Mostrando recursos 38.041 - 38.060 de 80.659

  1. Quantitative Estimation of Competency as a Fuzzy Set

    Leonid Vasylevych; Ivan Iurtyn; Borys Grinchenko; Key Terms Mathematicalmodelling
    Abstract. The authors of this paper have used the assessment of competence as a fuzzy discrete set consisting of essential capacities. There has been proposed a procedure of competence quantitative estimation on the basis of discrimination index of discrete fuzzy sets fixed on one totality. A linguistic variable “Competency coefficient ” has been used here for making appropriate decisions on the grounds of competency quantitative estimation. Assessment of a person’s competency is proposed as a fuzzy discrete set consisting of necessary abilities as its values. Using such competency assessment allows to estimate persons ’ competency quantitatively and to compare them.

  2. Generating Single Granularity-Based Fuzzy Classification Rules for Multiobjective Genetic Fuzzy Rule Selection

    Rafael Alcalá; Yusuke Nojima; Francisco Herrera; Hisao Ishibuchi
    Abstract — Recently, multiobjective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds of algorithms can obtain a set of solutions with different trade-offs. The application of multiobjective evolutionary algorithms to fuzzy rule-based systems is often referred to as multiobjective genetic fuzzy systems. The first study on multiobjective genetic fuzzy systems was multiobjective genetic fuzzy rule selection in order to simultaneously achieve accuracy maximization and complexity minimization. This approach is based on the generation of a set of candidate...

  3. Medical Record Retrieval and Extraction for Professional Information Access

    Chia-chun Lee; Hen-hsen Huang; Hsin-hsi Chen
    This paper analyzes the linguistic phenomena in medical records in different departments, including average record size, vocabulary, entropy of medical languages, grammaticality, and so on. Five retrieval

  4. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Fusion of Word and Letter Based Metrics for Automatic MT Evaluation �

    Muyun Yang; Junguo Zhu; Sheng Li; Tiejun Zhao
    With the progress in machine translation, it becomes more subtle to develop the evaluation metric capturing the systems ’ differences in comparison to the human translations. In contrast to the current efforts in leveraging more linguistic information to depict translation quality, this paper takes the thread of combining language independent features for a robust solution to MT evaluation metric. To compete with finer granularity of modeling brought by linguistic features, the proposed method augments the word level metrics by a letter based calculation. An empirical study is then conducted over WMT data to train the metrics by ranking SVM. The...

  5. Implementation of Fuzzy Pid Controller And Performance Comparision With Pid For Position Control Of Dc Motor

    A. Harsha Vardhan; A. Sai Bharadwaj; S. Srinivasulu Raju; N. Archana
    Abstract:- This paper gives the demonstration about the position control of DC motor using a Fuzzy PID controller to meet the desired position in presence of set point changes the most commonly used controller in the industry field is the proportional-integral-derivative (PID) controller. The PID controllers mostly used in industries due to their robust performance in a wide range of operating conditions & their simple tuning methods. This paper presents design of PID controller with Ziegler-Nichols (ZN) technique for controlling the position of the DC motors. Fuzzy logic controller (FLC) provides an alternate to PID controller, especially when the available...

  6. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence i, Poet: Automatic Chinese Poetry Composition through a Generative Summarization Framework under Constrained Optimization

    Rui Yan; Han Jiang; Mirella Lapata; Shou-de Lin; Xueqiang Lv; Xiaoming Li
    Part of the long lasting cultural heritage of China is the classical ancient Chinese poems which follow strict formats and complicated linguistic rules. Automatic Chinese poetry composition by programs is considered as a challenging problem in computational linguistics and requires high Artificial Intelligence assistance, and has not been well addressed. In this paper, we formulate the poetry composition task as an optimization problem based on a generative summarization framework under several constraints. Given the user specified writing intents, the system retrieves candidate terms out of a large poem corpus, and then orders these terms to fit into poetry formats, satisfying...

