31,712 research outputs found

    FPGA design methodology for industrial control systems—a review

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    This paper reviews the state of the art of fieldprogrammable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic

    Информационная поддержка анализа навыков и умений контингента студентов высшего учебного заведения

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    In the below article, the application of the fuzzy logical conclusion method is considered as decision-maker in the process of analyzing the students skills and abilities based on the requirements of potential employers, in order to reduce the time of the first interview for potential candidates on a vacant position. When analyzing the results of the assessment of the competence of university students, a certain degree of fuzziness arises. In modern practice, fuzzy logic is used in many different assessment methods, including questioning, interviewing, testing, descriptive method, classification method, pairwise comparison, rating method, business games competence models, and the like. Each of the methods has its advantages and disadvantages, but they are effective only as part of a unified personnel management system. As a method for implementing a systematic approach to the assessment of the contingent of students, it is proposed to use fuzzy logic, a mathematical apparatus that allows you to build a model of an object based on fuzzy judgments. The use of fuzzy logic, the mathematical apparatus of which allows you to build a model of the object, based on fuzzy reasoning and rules. The most important condition for creating such a model is to translate the fuzzy, qualitative assessments used by man into the language of mathematics, which will be understood by the computer. The most used are fuzzy inferences using the Mamdani and Sugeno methods. In a fuzzy inference of the Mamdani type, the value of the output variable is given by fuzzy terms, in the conclusion of the Sugeno type, as a linear combination of the input variables. Research in the field of application of fuzzy logic in socio-economic systems suggests that it can be used to assess the competencies of university students.В данной работе рассмотрено использование метода нечеткого логического вывода для поддержки принятия решения в задачах анализа навыков и умений контингента студентов исходя из требований потенциальных работодателей, с целью уменьшения времени на первичную обработку информации касательно потенциальных кандидатов на вакантную должность. При анализе результатов оценки компетентности студентов вузов возникает определенная степень нечеткости. В современной практике нечеткая логика применяется во многих различных методах оценки, в том числе анкетирование, интервью, тестирование, описательный метод, метод классификации, парное сравнение, рейтинговый метод, деловые игры модели компетентности и тому подобное. Каждый из методов имеет свои преимущества и недостатки, но эффективны они только в составе единой системы управления персоналом. Как метод для реализации системного подхода к оценке контингента студентов предложено использовать нечеткую логику, математический аппарат, который позволяет построить модель объекта, основанную на нечетких суждениях. Использование нечеткой логики, математический аппарат которой позволяет построить модель объекта, основываясь на нечетких рассуждениях и правилах. Важнейшее условие создания такой модели заключается в том, чтобы перевести нечеткие, качественные оценки, применяемые человеком, на язык математики, которая будет понятна вычислительной машине. Наиболее используемыми являются нечеткие выводы с помощью способов Мамдани и Сугено. В нечетком выводе типа Мамдани значение выходной переменной задаются нечеткими термами, в заключении типа Сугено – как линейная комбинация входных переменных. Исследования в области применения нечеткой логики в социоэкономических системах позволяют говорить о возможности ее использования для оценки компетенций студентов вузов

    Fuzzy Logic and Its Uses in Finance: A Systematic Review Exploring Its Potential to Deal with Banking Crises

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    The major success of fuzzy logic in the field of remote control opened the door to its application in many other fields, including finance. However, there has not been an updated and comprehensive literature review on the uses of fuzzy logic in the financial field. For that reason, this study attempts to critically examine fuzzy logic as an effective, useful method to be applied to financial research and, particularly, to the management of banking crises. The data sources were Web of Science and Scopus, followed by an assessment of the records according to pre-established criteria and an arrangement of the information in two main axes: financial markets and corporate finance. A major finding of this analysis is that fuzzy logic has not yet been used to address banking crises or as an alternative to ensure the resolvability of banks while minimizing the impact on the real economy. Therefore, we consider this article relevant for supervisory and regulatory bodies, as well as for banks and academic researchers, since it opens the door to several new research axes on banking crisis analyses using artificial intelligence techniques

    Comparación de técnicas de clasificación deductivas para estimar la distribución potencial de insectos cuarentenarios

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    El objetivo de este trabajo fue comparar el desempeño de los criterios de clasificación nítidos y difusos en la construcción de modelos deductivos de la distribución potencial de insectos exóticos. Considerando criterios de clasificación binaria nítida y difusa, de capas ráster de temperatura máxima, media y mínima diaria, se generó un índice de riesgo bioclimático relativo, considerando el número de días con condiciones óptimas para el desarrollo de Bactrocera oleae (Gmelin) (Diptera: Tephritidae) y Cerotoma arcuatus (Olivier) (Coleoptera: Chrysomelidae). Se realizaron análisis de sensibilidad de los modelos. Los modelos deductivos de distribución potencial de especies realizados mediante clasificación difusa, serían más robustos y menos restrictivos en la determinación de áreas de riesgo fitosanitario potencial que aquellos realizados con criterios de clasificación nítidos. Estos últimos serían más sensibles y tendrían mayor capacidad de discriminar áreas con diferentes perfiles de riesgo ambiental.The objective of this paper was to evaluate the performance of crisp and fuzzy classification criteria in the construction of deductive potential distribution models of exotic insects. As case studies, Bactrocera oleae (Gmelin) (Diptera: Tephritidae) and Cerotoma arcuatus (Olivier) (Coleoptera: Chrysomelidae) were selected. Considering crisp and fuzzy classification for raster layers of maximum, average and minimum daily temperature, a relative bioclimatic risk index was generated. The number of days with optimal conditions for pests’ development was considered. Sensitivity analyses of both models were performed. Considering each case evaluated and the variables used, deductive pest distribution models made by fuzzy classification was more robust and less conservative in the determination of potential phytosanitary risk areas than those made with crisp classification criteria. This last case was more sensitive and would have a greater capacity to discriminate areas with different environmental risk profiles.Fil: Heit, Guillermo Eugenio. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Zoología Agrícola; ArgentinaFil: Sione, Walter Fabian. Universidad Autónoma de Entre Rí­os. Facultad de Ciencia y Tecnología. Centro Regional de Geomática; Argentina. Universidad Nacional de Luján; ArgentinaFil: Claps, Lucia Elena. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Superior de Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Aceñolaza, Pablo Gilberto. Provincia de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Universidad Autónoma de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; Argentin
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