Forecasting high waters at Venice Lagoon using chaotic time series analisys and nonlinear neural netwoks

Time series analysis using nonlinear dynamics systems theory and multilayer neural networks models have been applied to the time sequence of water level data recorded every hour at 'Punta della Salute' from Venice Lagoon during the years 1980-1994. The first method is based on the reconstruction of the state space attractor using time delay embedding vectors and on the characterisation of invariant properties which define its dynamics. The results suggest the existence of a low dimensional chaotic attractor with a Lyapunov dimension, DL, of around 6.6 and a predictability between 8 and 13 hours ahead. Furthermore, once the attractor has been reconstructed it is possible to make predictions by mapping local-neighbourhood to local-neighbourhood in the reconstructed phase space. To compare the prediction results with another nonlinear method, two nonlinear autoregressive models (NAR) based on multilayer feedforward neural networks have been developed. From the study, it can be observed that nonlinear forecasting produces adequate results for the 'normal' dynamic behaviour of the water level of Venice Lagoon, outperforming linear algorithms, however, both methods fail to forecast the 'high water' phenomenon more than 2-3 hours ahead.Publicad

A family of Chebyshev-Halley type methods in Banach spaces

A family of third-order iterative processes (that includes Chebyshev and Halley's methods) is studied in Banach spaces. Results on convergence and uniqueness of solution are given, as well as error estimates. This study allows us to compare the most famous third-order iterative processes

Third-order iterative methods with applications to Hammerstein equations: A unified approach

AbstractThe geometrical interpretation of a family of higher order iterative methods for solving nonlinear scalar equations was presented in [S. Amat, S. Busquier, J.M. Gutiérrez, Geometric constructions of iterative functions to solve nonlinear equations. J. Comput. Appl. Math. 157(1) (2003) 197–205]. This family includes, as particular cases, some of the most famous third-order iterative methods: Chebyshev methods, Halley methods, super-Halley methods, C-methods and Newton-type two-step methods. The aim of the present paper is to analyze the convergence of this family for equations defined between two Banach spaces by using a technique developed in [J.A. Ezquerro, M.A. Hernández, Halley’s method for operators with unbounded second derivative. Appl. Numer. Math. 57(3) (2007) 354–360]. This technique allows us to obtain a general semilocal convergence result for these methods, where the usual conditions on the second derivative are relaxed. On the other hand, the main practical difficulty related to the classical third-order iterative methods is the evaluation of bilinear operators, typically second-order Fréchet derivatives. However, in some cases, the second derivative is easy to evaluate. A clear example is provided by the approximation of Hammerstein equations, where it is diagonal by blocks. We finish the paper by applying our methods to some nonlinear integral equations of this type

A construction procedure of iterative methods with cubical convergence II: Another convergence approach

We extend the analysis of convergence of the iterations considered in Ezquerro et al. [Appl. Math. Comput. 85 (1997) 181] for solving nonlinear operator equations in Banach spaces. We establish a different Kantorovich-type convergence theorem for this family and give some error estimates in terms of a real parameter [-5, 1). © 1998 Elsevier Science Inc. All rights reserved

A note on a modification of Moser's method

We use a recurrence technique to obtain semilocal convergence results for Ulm's iterative method to approximate a solution of a nonlinear equation F (x) = 0fenced((x n + 1 = x n - B n F (x n),, n 0,; B n + 1 = 2 B n - B n F (x n + 1) B n,, n 0 .))This method does not contain inverse operators in its expression and we prove it converges with the Newton rate. We also use this method to approximate a solution of integral equations of Fredholm-type. © 2007 Elsevier Inc. All rights reserved

Bedform variability and flow regime in a barrier-inlet system. The mesotidal Piedras mouth (Huelva, SW Spain)

Bedform fields from the Piedras River mouth (Huelva, SW Spain) have been studied using side-scan sonar techniques, combined with visual scuba-dives, and direct geometric measuring. The dominant flow regime has been determined from the results in these tidal environments, where erosive processes dominate during ebb, transporting sand as a bedload towards the mouth and central sector of the tidal channel. The process is reversed during tidal floods. During neap tides, larger bedforms maintain their geometry and position, whereas small ripples are re-oriented under different tidal conditions. Sand patches, dunes and ripples are interpreted as sediment bypassing zones. Large forms indicate high energy flow, which can only migrate when flow velocity reaches threshold values for the movement, with net sand transport towards open areas. Depositional features indicate low, moderate, and high-energy conditions. Here, a depositional regime dominated by sediment accommodation is dominant, where sandy sediments are continuously remobilized, transported and re-deposited, even closer to the estuarine mouth. In inner zones finer particles, such as clay and silt, are transported by tides as suspended matter and deposited in protected inner areas. The final results are long narrow tidal flats, which alternate with sandy areas dominated by erosion