  7. Inheritance in an object-oriented representation of linguistic categories

    Walter Daelemans; Koenraad De Smedt; Walter Daelemans; Koenraad De Smedt
    We describe an object-oriented approach to the representation of linguistic knowledge. Rather than devising a dedicated grammar formalism, we explore the use of powerful but domain-independent object-oriented languages. We use default inheritance to organize regular and exceptional behavior of linguistic categories. Examples from our work in the areas of morphology, syntax and the lexicon are provided. Special attention is given to multiple inheritance, which is used for the composition of new categories out of existing ones, and to structured inheritance, which is used to predict, among other things, to which rule domain a word form belongs.

  8. Genetic learning of membership functions for mining fuzzy association rules

    Rafael Alcalá; Jesús Alcalá-fdez; M. J. Gacto; Francisco Herrera
    Abstract — Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data in real-world applications, however, usually consists of quantitative values. In the last years, the fuzzy set theory has been applied to data mining for finding interesting association rules in quantitative transactions. Recently, a new rule representation model was presented to perform a genetic lateral tuning of membership functions. It is based on the 2-tuples linguistic representation model allowing us to adjust the context associated to the linguistic label membership functions. Based on the...

  9. Vowel labelling in a pluricentric language Flemish and Dutch labellers at work

    Hanne Kloots; Evie Coussé; Steven Gillis; Centrum Nederl; Se Taal En Spraak
    Labelling speech sounds, i.e. classifying them into particular linguistic categories, can be influenced by several linguistic and extralinguistic factors, such as the emotional and physical condition of the speaker, the level of expertise and

  10. A Case Study on Medical Diagnosis of Cardiovascular Diseases Using a Genetic Algorithm for Tuning Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets

    J. Sanz; M. Pagola; H. Bustince; A. Brugos; A. Fernández; F. Herrera
    Abstract—In this contribution, we use Fuzzy Rule-Based Classification Systems for classifying the patients with respect to the risk of suffering cardiovascular diseases. Specifically, we use a methodology in which the linguistic labels of the classifier are modeled by means of IVFSs. Thereafter, they are genetically post-processed for tuning the amplitude of the support of the upper bound of each membership function. In this manner a good management of the uncertainty, associated with the definition of the fuzzy terms, is provided to the system. We show the goodness of our methodology by comparing its performance with respect to the one provided...

  11. Memory-based word sense disambiguation

    Jorn Veenstra; Antal Van; Den Bosch; Sabine Buchholz
    Abstract. We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluation task. For each ambiguous word, a semantic word expert is automatically trained using a memory-based approach. In each expert, selecting the correct sense of a word in a new context is achieved by finding the closest match to stored examples of this task. Advantages of the approach include (i) fast development time for word experts, (ii) easy and elegant automatic integration of information sources, (iii) use of all available data for training the experts, and (iv) relatively high accuracy with minimal linguistic...

  12. Genetic Lateral and Amplitude Tuning of Membership Functions for Fuzzy Systems

    Rafael Alcalá; Jesús Alcalá-fdez; María José Gacto; Francisco Herrera
    Abstract — In this work, we extend the genetic lateral tuning of membership functions [1] based on the linguistic 2-tuples representation [2], in order to also perform a tuning of the support amplitude of the membership functions. To do so, we present a new symbolic representation which extends the linguistic 2-tuples representation model with a parameter β to represent the amplitude variation of the support of its associated membership function. I.

  13. FUZZ-IEEE AGeneticAlgorithmforTuningFuzzyRule-BasedClassification SystemswithInterval-ValuedFuzzySets


    Abstract—Fuzzy Rule-Based Classification Systems are a widelyusedtoolinDataMiningbecauseoftheinterpretability givenbytheconceptoflinguisticlabel.However,theuseofthis typeofmodelsimpliesadegreeofuncertaintyinthedefinition ofthefuzzypartitions.Inthisworkwewillusetheconceptof Interval-ValuedFuzzySettodealwiththisproblem.Theaimof thiscontributionistoshowtheimprovementintheperformance oflinguisticFuzzyRule-BasedClassificationSystemsafterward theapplicationofacooperativetuningmethodologybetweenthe tuning of the amplitude of the support and the lateral tuning (based on the 2-tuples fuzzy linguistic model) applied to the linguisticlabelsmodeledwithInterval-ValuedFuzzySets. I.

