Stability of the soil slopes is one of the most challenging issues in civil engineering projects.
Due to the complexity and non-linearity of this threat, utilizing simple predictive models does …

As new generations of technology appear, legacy knowledge management solutions and
applications become increasingly out of date, necessitating a paradigm shift. Machine …

Current study aimed to combine the multi-layer Perceptron (MLP) neural network technique
with five metaheuristic computational algorithms, namely invasive weed optimization (IWO …

Having a reliable approximation of heating load (HL) and cooling load (CL) is a substantial
task for evaluating the energy performance of buildings (EPB). Also, the appearance of soft …

The use of aircraft operation logs to develop a data-driven model to predict probable failures
that could cause interruption poses many challenges and has yet to be fully explored. Given …

Time series prediction using machine learning: a case of Bitcoin returns | Emerald Insight Books
and journals Case studies Expert Briefings Open Access Publish with us Advanced search Time …

This paper effectively uses the data mining and optimization methods to investigate a
classification based on decision trees algorithm, then optimizes by the method of grid search …

One of the main areas where machine learning (ML) techniques are used vastly is in
prediction of diseases. Diabetic neuropathy (DN) disease is a complication of diabetes …

Diabetes is a serious disease which is increasing at an alarming rate all over the world and
it may cause some longterm issues such as affecting the eyes, heart, kidneys, brain, feet and …

Objective When developing prediction models, researchers commonly employ a single
model which uses all the available data (end-to-end approach). Alternatively, a similarity …