Predicting the future trajectories of pedestrians is a challenging problem that has range application, from crowd surveillance to autonomous driving. In literature, methods approach pedestrian trajectory prediction have evolved, transitioning physics-based models data-driven based on recurrent neural networks. this work, we propose new prediction, with introduction novel 2D convolutional model....

This paper presents review of application of artificial neural networks in weather classification and prediction; some existing weather forecasting models have limitations and also benefits of neural network are discussed in this paper. Accurate weather prediction is important in today’s world as agricultural sector is widely dependent on it. Since there is non-linearity in weather data therefo...

rotating machines in particular induction electrical machines are important industry instruments. in manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. in this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using...

In the present study, prediction of Alumina recovery efficiency (A.R.E), the amount of produced red mud (A.P.R), red mud settling rate (R.S.R) and bound-soda losses (B.S.L) in Bayer process red mud has been carried out for the first time in the field. These predictions are based on Lime to bauxite ratio and chemical analyses of bauxite and lime as Bayer process feed materials. Radial basis func...