  14. Review on Recent Speech Recognition Techniques

    Prof Deepa; H. Kulkarni
    Abstract- The objective of Speech Recognition is to determine the sequence of sound units from the Speech signal so that the linguistic message in the form of text to be decoded from the speech Signal. Speech is a sequence of sound units corresponding to a linguistic message. The main problem in these speech applications is processing of the speech signal in a manner similar to human auditory Processing mechanism, so that features relevant to a particular task can be extracted. This paper reviews some of the technologies used for speech recognition for different techniques and survey of some different recognition...

  15. World Bank and IZA ∗

    Mehtabul Azam; Aimee Chin; Nishith Prakash
    India’s colonial legacy and linguistic diversity give English an important role in its economy, and this role has expanded due to globalization in recent decades. It is widely believed that there are sizable economic returns to English-language skills in India, but the extent of these returns is unknown due to lack of data containing measures of both earnings and English ability. In this paper, we use a newly available data set–the India Human Development Survey, 2005–to quantify the effects of English-speaking ability. We find that being fluent in English (compared to not speaking any English) increases hourly wages by 32%,...

  16. Implementation of Fuzzy Logic System for DC Motor Speed Control using Microcontroller

    Mrs. A. A Thorat
    This paper presents an insight into the speed control of DC motor using a fuzzy logic controller to meet the desired speed. Fuzzy logic is one of the most successful applications of fuzzy set in which the variables are linguistic rather than numeric. A fuzzy logic controller (FLC) is based on a set of control rules (fuzzy rules) among linguistic variables. The personal computer provides the necessary flexibility in setting any speed profile with the use of fuzzy packages. The proposed fuzzy controller results in a better response compared to the basic fuzzy controller and normal response of DC motor....

  17. Part-of-speech tagging for Dutch with MBT, a memory-based tagger generator

    Walter Daelemans; Jakub Zavrel; Peter Berck
    We present a part of speech tagger (morphosyntactic disambiguator) for Dutch, constructed by means of the Memory-Based Tagger generation method. In this approach, inductive learning methods are used to derive a tagger, lexicon and unknown word category guesser fully automatically from a tagged example corpus. Advantages of the approach are (i) fast tagger development time without linguistic engineering, (ii) accuracy better than or comparable to state of the art statistical and rule-based approaches, (iii) fast tagging speed, and (iv) reliable unknown word category guessing without the overhead of morphological analysis. 1

  18. ON THE ACQUISITION OF THE INDEFINITE ARTICLE: A CROSS-LINGUISTIC STUDY OF FRENCH, ITALIAN, ROMANIAN AND SPANISH CHILD SPEECH

    Martine Coene
    The present article argues that the idea of morphology-driven syntax carries over to first-language acquisition. Morphology encodes properties of functional categories, i.e. particular features and feature values that must be set according to the target (adult) language during the acquisition process. In agreement with previous findings concerning the acquisition of functional categories in the verbal domain, we discuss here some cross-linguistic data with respect to the nominal functional domain. In this respect, specificity can be said to develop stepwise, as the result of the valuation of the /number / before the /person / feature of noun phrases, which finds its...

  19. On the Arbitrariness of Lexical Categories

    Gert Durieux; Walter Daelemans; Steven Gillis
    In this paper, we look at lexical categories and their predictability from a machine learning perspective. Starting from linguistic intuitions about predictability in three different domains, we show how standard techniques for analyzing classification tasks arive at a similar predictability scale. In the second part of the paper, we carry out machine learning experiments covering these domains and relate learnability results to the previous analysis. The IB1-IG classifier is found to be capable of learning in all three domains, although with varying degrees of success.

  20. Differential effects of phonology and Morphology in Children’s Orthographic Systems: A crosslinguistic study of Hebrew and

    Steven Gillis; Dorit Ravid
    In recent years linguists and psychologists have shown growing interest in the linguistic nature of orthographic systems (Aronoff, 1994), in their psycholinguistic representation in adults (Derwing, 1992) and in their development in learning to read and write (Bryant & Goswami, 1987; Treiman,

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