analysis to determine the time points for stock transactions. This study is mainly based on the technical indicators and the weighted fuzzy time series. Borrowing the idea from the ensemble algorithms, we calculate the accuracy rate of the historical predictions of e
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Li, Chen-Hsun, and 李承勳. "Fuzzy Time Series based on weighted-transitional matrix for forecasting outpatient visits." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/04333506944218438540.

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碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>94<br>It is obvious that forecasting activities play an important role in our daily life. Traditional time series methods can predict the trend problem, but fail to forecast the problems with linguistic historical data. Furthermore, traditional time series method requires more history data and the data must be normal distribution to get a better forecasting performance. To deal with these kinds of problems, fuzzy time series is proposed. There are still existed a drawback which can be detected: In the world of fuzzy time series, the view always focus on obvio
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Chen, Man-Hua, and 陳蔓樺. "An Application of Fuzzy-weighted Bootstrap Estimation Method in Semi-parametric Model." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/75440943705862168431.

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碩士<br>淡江大學<br>統計學系<br>88<br>When the semi-parametric model contains outliers, the bootstrap estimation method and the optimal fuzzy clustering analysis method are combined to generate a fuzzy-weighted bootstrap estimation method. The new estimation method was proposed by Tsai(1999) and it can reduce the influence of outliers efficiently. When the sample size of data set is not very large, the proposed method of Tsai(1999) is more reasonable than the proposed test by Wu et al.(1996). In this paper, some simulations are provided to demonstrate the application of the fuzzy-weighted bootstrap esti
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Roy, Andreas Franskie Van, and AndreasFranskieVanRoy. "Evolutionary Fuzzy Decision Model for Construction Management using Weighted Support Vector Machine." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/88562275650834329958.

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博士<br>國立臺灣科技大學<br>營建工程系<br>98<br>Construction projects are, by their very nature, challenging; and project decision makers must work successfully within an environment that is frequently complex and fraught with uncertainty. As many decisions must be made intuitively based on limited information, successful decision making depends heavily on two factors, including the experience of the expert(s) involved and the quality of knowledge accumulated from previous experience. Knowledge, however, is subject to various factors that cause its value and accuracy to deteriorate. Research has demonstrated
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Chen, Wei-Han, and 陳韋翰. "Using Generalized Fuzzy Weighted Mean Aggregation in Impulse Noise Removal of Images." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/67273500132487858428.

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碩士<br>國立交通大學<br>電控工程研究所<br>103<br>In this thesis, we have porposed weighted mean aggregation to construct interval-valued fuzzy relation for grayscale and color images noise detection. In the beginning, we employ two weighting parameters, and perform the weighted mean aggregation for the central pixel and its eight neighbor pixels in a sliding window across the image to lead to the fuzzy images. In the end, the image noise map is obtained through a suitable thresholding. Moreover, to decrease the noisy and un-contaminated pixel detection error, we have derived the iterative learning mechanism
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Amornnikun, Patipharn, and Patipharn Amornnikun. "Metaheuristic-Based Possibilistic Multivariate Fuzzy Weighted C-Means Algorithms for Market Segmentation." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/swmwcm.

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Che-Chung, Lin. "Weighted-Least-Square Method for GPS Positioning Using Genetic-Algorithms-Optimized Fuzzy Controller." 2005. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-2007200522224300.

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