Improved Epstein-Glaser renormalization in x-space versus differential renormalization

Renormalization of massless Feynman amplitudes in x-space is reexamined here, using almost exclusively real-variable methods. We compute a wealth of concrete examples by means of recursive extension of distributions. This allows us to show perturbative expansions for the four-point and two-point functions at several loop order. To deal with internal vertices, we expound and expand on convolution theory for log-homogeneous distributions. The approach has much in common with differential renormalization as given by Freedman, Johnson and Latorre; but differs in important details

Análisis técnico-económico de las explotaciones caprinas de raza Malagueña: Estrategias de mejora de su viabilidad

publishedTomo I . Sección: Sistemas Ganaderos-Economía y Gestión. Sesión: Economía I. Ponencia nº 1

Implementation of an extended ZINB model in the study of low levels of natural gastrointestinal nematode infections in adult sheep

Background: In this study, two traits related with resistance to gastrointestinal nematodes (GIN) were measured in 529 adult sheep: faecal egg count (FEC) and activity of immunoglobulin A in plasma (IgA). In dry years, FEC can be very low in semi-extensive systems, such as the one studied here, which makes identifying animals that are resistant or susceptible to infection a difficult task. A zero inflated negative binomial model (ZINB) model was used to calculate the extent of zero inflation for FEC; the model was extended to include information from the IgA responses. Results: In this dataset, 64 % of animals had zero FEC while the ZINB model suggested that 38 % of sheep had not been recently infected with GIN. Therefore 26 % of sheep were predicted to be infected animals with egg counts that were zero or below the detection limit and likely to be relatively resistant to nematode infection. IgA activities of all animals were then used to decide which of the sheep with zero egg counts had been exposed and which sheep had not been recently exposed. Animals with zero FEC and high IgA activity were considered resistant while animals with zero FEC and low IgA activity were considered as not recently infected. For the animals considered as exposed to the infection, the correlations among the studied traits were estimated, and the influence of these traits on the discrimination between unexposed and infected animals was assessed. Conclusions: The model presented here improved the detection of infected animals with zero FEC. The correlations calculated here will be useful in the development of a reliable index of GIN resistance that could be of assistance for the study of host resistance in studies based on natural infection, especially in adult sheep, and also the design of breeding programs aimed at increasing resistance to parasites

CONTROL ÓPTIMO PARA EL CONTROL DE TEMPERATURA EN EL CULTIVO DE TOMATE EN INVERNADERO BASADO EN UN SISTEMA DINÁMICO.

ResumenUn control óptimo para regular la temperatura al interior de un invernadero se puede obtener a partir del modelo matemático integrado del cultivo y del invernadero. El modelo en consideración es exclusivo de la sierra norte del estado de Puebla, México; pues los parámetros necesarios se determinaron durante un periodo de cosecha de 80 días en la época de invierno. El modelo considera cinco estados: relativo con el cultivo consideramos el número de nodos, la masa seca del dosel y la masa seca de la raíz; relativo con el invernadero consideramos, la temperatura al interior del invernadero y la humedad relativa.Para aplicar la teoría de control óptimo, seleccionamos un costo funcional con el fin de aumentar el beneficio del agricultor, significa que el agricultor además de aumentar potencialmente la producción del cultivo obtendrá un ahorro en los gastos de consumo de energía.Construimos el algoritmo que da solución al problema de control óptimo y realizamos la simulación en un periodo de 80 días.Palabra(s) Clave: Control óptimo, Modelo dinámico integrado, Sistema de calefacción, Variables auxiliares, Variables de estado. OPTIMUM CONTROL FOR TEMPERATURE CONTROL IN GREENHOUSE TOMATO CULTIVATION BASED ON A DYNAMIC SYSTEMAbstractAn optimal control to regulate the temperature inside of a greenhouse can be obtained from a mathematical model, where such mathematical model integrates the dynamic model of the crop (tomato crop) and the greenhouse. This paper considers the dynamic model exclusive from northern mountain range of Puebla, Mexico. This means that all parameters were determined from a harvest throughout a period of 80 days in the winter season. The dynamic model considered 5 state variables, three of them are relative from the crop, they are the number of nodes (plant development), the biomass dry canopy, and the biomass dry root. The last 2 variables state are linked to the greenhouse, these are the temperature inside of the greenhouse and the relative humidity. Applying the optimal control theory with a proposal criterion of optimization, admissible trajectories for the variables state were obtained; such trajectories maximize the benefit of the crop, thereby the farmers and harvest improves the crop production, and reduce the energy consumption. An algorithm was built, which gives a solution for the optimal control and simulates a harvest throughout a period of 80 days.Keywords: Auxiliary states, Heating system, Integrated Dynamic Model, Optimal control, Variable state