Accurately predicting the particle size distribution of a muck-pile after blasting is always an
important subject for mining industry. Adaptive neuro-fuzzy inference system (ANFIS) has …

Machine learning (ML) techniques have been utilized for the crop monitoring and yield
estimation/prediction using remotely sensed data. However, these methods have been …

The complex impacts of disease stages and disease symptoms on spectral characteristics of
the plants lead to limitation in disease severity detection using the spectral vegetation …

This paper deals with the prediction of surface roughness in manufacturing polycarbonate
(PC) by applying Bayesian optimization for machine learning models. The input variables of …

In the present study, random forest regression (RFR), support vector regression (SVR) and
artificial neural network regression (ANNR) models were evaluated for the retrieval of soil …

Media visual sculpture is a landscape element with high carbon emissions. To reduce
carbon emission in the process of creating and displaying visual art and structures (visual …

Anesthesia induction is associated with frequent blood pressure fluctuation such as
hypotension and hypertension. If it is possible to precisely predict blood pressure a few …

Price is the key factor in financial activities. Unexpected fluctuation in price is the sign of
market instability. Nowadays Machine learning provides enormous techniques to forecast …

Identifying the products which are highly sold in the fashion apparel industry is one of the
challenging tasks, which leads to reduce the write off and increases the revenue. In fact …

One of the main challenges in short-term electrical load forecasting is extraction of nonlinear
relationships and complex dependencies among different time instances of the load time …