Économie mathématique

Résumé

vignette|Les acteurs économiques (STN et actionnaires) sont classés par importance décroissante, donnée par . Un point de données situé en () correspond à une fraction des principaux acteurs économiques détenant cumulativement la fraction du contrôle, de la valeur ou des revenus d'exploitation du réseau. Les différentes courbes se réfèrent au contrôle du réseau calculé avec trois modèles (LM, TM, RM), voir l'annexe S1, section 3.1, et aux revenus d'exploitation. La ligne horizontale indique une valeur égale à . Le niveau de concentration est déterminé par la valeur de l'intersection entre chaque courbe et la ligne horizontale. L'échelle est semi-logarithmique. L'économie mathématique est l'application des méthodes mathématiques pour représenter des théories économiques et analyser les problèmes posés en économie. Histoire L'économie est, pendant longtemps, une discipline littéraire et descriptive. Adam Smith n'utilise pas ou peu de mathématiques, et l'École classique qu'il

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https://fr.wikipedia.org/wiki/%C3%89conomie_math%C3%A9matique

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This course provides students with a working knowledge of macroeconomic models that explicitly incorporate financial markets. The goal is to develop a broad and analytical framework for analyzing the interaction of financial decisions, macroeconomic events and policy decisions.

This course presents the problem of static optimization, with and without (equality and inequality) constraints, both from the theoretical (optimality conditions) and methodological (algorithms) point of view. Economics and financial applications are provided. Dynamic optimization is also introduced

The course will provide the opportunity to tackle real world problems requiring advanced computational skills and visualisation techniques to complement statistical thinking. Students will practice proposing efficient solutions, and effectively communicating the results with stakeholders.

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CHARACTERIZATION OF THE THERMOECONOMIC OPTIMIZATION PROBLEM OF AN ELECTRICITY STORAGE SYSTEM BASED ON THEORETICAL THERMODYNAMIC CYCLES

Manuel Rizzato

2012

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Phosphorus (P) is the second essential nutrient for plant growth but can become an ecological and economical concern in case of over-fertilization. Soil P dynamic is influenced by many parameters like soil physical-chemical properties and farming practices. A better understanding of the factors controlling its distribution is required to achieve best P crops management. In Switzerland, the FRIBO network was launched in 1987 and comprises of 250 sites covering a wide diversity of soils and three different land uses (croplands, grasslands and mountain pastures) across the Fribourg canton. A spatial investigation of the different P forms for the FRIBO network led to the following main conclusions: i) The P status in agricultural soils was significantly different among the three land uses encountered, with the highest mean values of available P found in croplands (from 2.12 to 81.3 mg.kg-1 according to the indicator used), whereas total P was more abundant in permanent grasslands (1186.2 mg.kg-1), followed by mountain pastures (1039.0 mg.kg-1) and croplands (935.0 mg.kg-1). A full characterization of the soil P status provides necessary data on P distribution related to soil properties and land use, and should help to develop more accurate estimation procedures and fertilization strategies in a near future; ii) Environmental variables derived from digital elevation model (DEM) only explained a small part of the spatial variation of the different P forms (20 to 25%). Thus, the geostatistic analyses revealed that land use play a major role in soil P distribution. However, this pattern was less visible for total P than for available P. Future studies should include more data points as well as additional variables such as parent material and soil type to accurately estimate the role of soil parameters on the distribution of P-related forms.

Elsevier2014

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Lattice-and-Plate Model: Mechanics Modeling of Physical Origami Robots

Jamie Paik, Hongying Zhang

Origami robots are characterized by their compact design, quasi-two-dimensional manufacturing process, and folding joint-based transmission kinematics. The physical requirements in terms of payload, range of motion, and embedding core robotic components have made it unrealistic to rely on conventional mathematical models for designing these new robots. Therefore, origami robots require a comprehensive approach to model their mechanics. Currently, there is no generalized mechanics model to achieve this goal. Therefore, in this work, we propose a nonlinear lattice-and-plate model to simulate the mechanics of physical origami robots within several seconds, including the localized bending on flexible hinges, global displacements of rigid panels, and trajectory of predefined outputs. Moreover, this proposed model captures the large displacement and self-contact of adjacent panels during locomotion. We validate the efficiency of the model on various origami actuators, grippers, and metamaterials. To conclude, the computational model can help to accelerate the design iteration of origami robots.

MARY ANN LIEBERT, INC2022

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