Rainfall forecasting is critical for the economy, but it has proven difficult due to uncertainties, complexities, and interdependencies that exist in climatic systems. An efficient rainfall model will be beneficial implementing suitable measures against natural disasters such as floods landslides. In this paper, a novel hybrid of empirical mode decomposition (EMD) random forest (RF) was develop...

This criterion should be contrasted with the RSS encountered earlier in the course. The RSS pertains to model estimation, since we are already assuming a given model for some particular data set; and it suffices to estimate the specific values of our estimators for the unknown parameters. The MSE combines the previous two criteria, on the unbiasedness and the variance of β̂, through the followin...

Intermittency of electrical power in developing countries, as well some European countries such Turkey, can be eluded by taking advantage solar energy. Correct prediction radiation constitutes a very important step to take PV panels. We propose an experimental study predict the amount using classical artificial neural network (ANN) and deep learning methods. panel data were collected at Duzce U...

A frame design technique for use with vector selection algorithms, for example Matching Pursuits (MP), is presented. The design algorithm is iterative and requires a training set of signal vectors. The algorithm, called Method of Optimal Directions (MOD), is an improvement of the algorithm presented in [1]. The MOD is applied to speech and electrocardiogram (ECG) signals, and the designed frame...

XGBoost algorithm and Lasso regression compare r-square, Mean Square Error (MSE), Root MSE, RMSLE values. The should be efficient enough to produce the exact fare amount of trip before starts. sample size for implementing this work was N=10 each groups considered. It iterated 20 times accurate prediction cab price with G power in 80% threshold 0.05%, CI 95% mean standard deviation. calculation ...

Spatial cross-validation and average-error statistics are examined with respect to their abilities to evaluate alternate spatial interpolation methods. A simple crossvalidation methodology is described, and the relative abilities of three, dimensioned error statistics—the root-mean-square error (RMSE), the mean absolute error (MAE), and the mean bias error (MBE)—to describe average interpolator...

This paper analyses three algorithms recently studied in the Computational Learning Theory community: the Gradient Descent (GD) Algorithm, the Exponentiated Gradient Algorithm with Positive and Negative weights (EG algorithm) and the Exponentiated Gradient Algorithm with Unnormalised Positive and Negative weights (EGU algorithm). The analysis is of the form used in the signal processing communi...