Multiple regression approach has been used to forecast the crop production widely. This study undertaken evaluate performance of stepwise and Lasso (Least absolute shrinkage selection operator) technique in variable development wheat model for yield using weather data period 1984-2015, collected from IARI, New Delhi. Statistical parameters viz. R2, RMSE, MAPE were 0.81, 195.90 4.54 per cent res...

Electric vehicles (EVs) and hybrid (HEVs) are being increasingly utilized for various reasons. The main reasons their implementation that they consume less or do not fossil fuel (no carbon dioxide pollution) cause sound pollution. However, this technology has some challenges, including complex troublesome accurate state of health estimation, which is affected by different factors. According to ...

An analog and mixed-signal (AMS) circuit that draws on machine learning while using a regression model differs in terms of the design compared to more sophisticated designs. Technology structures are advanced than conventional CMOS processes, specifically fin field-effect transistor (FinFET) silicon-on-insulator (SOI), have been proposed provide higher computation performance required meet vari...

in the present work, the effects of operating conditions including ph, transmembrane pressure, oil concentration, and temperature on fouling resistance and the rejection of turbidity for a polymeric membrane in an ultrafiltration system of wastewater treatment were studied. a new modeling technique called evolutionary polynomial regression (epr) was investigated. epr is a method based on regres...

Main objectives of feature extraction in signal regression are the improvement of accuracy of prediction on future data and identification of relevant parts of the signal. A feature extraction procedure is proposed that uses boosting techniques to select the relevant parts of the signal. The proposed blockwise boosting procedure simultaneously selects intervals in the signal’s domain and estima...

Applications are given of a formula for the exact probability density function of the maximum likelihood estimates of a statistical model, where the data generating model is allowed to differ from the estimation model. The main examples are supported by simulation experiments. Curved exponential families are investigated, for which an approach is described that can be used in many practical sit...