.../methodology/approach We propose a framework that combines two methods. First, we use a Discrete Wavelet Transform (DWT) to clean the data, separating the underlying trends from market noise. Second, we feed this denoised data into a time-series recurrent neural network (TRNN). We optimized the TRNN...

...H. Bello-Salau; A.M. Aibinu; A.J. Onumanyi; E.N. Onwuka; J.J. Dukiya; H. Ohize This paper presents a new algorithm for detecting and characterizing potholes and bumps directly from noisy signals acquired using an Accelerometer. A wavelet transformation based filter was used to decompose the signals...