Artificial intelligence is a branch of computer science that attempts to understand the
essence of intelligence and produce a new intelligent machine capable of responding in a …

Sedimentary petrology is the basis for most mineral and textural identification in sandstones.
Automating mineralogical interpretation of an entire thin section image has many practical …

Correct identification macerals is important for analyzing petrographic characteristics of coal.
Traditional methods based on manual measurement are time-consuming and physically …

Automatic identification of coal macerals has been a long-term pursuit for coal petrologists.
As the rapid developments of computational processing capacities and algorithms in recent …

Fine‐grained sediment (mud) and lithified equivalents (mudrock, mudstone, and shale)
contain components similar to ones in coarser sedimentary materials, albeit of such small …

Coal ash content is an important criterion for evaluating coal quality. In recent years, the
online ash measurement approach based on a convolutional neural network (CNN) has …

Analyzing the photomicrographs of coal and conducting maceral analysis are essential
steps in understanding the coal's characteristics, quality, and potential uses. However, due …

The aim of the study was to analyse the effect of temperature on the sorption and diffusion of
CO 2 and CH 4 on hard coal. Four coal samples, characterized by various degrees of …

Featured Application Maceral Analysis; Coal Processing. Abstract An intelligent analytical
technique which is able to accurately identify maceral components is highly desired in the …

In this study, the ilmenite content in beach placer sand was estimated using seven soft
computing techniques, namely random forest (RF), artificial neural network (ANN), k-nearest …