898 resultados para Expert systems


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This work describes how genetic programming is applied to evolving controllers for the minimum time swing up and inverted balance tasks of the continuous state and action: limited torque acrobot. The best swing-up controller is able to swing the acrobot up to a position very close to the inverted ‘handstand’ position in a very short time, shorter than that of Coulom (2004), who applied the same constraints on the applied torque values, and to take only slightly longer than the approach by Lai et al. (2009) where far larger torque values were allowed. The best balance controller is able to balance the acrobot in the inverted position when starting from the balance position for the length of time used in the fitness function in all runs; furthermore, 47 out of 50 of the runs evolve controllers able to maintain the balance position for an extended period, an improvement on the balance controllers generated by Dracopoulos and Nichols (2012), which this paper is extended from. The most successful balance controller is also able to balance the acrobot when starting from a small offset from the balance position for this extended period.

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The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

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Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.

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This thesis studies the properties and usability of operators called t-norms, t-conorms, uninorms, as well as many valued implications and equivalences. Into these operators, weights and a generalized mean are embedded for aggregation, and they are used for comparison tasks and for this reason they are referred to as comparison measures. The thesis illustrates how these operators can be weighted with a differential evolution and aggregated with a generalized mean, and the kinds of measures of comparison that can be achieved from this procedure. New operators suitable for comparison measures are suggested. These operators are combination measures based on the use of t-norms and t-conorms, the generalized 3_-uninorm and pseudo equivalence measures based on S-type implications. The empirical part of this thesis demonstrates how these new comparison measures work in the field of classification, for example, in the classification of medical data. The second application area is from the field of sports medicine and it represents an expert system for defining an athlete's aerobic and anaerobic thresholds. The core of this thesis offers definitions for comparison measures and illustrates that there is no actual difference in the results achieved in comparison tasks, by the use of comparison measures based on distance, versus comparison measures based on many valued logical structures. The approach has been highly practical in this thesis and all usage of the measures has been validated mainly by practical testing. In general, many different types of operators suitable for comparison tasks have been presented in fuzzy logic literature and there has been little or no experimental work with these operators.

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Ce mémoire de maîtrise traite d’un phénomène social critique qui a gagné en importance au Québec : la montée des groupes de résistance populaire contre des projets d’exploitation des ressources naturelles. À partir d’une étude de cas, l’auteur tâche ici d’approfondir les questions relatives à ces luttes collectives tout en mettant en lumière les diverses modalités d’engagement qui, par leurs registres et leurs compositions en « systèmes-experts », se répercutent dans l’espace public tout en transformant, d’une certaine manière, l’arène politique. Ces dynamiques des mouvements de résistance tendent également à s’infléchir en amont des projets de développement, pour se matérialiser en aval, soit dès les premières phases d’appropriation territoriale, c’est-à-dire les premiers travaux exploratoires comme tels. Cette enquête de terrain se focalise sur ces enjeux. En prenant comme observatoire le projet de Terra Ventures à Sept-Îles, en région nord-côtière, concernant un projet d’exploration uranifère, l’auteur insiste sur les multiples références collectives qui sont autant de perspectives pour comprendre ce phénomène. À travers l’étude de cette résistance populaire qui s’est profilée contre ce projet d’exploration, c’est l’industrie minière au Québec, son histoire, ses mythes, et sa mémoire qui est, enfin, en trame de fond.

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We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

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Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

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Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

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The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

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This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

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An overview of COMP3028 Knowledge Technologies

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En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.

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Para maximizar los beneficios, una compañía fundamenta sus acciones en ciertas estrategias que ayudan a cumplir su objetivo de generar utilidades. Entre las diferentes acciones que una organización puede utilizar, están las de responsabilidad social y las de relaciones estratégicas con la comunidad. Partiendo de la definición de comunidad, pasando por una descripción de responsabilidad social y sus diferentes formas de aplicabilidad dentro de una empresa, hasta la definición de relación estratégica con la comunidad; esta investigación dirige sus esfuerzos a determinar el vínculo que existe entre los conceptos de responsabilidad social y relación estratégica comunitaria. Adicionalmente, se plantea que otras estrategias de relacionamiento con clientes, como el mercadeo relacional o el CRM, las cuales enfocan sus esfuerzos en conocer a cada uno de los clientes de una compañía para plantear una oferta acorde a sus necesidades, no son muy efectivas a la hora de crear un vínculo emocional con la comunidad.

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En el sector de la promoció construcció, i en especial, en el subsector de la promoció construcció d'habitatges, l'empresari ha de tenir un bon coneixement de les variables d'entorn ja que la consideració de les mateixes seran fonamentals a l'hora de prendre decisions sobre planificació estratègica. En l'actualitat vivim una fase de canvis socioeconòmics que dificulten la previsió del comportament futur de les variables d'entorn. Per tant, el subjecte decisor es troba en un ambient d'incertesa que s'aguditza per la majoritària presència de factors qualitatius difícils de quantificar. Llavors, l'empresari promotor constructor haurà de recórrer a tècniques operatives de gestió que tinguin present aquesta situació i això serà possible a partir de les eines que ens ofereix la lògica borrosa. Aquesta tesi s'ha estructurat en tres parts: En la primera part, exposem les característiques específiques i l'evolució del sector. En la segona part, expliquem la metodologia i, en la tercera part, exposem diverses aplicacions de la metodologia borrosa per l'establiment de noves estratègies de gestió aplicades al sector objecte d'estudi.

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La present tesi pretén recollir l'experiència viscuda en desenvolupar un sistema supervisor intel·ligent per a la millora de la gestió de plantes depuradores d'aigües residuals., implementar-lo en planta real (EDAR Granollers) i avaluar-ne el funcionament dia a dia amb situacions típiques de la planta. Aquest sistema supervisor combina i integra eines de control clàssic de les plantes depuradores (controlador automàtic del nivell d'oxigen dissolt al reactor biològic, ús de models descriptius del procés...) amb l'aplicació d'eines del camp de la intel·ligència artificial (sistemes basats en el coneixement, concretament sistemes experts i sistemes basats en casos, i xarxes neuronals). Aquest document s'estructura en 9 capítols diferents. Hi ha una primera part introductòria on es fa una revisió de l'estat actual del control de les EDARs i s'explica el perquè de la complexitat de la gestió d'aquests processos (capítol 1). Aquest capítol introductori juntament amb el capítol 2, on es pretén explicar els antecedents d'aquesta tesi, serveixen per establir els objectius d'aquest treball (capítol 3). A continuació, el capítol 4 descriu les peculiaritats i especificitats de la planta que s'ha escollit per implementar el sistema supervisor. Els capítols 5 i 6 del present document exposen el treball fet per a desenvolupar el sistema basat en regles o sistema expert (capítol 6) i el sistema basat en casos (capítol 7). El capítol 8 descriu la integració d'aquestes dues eines de raonament en una arquitectura multi nivell distribuïda. Finalment, hi ha una darrer capítol que correspon a la avaluació (verificació i validació), en primer lloc, de cadascuna de les eines per separat i, posteriorment, del sistema global en front de situacions reals que es donin a la depuradora