Дисертації з теми "Ruleset generation"
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Haq, Ikram. "Fraud detection for online banking for scalable and distributed data." Thesis, Federation University Australia, 2020. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171977.
Повний текст джерелаDoctor of Philosophy
Gundavarapu, Madhavi. "RuleGen – A Rule Generation Application Using Multiset Decision Tables." University of Akron / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=akron1140111266.
Повний текст джерелаKoh, Yun Sing, and n/a. "Generating sporadic association rules." University of Otago. Department of Computer Science, 2007. http://adt.otago.ac.nz./public/adt-NZDU20070711.115758.
Повний текст джерелаMa, Liangjun, and Shouchuan Zhang. "Generating Fuzzy Rules For Case-based Classification." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16444.
Повний текст джерелаJohnson, Christopher Wayne Bagai Rajiv. "Mechanical generation of concrete syntax rules for the Schütz semantic editor." Diss., A link to full text of this thesis in SOAR, 2007. http://soar.wichita.edu/dspace/handle/10057/1141.
Повний текст джерела"May 2007." Title from PDF title page (viewed on Dec. 26, 2007). Thesis adviser: Rajiv Bagai. Includes bibliographical references (65-66 leaves).
Powell, Anastasia. "Generation Y : re-writing the rules on sex,love and consent /." Connect to thesis, 2007. http://eprints.unimelb.edu.au/archive/00004035.
Повний текст джерелаFry, John, T. Galla, and J. M. Binner. "Quantitative decision-making rules for the next generation of smarter evacuations." Springer, 2015. http://hdl.handle.net/10454/17563.
Повний текст джерелаHall, A. R. "Automatic speech recognition using morpheme structure rules for word hypothesis and dictionary generation." Thesis, London South Bank University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.352963.
Повний текст джерелаBakshi, Arjun. "Methodology For Generating High-Confidence Cost-Sensitive Rules For Classification." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377868085.
Повний текст джерелаKuri, Bless. "Sustainable generation mix as a reference in effective design of electricity market structures and rules." Thesis, University of Bath, 2006. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440360.
Повний текст джерелаJohnston, Cristin D. "Observation training evaluating a procedure for generating self-rules in the absence of reinforcement /." abstract and full text PDF (UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3316373.
Повний текст джерелаPetersen, Henry. "Generating High Precision Classification Rules for Screening of Irrelevant Studies in Systematic Review Literature Searches." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/15454.
Повний текст джерелаMorak, Michael. "The impact of disjunction on reasoning under existential rules." Thesis, University of Oxford, 2014. https://ora.ox.ac.uk/objects/uuid:b8f012c4-0210-41f6-a0d3-a9d1ea5f8fac.
Повний текст джерелаAlbhbah, Atia Mahmod. "Dynamic web forms development using RuleML : building a framework using metadata driven rules to control Web forms generation and appearance." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/5719.
Повний текст джерелаAlbhbah, Atia M. "Dynamic web forms development using RuleML. Building a framework using metadata driven rules to control Web forms generation and appearance." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/5719.
Повний текст джерелаAdemi, Muhamet. "adXtractor – Automated and Adaptive Generation of Wrappers for Information Retrieval." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20071.
Повний текст джерелаHonorato-Zimmer, Ricardo. "On a thermodynamic approach to biomolecular interaction networks." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28904.
Повний текст джерелаMasachis, Gelo Sara. "When mRNA folding rules gene expression : lessons from type I toxin-antitoxin systems." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0191/document.
Повний текст джерелаToxin-antitoxin (TA) systems are small genetic modules widely present in bacterial genomes. They usually code for a small toxic protein and its cognate antitoxin and can be classified into six types depending on the nature and mode of action of the antitoxin. This work focuses on the study of type I, for which the antitoxin is an antisense RNA that targets the toxin mRNA to inhibit its expression. We characterized the aapA3/IsoA3 system, encoded on the chromosome of the human gastric pathogen Helicobacter pylori. To date, most TAs have been studied using artificial expression systems, which do not allow the characterization of transcriptional or post-transcriptional regulation. Taking advantage of the lethality induced by the toxin chromosomal expression in the absence of antitoxin, we developed a high-throughput genetic selection of suppressor mutations revealed by Next-Generation Sequencing. This approach, named FASTBAC-Seq, allowed us to map a myriad of toxicity determinants located in both, coding and noncoding regions, of the aapA3 toxic gene. More precisely, some suppressor mutations revealed the existence of transient RNA hairpins that act co-transcriptionally to prevent translation initiation while the toxinencoding mRNA is being made. Such functional RNA metastable structures are essential to uncouple the transcription and translation processes and allow the presence of these toxic genes on bacterial chromosomes. Although untranslated mRNAs become rapidly unstable, our work also revealed the presence of two protective stem-loops located at both mRNA ends that prevent from both, 5’ and 3’ exonucleolytic activity. Altogether, our work evidenced the consequences of the strong selection pressure to silence toxin expression under which the TAs evolve, and highlighted the key role of mRNA folding in the co- and post-transcriptional regulation of this family of genes. These RNA-based regulatory mechanisms may be exploited in the future for biotechnological (e.g., increased protein production through mRNA stabilization) or biomedical (e.g., development of alternative antimicrobial strategies aiming at the activation of toxin synthesis) applications
Geležis, Jonas. "Programinio kodo generavimo iš grafinių veiklos taisyklių modelių galimybių tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090831_153530-40477.
