Accurate prediction of mercury content emitted from fossil-fueled power stations is of the
utmost importance for environmental pollution assessment and hazard mitigation. In this …

Settlement simulating in cohesion materials is a crucial issue due to complexity of cohesion
soil texture. This research emphasis on the implementation of newly developed machine …

This work presents proposing two artificial intelligence methods including Least squares
support vector machine (LSSVM) and Adaptive neuro fuzzy inference system (ANFIS) for the …

Asphaltene precipitation is one of the major problems in petroleum industry that causes
significant costs to the petroleum industry. Numerous researches have been done by …

The present work suggested predicting models based on machine learning algorithms
including the least square support vector machine (LSSVM), artificial neural network (ANN) …

This study presents a coupled invasive weed optimization-adaptive neuro fuzzy inference
system method to simulate physical habitat in streams. We implement proposed method in …

Asphaltene precipitation and its subsequent deposition are considered as one of the most
problematic issues in the oil industry because it cause frequent production interruptions and …

Accurate determinations of water (H2O) content in natural gases especially in the methane
(CH4) phase are highly important for chemical engineers dealing with natural gas …

One of the problematic concerns in petroleum industries is the deposition of heavy fractions
of crude oil such as asphaltene fraction during production and transportation. The utilization …

The different tasks of petroleum engineers such as well testing and simulation are highly
function of reservoir fluids properties so the accuracy of these properties can affect the oil …