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In this paper, we propose a new task of ESNs in order to solve distributed optimal control problems for systems governed by parabolic differential equations with discrete time delay using an adaptive critic designs. The optimal control problems are discretised by using a finite element method in time and space, then transcribed into a nonlinear programming problems. To find optimal controls and optimal trajectories ESNs adaptive critic designs are used to approximate co-state equations.

The efficiency of our approach is demonstrated for a SIR distributed system to control the spread of diseases. Computer Science. Space-time RBF method for solving hyperbolic optimal control problems more. Intuition, Imagination and Visual Evidence in Geometry more. Duality concept in curve and surface modelling more.

The paper deals with projective construction of envelope conic section, line conic and its corresponding point conic and generally, with dual Bezier curve and its corresponding point curve. Also, the role of dual Bezier curves in surface Also, the role of dual Bezier curves in surface modelling is studied.

Duality concept is useful in both; special plane curve modelling and developable surface modelling. The present paper describes the back-propagation learning of a partial functional differential equation with reaction-diffusion term. The time-dependent recurrent learning algorithm is developed for a delayed recurrent neural network with The time-dependent recurrent learning algorithm is developed for a delayed recurrent neural network with the reaction-diffusion term.

The proposed simulation methods are illustrated by the back-propagation learning of continuous multilayer Hopfield neural network with a discrete time delay and reaction-diffusion term using the prey-predator system as a teacher signal. The results show that the continuous Hopfield neural networks are able to approximate the signals generated from the predator-prey system with Hopf bifurcation.

A 24h forecast of solar irradiance using echo state neural networks more. Artificial neural networks have demonstrated to be good at timeseries forecasting problems, being widely studied in literature. In this study an artificial neural network model is introduced for modelling the solar irradiance. Forecasting of solar irradiance is in general significant for planning the operations of power plants which convert renewable energies into electricity.

In particular, the possibility to predict the solar irradiance up to 24h or even more can become fundamental in making power dispatching plans. In this paper, a practical method for solar irradiance forecast using artificial neural network is presented. The proposed echo state neural networks model makes it possible to forecast the solar irradiance on the base of 24h using the present values of the mean hours solar irradiance, air temperature, humidity, and the wind speed.

An experimental database of solar irradiance, air temperature, humidity, wind speed data from October 17th to May 11th has be Neural Network Simulation of Photosynthetic Production more. A neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints and discrete time delay. The optimal control problem is transcribed into nonlinear programming problem The optimal control problem is transcribed into nonlinear programming problem which is implemented with adaptive critic neural network.

The proposed simulation methods is illustrated by the optimal control problem of photosynthetic production described by discrete time delay differential equations. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Surface Modeling with Quadratic Triangular Patches more. The paper contents overview and comparison of various constructions of mainly quadratic triangular patches, ruminates conditions under which they form a part of quadratic surface. The triangular patches are expressed in a simple matrix The triangular patches are expressed in a simple matrix form for comparison and visualization. The examples are illustrated by program Maple.

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