Повний текст джерелаOne of the reasons for a relatively slow growth of the business rules approach could be the lack of developments in the field of program code generation from the business rules models. During this work methods for code generation from IS requirements models are analysed. The focus is placed on a modified Ross method based rules modelling method aiming to create an adequate code generation methodology.
Dymock, Yosabeth. "Vi behandlar andra så som vi själva vill bli behandlade : En studie om att undersöka och problematisera regler inom fritidshemmet utifrån generationsmaktordningen." Thesis, Södertörns högskola, Lärarutbildningen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-32590.
Повний текст джерелаThe purpose of this study has been to explore and problematize how rules affect the superiority educators have in relation to pupils, based on the generation power structure. As a basis for the result are qualitative observations from three recreation centers and qualitative interviews with four educators from these. The empirical material is analyzed with the help of social constructivism and a childish perspective. These theories are based on the assumption that we socially construct our reality as well as to see injustices and subordination based on an age and power perspective. The results show that the recreation centre is a complex arena where pupils are expected to navigate between rules that are visible, invisible, changeable and difficult to interpret. It also shows that rules are made visible through reprimands that take place in different situations and in different ways. During the interviews, pupils resistance to rules is described, but is not entirely unproblematic because of the way educators interpret the resistance and value it. One conclusion is that rules, how they are created and how they are maintained reinforce the superiority educators have in a partially unjustified manner. But that this is something that can be challenged and renegotiated.
Mayer, Rosirene. "A linguagem de Oscar Niemeyer." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2003. http://hdl.handle.net/10183/6693.
Повний текст джерелаThis work aims at describing the elements that characterize Oscar Niemeyer’s singular architectural language. It argues that the identification of these elements passes for the scrutiny of non-visible aspects of his work. The identification was possible taking into consideration from the analysis of buildings characterized for curved profile and the construction of a model that associates the compositional elements utilized by Niemeyer to a Shape Grammar. The utilization of the model made it possible to reveal the generative principles - set of rules, vocabulary and geometric relations - that characterize Niemeyer’s style and architectural language. It also helped showing how Niemeyer’s language associates, in an original way, operations of transformation such as rotation, reflection, and translation to a vocabulary of curves. The association has its parameters on a drawn line which acts as a regulator based on the golden section. As its conclusion, the work suggests possibilities of development of this grammar for all the forms utilized by Niemeyer and the aplication of generative principles in the teaching of architecture.
D’Agnese, Daniele. "Strumenti per la generazione automatica di documentazione di profili d’uso di linguaggi standard basati su Core Components." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/2702/.
Повний текст джерелаLopes, Priscilla de Abreu. "Agrupamento de dados semissupervisionado na geração de regras fuzzy." Universidade Federal de São Carlos, 2010. https://repositorio.ufscar.br/handle/ufscar/7061.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Inductive learning is, traditionally, categorized as supervised and unsupervised. In supervised learning, the learning method is given a labeled data set (classes of data are known). Those data sets are adequate for problems of classification and regression. In unsupervised learning, unlabeled data are analyzed in order to identify structures embedded in data sets. Typically, clustering methods do not make use of previous knowledge, such as classes labels, to execute their job. The characteristics of recently acquired data sets, great volume and mixed attribute structures, contribute to research on better solutions for machine learning jobs. The proposed research fits into this context. It is about semi-supervised fuzzy clustering applied to the generation of sets of fuzzy rules. Semi-supervised clustering does its job by embodying some previous knowledge about the data set. The clustering results are, then, useful for labeling the remaining unlabeled data in the set. Following that, come to action the supervised learning algorithms aimed at generating fuzzy rules. This document contains theoretic concepts, that will help in understanding the research proposal, and a discussion about the context wherein is the proposal. Some experiments were set up to show that this may be an interesting solution for machine learning jobs that have encountered difficulties due to lack of available information about data.
