The deformation process of landslide displacement has complex nonlinear characteristics. In view the problems large error, slow convergence and poor stability traditional neural network prediction model, in order to better realize accurate effective displacement, this research proposes a model based on Genetic Algorithm (GA) optimized Elman network. This combines GA with optimize weights, thres...

A reduced model technique based on a coarse boundary element method (BEM) mesh is developed in order to increase the rate of convergence of a genetic algorithm (GA) used for solving a non-destructive evaluation problem. The inverse problem investigated consists of identifying the geometry of discontinuities in a conductive material with isotropic conductivity from Cauchy data measurements taken...

We are developing GA-based tools for use in constructing high quality approximations to continuous functions. In this paper we report on a GA-based method for adaptively selecting e ective interpolation points. We evaluate our approach on a variety of test functions, and we compare are results to more traditional approaches. The results are quite promising and suggest directions for further imp...

Geometric algebra (GA) is a mathematical framework that allows the compact description of geometric relationships and algorithms in many fields of science and engineering. The execution of these algorithms, however, requires significant computational power that made the use of GA impractical for many real-world applications. We describe how a GA-based formulation of the inverse kinematics probl...

Albuquerque, USA, April 20-25, 1997 Genetic Design of 3D Modular Manipulators O. Chocron and P. Bidaud Laboratoire de Robotique de Paris CNRS-UPMC-UVSQ 10-12 Avenue de l'Europe, 78140 V elizy, France. E-mail: chocron,[email protected] Abstract This paper proposes a method for task based design of modular robotic systems using Genetic Algorithms (GA). We introduce a 3D kinematic description f...