Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The research aimed to prepare muscle elongation exercises for the arms with high intensity in which the training methods for young blind fencers vary, and to identify the effect of the diversity of muscle elongation exercises for the arms with high intensity on the cellular basal efficiency (lactic acid and sodium bicarbonate) and pulmonary respiration for young blind weapon fencers in terms of sports technology, and the experimental approach was adopted by designing the experimental and equal control groups, and the limits of the research community were represented by young fencers with shish weapon under the age of (20) years in the Army Sports Club, whose number is Total (15) swordsmen, continuing their training for the sports season (20