O aprendizado indutivo é, tradicionalmente, dividido em supervisionado e não supervisionado. No aprendizado supervisionado é fornecido ao método de aprendizado um conjunto de dados rotulados (dados que tem a classe conhecida). Estes dados são adequados para problemas de classificação e regressão. No aprendizado não supervisionado são analisados dados não rotulados, com o objetivo de identificar estruturas embutidas no conjunto. Tipicamente, métodos de agrupamento não se utilizam de conhecimento prévio, como rótulos de classes, para desempenhar sua tarefa. A característica de conjuntos de dados atuais, grande volume e estruturas de atributos mistas, contribui para a busca de melhores soluções para tarefas de aprendizado de máquina. É neste contexto em que se encaixa esta proposta de pesquisa. Trata-se da aplicação de métodos de agrupamento fuzzy semi-supervisionados na geração de bases de regras fuzzy. Os métodos de agrupamento semi-supervisionados realizam sua tarefa incorporando algum conhecimento prévio a respeito do conjunto de dados. O resultado do agrupamento é, então, utilizado para rotulação do restante do conjunto. Em seguida, entram em ação algoritmos de aprendizado supervisionado que tem como objetivo gerar regras fuzzy. Este documento contém conceitos teóricos para compreensão da proposta de trabalho e uma discussão a respeito do contexto onde se encaixa a proposta. Alguns experimentos foram realizados a fim de mostrar que esta pode ser uma solução interessante para tarefas de aprendizado de máquina que encontram dificuldades devido à falta de informação disponível sobre dados.
De, Waal Elda. "The educator-learner relationship within the South African public school system :|ban educational-juridical perspective / Elda de Waal." Thesis, Potchefstroom University for Christian Higher Education, 2000. http://hdl.handle.net/10394/8616.
Повний текст джерелаThesis (Ph.D.)--Potchefstroom University for Christian Higher Education, 2000
Castro, Pablo Alberto Dalbem de. "Um paradigma baseado em algoritmos genéticos para o aprendizado de regras Fuzzy." Universidade Federal de São Carlos, 2004. https://repositorio.ufscar.br/handle/ufscar/546.
Повний текст джерелаFinanciadora de Estudos e Projetos
The construction of the knowledge base of fuzzy systems has been beneficited intensively from automatic methods that extract the necessary knowledge from data sets which represent examples of the problem. The evolutionary computation, especially genetic algorithms, has been the focus of a great number of researches that deal with the problem of automatic generation of knowledge bases as search and optimization processes using di erent approaches. This work presents a methodology to learn fuzzy rule bases from examples by means of Genetic Algorithms using the Pittsburgh approach. The methodology is composed of 2 stages. The first one is the genetic learning of rule base and the other one is the genetic optimization of the rule base previously obtained in order to exclude redundant and unnecessary rules. The first stage uses a Self Adaptive Genetic Algorithm, that changes dynamically the crossover and mutation rates ensuring genetic diversity and avoiding the premature convergence. The membership functions are defined previously by the fuzzy clustering algorithm FC-Means and remain fixed during all learning process. The application domain is multidimensional pattern classification, where the attributes and, sometimes, the class are fuzzy, so they are represented by linguistic values. The proposed methodology performance is evaluated by computational simulations on some real-world pattern classification problems. The tests focused the accuracy of generated fuzzy rules in di erent situations. The dynamic change of algorithm parameters showed that better results can be obtained and the use of don t care conditions allowed to generate a small number of comprehensible and compact rules.
A construção da base de conhecimento de sistemas fuzzy tem sido beneficiada intensamente por métodos automáticos que extraem o conhecimento necessário a partir de conjuntos de dados que representam exemplos do problema. A computação evolutiva, em particular os algoritmos genéticos, tem sido alvo de um grande número de pesquisas que tratam, usando abordagens variadas, a questão da geração automática da base de conhecimento de sistemas fuzzy como um processo de busca e otimização. Este trabalho apresenta uma metodologia para o aprendizado de bases de regras fuzzy a partir de exemplos por meio de Algoritmos Genéticos usando a abordagem Pittsburgh. A metodologia é composta por duas etapas. A primeira é a geração genética da base de regras e a segunda é a otimização genética da base de regras previamente obtida, a fim de eliminar regras redundantes e desnecessárias. A primeira etapa utiliza um algoritmo genético auto-adaptativo, que altera dinamicamente os valores das taxas de cruzamento e mutação, a fim de garantir diversidade genética na população e evitar convergência prematura. As funções de pertinência são previamente definidas pelo algoritmo de agrupamento fuzzy FC-Means e permanecem fixas durante todo o processo de aprendizado. O domínio da aplicação é a classificação de padrões multi-dimensionais, onde os atributos e, algumas vezes, as classes são fuzzy, portanto, representados por valores lingüísticos. O desempenho da metodologia proposta é avaliado por simulações computacionais em alguns problemas de classificação do mundo real. Os testes focaram a acuidade das bases de regras geradas em diferentes situações. A alteração dinâmica dos parâmetros do algoritmo mostrou que melhores resultados podem ser obtidos e o uso da condição de don t care permitiu gerar um reduzido n´umero de regras mais compreensíveis e compactas.
Pimenta, Adinovam Henriques de Macedo. "Geração genética de classificador fuzzy intervalar do tipo-2." Universidade Federal de São Carlos, 2009. https://repositorio.ufscar.br/handle/ufscar/444.
