937 resultados para modelli input-output programmazione lineare grafi pesati
Resumo:
En este trabajo se pretende ofrecer una visión del sector Agroalimentario (SAA) catalán, y muy especialmente, de cual es su situación comparativa dentro del SAA español. Analizando por medio de las tablas input-output aquellas ramas del SAA que actúan como motor en cada una de las economías estudiadas, al mismo tiempo que se detectan las analogías o divergencias entre las dos realidades, la autónoma y la nacional. Los indicadores utilizados para el estudio de la tabla input-output son: Chenery-Watanabe, Rasmussen, Backward linkages, Forward linkdages, multiplicador renta y multiplicador de las importaciones.
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Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.
Resumo:
This dissertation describes a networking approach to infinite-dimensional systems theory, where there is a minimal distinction between inputs and outputs. We introduce and study two closely related classes of systems, namely the state/signal systems and the port-Hamiltonian systems, and describe how they relate to each other. Some basic theory for these two classes of systems and the interconnections of such systems is provided. The main emphasis lies on passive and conservative systems, and the theoretical concepts are illustrated using the example of a lossless transfer line. Much remains to be done in this field and we point to some directions for future studies as well.
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In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.
Resumo:
Trata de conocer hasta qué punto la valoración académica de un individuo incide en la vida posterior del mismo, es decir, cuál puede ser el rendimiento de una persona en función del proceso educativo que haya seguido. Alumnos de cuarto de Bachiller, de edad comprendida entre 13 y 14 años que realizaron sus estudios en Cheste durante los cursos académicos de 1970-1971 y 1971-1972, con el Plan vigente de 1967. En total son 681 alumnos de los cuales el 53,86 por ciento pertenecen a zonas rurales y el 46,14 por ciento a zona urbana. En primer lugar trata teoriza sobre los estudios realizados de caracter input-output, tanto en el campo de la psicología como de la educación siendo consciente de esta forma de los problemas que los mismos dan y a los que deberá enfrentarse, posteriormente plantea el estudio realizando la investigación, seleccionando las variables que pretende estudiar, recogiendo datos , codificándolos, escogiendo una muestra de población y aplicando dichas variables para poder llegar a las conclusiones que finalmente ofrece el estudio y abriendo puertas a otros de las mismas carcterísticas. Encuesta, cuestionario, entrevista personal, test (AMPE). Variables input, dentro de las cuales se encuentran las variables estado (datos psicológicos), y las variables de flujo (rendimiento académico). Como variables psicológicas se consideran la actitud para el estudio, personalidad paranoide versus control, capacidad intelectual, extraversión. Como variables de rendimiento se estudia el rendimiento en cuarto de bachiller, el rendimiento en tercero de bachiller y destrezas físico-deportivas. Como variables de salida output se considera la situación laboral ocupacional, situación personal, situación económica y situación social. Análisis factorial, regresión múltiple, correlación de Pearson, análisis imput-output. Los resultados se encuentran implícitos en las siguientes conclusiones: 1) Los componenenes académicos influyen poco en la vida posterior del sujeto, si bien marcan o detectan en algún sentido su situación social convivencial sobre los demás aspectos. Ello nos induce a pensar que en el aula se califican a la vez que conocimientos, los comportamientos sociales. 2)Los componentes psicológicos influyen más en la situación personal entre los outpurs considerados 3)En el análisis input-output hay que destacar que los outputs no se explican en su totalidad con los inputs que hemos estudiado, lo que destaca la introduccion de muchas otras variables en la consideración de los aspectos tratados y éstas en gran cantidad.
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This study provides detailed information on the ability of healthy ears to generate distortion product otoacoustic emissions (DPOAEs).
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Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.
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This paper brings together two areas of research that have received considerable attention during the last years, namely feedback linearization and neural networks. A proposition that guarantees the Input/Output (I/O) linearization of nonlinear control affine systems with Dynamic Recurrent Neural Networks (DRNNs) is formulated and proved. The proposition and the linearization procedure are illustrated with the simulation of a single link manipulator.
Resumo:
A dynamic recurrent neural network (DRNN) is used to input/output linearize a control affine system in the globally linearizing control (GLC) structure. The network is trained as a part of a closed loop that involves a PI controller, the goal is to use the network, as a dynamic feedback, to cancel the nonlinear terms of the plant. The stability of the configuration is guarantee if the network and the plant are asymptotically stable and the linearizing input is bounded.