An approximation of orbit rendezvous is usually used in the global optimization multi-target missions, which can greatly affect efficiency process. A fast neural network-based surrogate model proposed to approximate optimal velocity increment perturbed low Earth orbits. According a dynamic analysis, initial and target orbits together with flight time are transformed into nine-dimensional normal...

A new mapping network combined wavelet and neural networks is proposed. The algorithm consists of two process: the selfconstruction of networks and the minimization of errors. In the first process, the network structure is determined by using wavelet analysis. In the second process, the approximation errors are minimized. The merits of the proposed network are as follows: network optimization, ...

Function approximation, which finds the underlying relationship from a given finite input-output data is the fundamental problem in a vast majority of real world applications, such as prediction, pattern recognition, data mining and classification. Various methods have been developed to address this problem, where one of them is by using artificial neural networks. In this paper, the radial bas...

In this paper, with the aim of estimating internal dynamics matrix of a gimbaled Inertial Navigation system (as a discrete Linear system), the discretetime Hamilton-Jacobi-Bellman (HJB) equation for optimal control has been extracted. Heuristic Dynamic Programming algorithm (HDP) for solving equation has been presented and then a neural network approximation for cost function and control input ...

The neural network with two weights is constructed and its approximation ability to any continuous functions is proved. For this neural network, the activation function is not confined to the odd functions. We prove that it can limitlessly approach any continuous function from limited close subset of R(m) to R(n) and any continuous function, which has limit at infinite place, from limitless clo...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

if both reference station (rs) and navigational device in differential global positioning system (dgps) receive signals from the same satellite, rs position components error (rpce) can be used to compensate for navigational device error. this research used hybrid method for rpce prediction which was collected by a low-cost gps receiver. it is a combination of genetic algorithm (ga) computing an...

the safety of buried pipes under repeated load has been a challenging task in geotechnical engineering. in this paper artificial neural network and regression model for predicting the vertical deformation of high-density polyethylene (hdpe), small diameter flexible pipes buried in reinforced trenches, which were subjected to repeated loadings to simulate the heavy vehicle loads, are proposed. t...

-This paper focuses the function approximation capability of feed forward neural network (FFNN). A Graphical user Interface (GUI) system has been developed and tested for function approximation. This GUI system can approximate any nonlinear/linear function which can have any number of input variable and six output variables. Configuration of neural network can be set from a single GUI window. A...