Повний текст джерелаUniversidade Federal de Sao Carlos
The objective of this work is to study, expand and evaluate the use of interval type-2 fuzzy sets in the knowledge representation for fuzzy inference systems, specifically for fuzzy classifiers, as well as its automatic generation form data sets, by means of genetic algorithms. This work investigates the use of such sets focussing the issue of balance between the cost addition in representation and the gains in interpretability and accuracy, both deriving from the representation and processing complexity of interval type-2 fuzzy sets. With this intent, an evolutionary model composed of three stages was proposed and implemented. In the first stage the rule base is generated, in the second stage the data base is optimized and finally, the number of rules of the rule base obtained is optimized in the third stage. The model developed was evaluated using several benchmark data sets and the results obtained were compared with two other fuzzy classifiers, being one of them generated by the same model using type-1 fuzzy sets and the other one generated by the Wang&Mendel method. Statistical methods usually applied for comparisons in similar contexts demonstrated a significant improvement in the classification rates of the intervalar type-2 fuzzy set classifier generated by the proposed model, with relation to the other methods.
O objetivo deste trabalho é estudar, expandir e avaliar o uso de conjuntos fuzzy intervalares tipo-2 na representação do conhecimento em sistemas de inferência fuzzy, mais especificamente para os classificadores fuzzy, bem como sua geração automática a partir de conjuntos de dados, por meio de algoritmos genéticos. Esse trabalho investiga o uso de tais conjuntos com enfoque na questão de balanceamento entre o acréscimo de custo da representação e os ganhos em interpretabilidade e precisão, ambos decorrentes da complexidade de representação e processamento dos conjuntos fuzzy intervalares do tipo-2. Com este intuito, foi proposto e implementado um modelo evolutivo composto por três etapas. Na primeira etapa á gerada a base de regras, na segunda é otimizada a base de dados e, por fim, na terceira etapa o número de regras da base gerada é otimizado. O modelo desenvolvido foi avaliado em diversos conjuntos de dados benchmark e os resultados obtidos foram comparados com outros dois classificadores fuzzy, sendo um deles gerados pelo mesmo modelo, porém, utilizando conjuntos fuzzy do tipo-1 e, o outro, gerado pelo método de Wang&Mendel. Métodos estatísticos de comparação usualmente aplicados em contextos semelhantes mostraram aumento significativo na taxa de classificação do classificador fuzzy intervalar do tipo-2 gerado pelo modelo em relação aos outros dois classificadores utilizados para comparação.
Holm, Cyril. "F. A. Hayek's Critique of Legislation." Doctoral thesis, Uppsala universitet, Juridiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-236890.
Повний текст джерелаJun-Liang, Lin Raw, and 林俊良. "Efficient Generation of Simplified Fuzzy Rules and Continuation Verification of Fuzzy Rules." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/84621614252951787323.
Повний текст джерела國立臺灣科技大學
電子工程技術研究所
86
In this thesis, we propose an efficiency fuzzy neural network system for generating simplified fuzzy rules. In the proposed fuzzy neural network system, the revision algorithms are successful in analyzing the distribution of input data andgenerating perfect simplified fuzzy rules from the concepts of the Back-Propagationand the Self-Organizing Map algorithms. These generated rules are fuzzy ruleswith constant consequences, besides, it is easy to be calculated and the computational load of its inference is not heavy. Also, the simulation of experiments show that the generation of simplified fuzzy rules is effective in the classification problems.Also, we present the concept of fuzzy rule continuation for the verification of fuzzy rule-based systems. Generally, the rules in rule-based systems might be inconsistency, such as redundant, subsumed, or conflict. The inconsistent rules will decrease the performance and cause an incorrect result for rule-based system. The concept of fuzzy rule continuation is that if fuzzy rules intersect between the antecedents of them, then the consequences of them should intersect too. That is, if these fuzzy rule-based systems are discontinuous, then they might be inconsistent systems that have some discontinuous fuzzy rules. In this thesis, this concept is applied to two examples and these simulation results show that the outputs of continuous fuzzy systems are better than these of discontinuous systems.
Hsu, Frank, and 許智豪. "Online Generation of Association Rules in Dynamic Databases." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/98474207419010644579.
Повний текст джерела劉家銘. "Online Generation of Association Rules by Negative Correlation." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/82169915037430124598.
Повний текст джерелаXu, Shi-Zhun, and 許時準. "Automatic generation of fuzzy control rules using machine learning methods." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/98859464359220870178.
Повний текст джерелаHsu, Shih-Chun, and 許時準. "Automatic Generation of Fuzzy Control Rules Using Machine Learning Methods." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/92786052098993771133.
Повний текст джерела國立臺灣大學
資訊工程研究所
82
This thesis presents a method for automatic generation of fuzzy control rules. Fuzzy control rules, which compose the the kernel of a fuzzy logic controller, represent the knowledge acquired from a human operator. In a complex environment with many input variables, the output may depend on some of the inputs. Moreover, each input may have a varying degree of influence on the output value. A good controller should focus on the important parameters while ignoring irrelevant ones. The ID3 algorithm is adopted to produce the initial estimate rules because it can select the most important input variables influencing the output. In addition to prioritizing relevant input variables, the ID3 algorithm can eliminate irrelevant inputs. The resulting decision tree from ID3 algorithm can be easily converted into IF-THEN type rules automatically. After the initial estimate rules are fuzzified, the back-propagation algorithm is adopted to tune the parameters of membership functions. Using the back-propagation algorithm have the advantage that the fuzzy rules are more adaptive even when the environment is dynamic. The proposed method can be applied to a variety of domains. In this work, nonlinear system identification and mobile robot control were used in the experiments. The experiment results were satisfactory.
Johnson, Christopher Wayne. "Mechanical generation of concrete syntax rules for the Schütz semantic editor." Thesis, 2007. http://hdl.handle.net/10057/1141.
Повний текст джерелаThesis (M.S.)--Wichita State University, College of Liberal Arts and Sciences, Dept. of Computer Science
Lin, Fu-Tyan, and 林富田. "A Fuzzy Neural Network Model for Fuzzy Rules Verification, Refinement and Generation." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/09568554229051504394.
Повний текст джерела國立臺灣科技大學
工程技術研究所
83
In this thesis, a fuzzy neural network, named Knowledge-Based Neural Network with Trapezoid Fuzzy inputs (KBNN/TFS), that processes trapezoid fuzzy inputs is proposed. In addition to fuzzy rules refinement, this model is capable of fuzzy rule verification and generation. The system architecture of the proposed model is based on our previous work, Knowledge-Based Fuzzy Neural Network (KBFNN). To facilitate the processing of fuzzy information, LR-fuzzy interval is employed. The proposed model provides an easy way for linking neural networks and fuzzy rules. Imperfect domain theories can be directly translated into KBNN/TFS structure. In KBNN/TFS, G-neurons are used to represent the output and intermediate fuzzy concepts, whereas S-neurons are used to perform the conjunction of the antecedents of fuzzy rules. Fuzzy weights are used to stand for the value of fuzzy variables. The imperfect fuzzy rules are revised by neural learning. A consistency checking algorithm is proposed for verifying the initial knowledge and the revised fuzzy rules. The algorithm is aimed at finding the redundant rules, conflicting rules and subsumed rules in fuzzy rule base.
Yang, Kung, and 楊洸. "An Approximation Reasoning Approach for Generating Fuzzy Decision Rules." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/86110227192570464543.
Повний текст джерела國立臺灣師範大學
資訊教育研究所
87
Most fuzzy classification systems proposed before applied a crisp-cut approach on the fuzzy degrees of the fuzzy attributes and conclusions to generate decision rules. Although, by the crisp-cut approach, decision rules with conjunction-disjunction form can be derived from training-samples, the membership functions of the conclusions cannot be generated. In this paper, a learning method named Fuzzy Approximation Reasoning Method is proposed. Two requirements can be satisfied by the method:(1)deriving fuzzy decision rules with conjunction-disjunction form from training-samples, and (2)generating the membership functions for the conclusions. In Fuzzy Approximation Reasoning Method, the dependency-degree function is designed for estimating the relationship between a conclusion and the fuzzy attributes. For the fuzzy attributes related to the conclusion, their membership functions will be combined to construct the membership function of the conclusion such that the associated fuzzy decision rule is derived. Moreover, the Fuzzy Approximation Reasoning Method also can be used to mine fuzzy association rules. In this paper, the Approximation Inducing Method is proposed to demonstrate how to mine fuzzy association rules by applying the Fuzzy Approximation Reasoning Method.
Chang, Chi-Hao, and 張志豪. "New Methods for Generating Fuzzy Rules from Numerical Data." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/62727720069770369894.
Повний текст джерела國立臺灣科技大學
電子工程系
89
The fuzzy classification system is an important application of the fuzzy set theory. Fuzzy classification systems can deal with perceptual uncertainties in classification problems. In order to design a fuzzy classification system, it is an important task to construct the membership function for each attribute and generate fuzzy rules from training instances for handling a specific classification problem. There are two approaches to construct the membership function for each attribute and generate fuzzy rules from training instances. One approach is based on human experts’ assistance, and the other approach is by applying machine learning techniques, such that the fuzzy classification system can construct membership functions and generate fuzzy rules from the training instances automatically. In recent years, many researchers have proposed different methods to construct membership functions and to generate fuzzy rules for handling fuzzy classification problems. However, there are some drawbacks in the existing methods: (1) Some existing methods need human experts to predefine initial membership functions, i.e., these methods can not construct membership functions from the training data set fully automatically. (2) Some existing methods are too complicated and need a lot of computation time. (3) Some existing methods generate too many fuzzy rules. In this thesis, we proposed two methods to construct the membership function for each attribute and to generate fuzzy rules automatically from training instances for handling fuzzy classification problems. The first method is based on the exclusion of attribute terms that can achieve a higher average classification accuracy rate and generate less fuzzy rules than the existing methods. The second method generates weighted fuzzy rules from training instances that can construct membership functions automatically without any human experts’ interaction and can generate less fuzzy rules than the existing methods.
Wu, Pei-Yun, and 吳珮芸. "An Efficient Generation of Candidate Itemsets and Count Algorithm for Mining Association Rules." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/39905924144178640330.
Повний текст джерела國立高雄應用科技大學
電子與資訊工程研究所碩士班
92
Mining association rules from transaction databases is one of important techniques in data mining. Applications of association rules extend to discovering frequent patterns in consumer behavior, marketing analysis, electronic commerce and education, and other areas. In this thesis, we developed EGC, is an efficient algorithm for mining association rules. The main improvements are EGC uses an innovative method for generating candidate itemsets by checking the numbers of the preceding frequent itemsets before joining procedure. And EGC uses the simple tree data structure for storing the candidate itemsets and counting their supports. In addition, EGC uses the database global pruning method of DCP for efficiently reducing the size of the database. The experiments show that the performance of EGC is better than Apriori and DHP,IHPwoTTP, and IHPwTTP. The execution time and memory required of EGC are less than Apriori, DHP, IHPwoTTP, and IHPwTTP. In other applications, EGC can efficiently mine interesting information from investor databases to provide the optimal portfolio for each investor of the brokerage securities firm.
Yung-Chou and 陳勇洲. "New Methods for Generating Fuzzy Rules for Fuzzy Classification Systems." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/59759052097981521421.
Повний текст джерела國立臺灣科技大學
電子工程系
89
The fuzzy classification system is an important application of the fuzzy set theory. The most important task to design fuzzy classification systems is to find a set of fuzzy rules from training data to deal with a specific classification problem. There are two main approaches to obtain the fuzzy rules of fuzzy classification systems. One of them is given by experts; the other is through an automatic learning process. In recent years, there are many method have been proposed to generate fuzzy rules from training instances for fuzzy classification systems. In this thesis, we proposed two new algorithms for generating fuzzy rules from training instances. We propose a new algorithm to generate weighted fuzzy rules from training data to deal with classification problems. Firstly, we convert the training data to fuzzy rules, and then we merge those fuzzy rules in order to reduce the number of fuzzy rules. Then, we calculate the weight of each input variable appearing in the generated fuzzy rules by the relationships of input variables. Then, we proposed another new algorithm to generate fuzzy rules using the genetic algorithm. Firstly, we divide the training data into several clusters and generate a fuzzy rule for each cluster. Then, we tune the membership functions of fuzzy rules by genetic algorithms. The proposed algorithms can get a higher average classification accuracy rate and generate less fuzzy rules than existing methods.
Li, Sin-Da, and 李信達. "A Bottom Up Algorithm for Mining Cross-Level Association Patterns without Redundant Rules Generation." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/65s577.
Повний текст джерела國立東華大學
資訊工程學系
95
Mining multilevel association rules is an interesting domain in data mining. However, the great parts of previous studies are devoted to mine at same level. By the way, many efficient associations will omit or the mined rules not perceive through the senses directly. Only a few works focus on mining cross level associations, and existing works still generate amount of redundant rules. In this thesis, we propose a bottom-up algorithm for mining cross-level association rules at multiple concept levels in large transaction database. Our algorithm, named ML-BottomUp, generates useful rules with high quality and none redundancy. Moreover, the similar rules are also been combined for generating efficient ones. A set of experiments is also performing to show the benefit of our approach.
Yeh, Ming-Shiow, and 葉明繡. "Generating Fuzzy Rules from Relational Database Systems for Fuzzy Information Retrieval." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/17850078135325377817.
Повний текст джерела國立交通大學
資訊科學學系
83
In this thesis, we present a fuzzy concept learning system algorithm (FCLS) to construct fuzzy decision trees from relational database systems and to generate fuzzy rules from the constructed fuzzy decision trees. The completeness of the constructed fuzzy decision tree is alsodiscussed in details. Based on the generated fuzzy rules, we also present a method to forecast null values in relational database systems. Furthermore,we also made an experiment to compare the proposed FCLS algorithm with the existing methods for analyzing the ability of approximation ofreal-valued functions. The experiment result shows that the overall result of approximation of the FCLS algorithm is better than the existing methods,especially when f(x)=x/2. Furthermore, we also present a new clustering algorithm to deal with fuzzy query processing for database systems. Theproposed algorithm is more flexible and more efficient than the existing method due to the fact that the proposed algorithm has the following good features: (1) The number of clusters does not need to be predefined. (2) The ranges of fuzzy terms can dynamically be changed. (3) It does not need to perform complicated membership function calculations. (4) The speed of fuzzy query processing can be much faster.
余筱薇. "The SCORM Sequencing Rules Generation System and Multimedia Curricular Construction Using Template Based Authoring System." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/93631764085995803291.
Повний текст джерела國立交通大學
資訊科學與工程研究所
94
In recent years, the multimedia presentation curriculums applying to teaching are getting widely available. To create interactive multimedia presentation documents, content creators such as school teachers who can use some multimedia authoring tools. However, to ensure the correctness of the multimedia presentations and interaction, teachers need to know some logic of programming. In other words, creating a multimedia curriculum requires a great deal of time and good computer literacy for teachers. Unfortunately, not every teacher has the background of programming. Undoubtedly, it is a hard job for most teachers to construct perfect multimedia curriculums. Due to the highly demand for multimedia curriculums, a wide variety of multimedia authoring tools are springing up one after another. However, multimedia curriculums made by different authoring tools have different standards, which results in reducing the interoperability of curriculums. For this reason, the American organization ADL (Advanced Distributed Learning) exerts a structured adaptive effort to develop the standards, tools and learning content for the learning environment. The standard is named SCORM (Sharable Course Object Reference Model) which provides a comprehensive suite of e-learning capabilities to enhance the interoperability, accessibility and reusability of learning content. Still, the rules of SCORM are very complex. There is a very high threshold for content creators to construct a multimedia curriculum conforming to SCORM. In this thesis, the two difficulties described above are solved. Our goals are to decrease the effort needed to create multimedia curriculums and to make the curriculums conform SCORM standard easily. Therefore, this thesis proposes the concept of "Multimedia Curriculum Template" for content creators. This topic is discussed in two main dimensions: "Multimedia Curriculum Template Construction" and "Multimedia Curriculum Template Imitating". This thesis analyzes the process of constructing multimedia curriculums, abstracts the repetition in the operation to form multimedia curriculum templates, and gives definitions of different classifications of these templates. According to the structure of multimedia curriculum, several levels of multimedia curriculum template's imitating are discussed, such as scene level, SCO level, and content organization level imitating. These different levels of templates enable content creators to compose a multimedia curriculum much more easily and efficiently. In order to reach the goal of improving the interoperability of learning content, this thesis discusses the definition of learning strategy based on SCORM sequencing rules and proposes the template of content organization and learning strategy. Without the need to know the detailed standard of SCORM, content creators will have no troubles using the templates to edit the learning strategy of multimedia curriculums and make the multimedia curriculum meet SCORM 100%.
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.
Повний текст джерела國立臺灣科技大學
電子工程系
89
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 genetic algorithm, we propose a new method consists of the FRG algorithm to tune the weights of the attributes appearing in the generated fuzzy rules for generating weighted fuzzy rules. We also apply the generated weighted fuzzy rules to deal with the Iris data classification problem. The proposed method can obtain a higher average classification accuracy rate and generate less fuzzy rules than the existing methods.
林育賢. "Auto generating fuzzy rules and membership function with evolvable hardware image filter." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/83786918209197576207.
Повний текст джерела國立高雄大學
電機工程學系碩博士班
105
Evolvable hardware (EHW), which is a combination of reconfigurable hardware and evolutionary algorithm, is an emerging research topic.Recent studies show that the integration of fuzzy theory and EHW demonstrates effectiveness on digital image filtering.However, in these studies fuzzy rules and membership functions are defined heuristically. Their performance on filtering a variety of types of image noise is limited. %% In this study, similarity and divergence of image pixels are analyzed and used for clustering.Each cluster is defined as a fuzzy classification rule.The belongingness of pixels to a cluster describes a model of fuzzy membership function in terms of similarity and divergence. %% A clustering-based incremental algorithm is developed for generating fuzzy rules and membership functions from a given set of image pixels.With each fuzzy classification rule, an EHW-based image filter is learned and used for filtering the pixels classified by the fuzzy rule.Because fuzzy rules are learned from image pixels, not defined statically, our proposed method can have better performance on processing noisy pixels with the correct circuits. %% In this study, the performance of our proposed method is compared with other ones.The experimental results show that our proposed method outperforms traditional methods on image filtering.\\
HU, DA-WEI, and 胡大偉. "A retargetable code generator using pattern-matching rules derived from peephole optimization." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/35305201659476132042.
Повний текст джерелаTsai, Fu-Ming, and 蔡富名. "New Methods for Constructing Membership Functions and Generating Fuzzy Rules from Training Instances." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/24396568981428727510.
Повний текст джерела國立臺灣科技大學
電子工程系
91
In recent years, many researchers construct fuzzy classification systems to deal with fuzzy classification problems. A fuzzy classification system uses the knowledge base consist of many fuzzy rules to deal with fuzzy classification problem. The most important task when developing a fuzzy classification system is to construct a knowledge base containing fuzzy rules. There are two approaches to obtain fuzzy rules in fuzzy classification systems. One of them is given directly by domain experts; the other is obtained through a machine learning process. In this thesis, we proposed two methods for constructing membership functions and generating fuzzy rules from training instances for handling fuzzy classification problems. The first method chooses important attribute terms and based on the attribute threshold value, the classification threshold value, and the level threshold to construct membership functions and generate fuzzy rule. This method can get a higher average classification accuracy rate than the existing methods. The second method chooses important attribute terms, constructs membership functions and generates fuzzy rules by using maximum attribute value, minimum attribute value, and average attribute value of each attribute of the training instance. This method can generate fewer fuzzy rules than the existing methods.
Kao, Cheng-Hsuan, and 高正烜. "A New Method for Generating Fuzzy Rules and Constructing Membership Functions from Training Data Containing Noise." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/56120466495488481798.
Повний текст джерела國立臺灣科技大學
電子工程系
88
The Fuzzy classification system is an important application of fuzzy logic. In a fuzzy classification system, objects can be classified properly by a fuzzy rule base. Fuzzy rules have been used as a tool to express knowledge in fuzzy logic, and they are more advantagous than the traditional IF-THEN rules. Fuzzy classification systems can properly deal with uncertainties and vagueness of the data involved in classification problems. One of important tasks in a fuzzy system is to find out a set of rules to deal with a specific classification problem. Usually we have two ways to do this task. One of them is to get knowledge from experts and to transfer it to fuzzy rules. However, the disadvantage of this way is that it is more difficult and needs more time for knowledge acquisition and validation. The other way is to use machine-learning methods, where fuzzy rules are generated from training data automatically. In recent years, there are many researchers focused on the research topic of generating fuzzy rules from training data for handling classification problems. In this thesis, we present a new algorithm to generate fuzzy rules from training data containing noise to deal with classification problems. The proposed algorithm can get a higher classification accuracy rate and generate less fuzzy rules and less input attributes in the antecedent portions of the generated fuzzy rules.
De, Kock Erika. "Decentralising the codification of rules in a decision support expert knowledge base." Diss., 2004. http://hdl.handle.net/2263/22959.
Повний текст джерелаDissertation (MSc Computer Science)--University of Pretoria, 2005.
Computer Science
unrestricted
Pereira, Carlos António Senra. "Modelação e prototipagem de ChatBots." Master's thesis, 2018. http://hdl.handle.net/1822/65020.
Повний текст джерелаGenericamente, ChatBots são programas que interagem com utilizadores humanos através de linguagens naturais. Os ChatBots podem ser criados com objetivos muito diversos, como por exemplo manter uma conversa “inteligente” com um humano, ou prestar serviços em algum domínio concreto, como seja atender chamadas num call-center, reencaminhado-as para um operador. Dada a heterogeneidade dos ChatBots, é importante identificar os seus princípios gerais de organização e de funcionamento. Neste trabalho foi desenvolvida uma proposta original de modelação de ChatBots, que procura identificar estes princípios gerais. Na modelação que desenvolvemos, os ChatBots são organizados em três componentes principais: a interface com o utilizador, o núcleo e o estado do ChatBot. O núcleo é a peça central do funcionamento do Chatbot, pois ele é responsável por processar as interações recebidas do utilizador, gerando reações em resposta. O núcleo contém um conjunto de regras que associam funções de reação a padrões linguísticos que, juntamente com o estado do ChatBot, determinam a escolha da reação a uma dada interação do utilizador. Para a modelação de padrões linguísticos, desenvolvemos aquilo que designamos por expressões regulares linguísticas (ERL). As ERL baseiam-se em expressões regulares, envolvendo etiquetas gramaticais, e incluem um mecanismo para extração das palavras-chave de um padrão linguístico, e deram origem a uma Domain Specific Language. A modelação que desenvolvemos permite a criação de um motor geral para a construção de ChatBots. Para uma prova de conceito, foi criado o Diabrete: um motor geral, open-source, escrito em Python, versão 3, com a base de dados em MySQL, que permite a criação de ChatBots que seguem a modelação desenvolvida neste trabalho. Na implementação do Diabrete recorremos a algumas ferramentas opensource, para levar a cabo as tarefas da análise sintática das frases dos utilizadores (biblioteca FreeLing) e para a construção de um classificador baseado em técnicas de machine learning para a escolha da reação a apresentar a uma dada interação do utilizador (biblioteca NLTK).
ChatBots are programs that interact with human users through natural languages. ChatBots can be created for very different purposes, such as maintaining an ”inteligent”conversation with a human, or providing services in a specific domain, such as answering calls in a call-center, and forward them to an operator. Given the heterogeneity of ChatBots, it becomes important to identify their general principles of organization and operation. In this work, we identify some of these general principles, and develop a new proposal for the modeling of ChatBots. In the developed model, ChatBots are organized into three main components: the user interface, the core of the ChatBot, and the state of the ChatBot. The core is the centerpiece of Chatbot’s operation, as it is responsible for processing the interactions received from the user, generating reactions in response. The core contains a set of rules that associates reaction functions with linguistic patterns that, together with the state of the ChatBot, determine the choice of reaction to a given user interaction. For modeling linguistic patterns, we develop what we call regular linguistic expressions (ERL). ERLs are based on regular expressions involving grammatical tags, include a mechanism for extracting the keywords from a linguistic standard, and have given rise to a Domain Specific Language. The model that we developed allows the design of a general generator for the construction of ChatBots. For a proof of concept, the Diabrete was created. Diabrete is a general, open-source generator, written in Python, version 3, with the database in MySQL, which allows the construction of ChatBots that follow the modeling developed in this work. In the implementation of Diabrete, we used some opensource tools to perform the tasks of the user-generated sentences (library FreeLing) and to construct a classifier based on machine learning techniques for the choice of reaction to be presented to a given user interaction (library NLTK).