Computational intelligence (CI) techniques have positively impacted the petroleum reservoir
characterization and modeling landscape. However, studies have showed that each CI …

This work demonstrates the capabilities of two hybrid models as Computational Intelligence
tools in the prediction of two important oil and gas reservoir properties, viz., porosity and …

Functional networks are a general framework useful for solving a wide range of problems in
probability, statistics, and engineering applications. In this article, we demonstrate that …

The deluge of multi-dimensional data acquired from advanced data acquisition tools
requires sophisticated algorithms to extract useful knowledge from such data. Traditionally …

We develop a modified differential evolution algorithm that produces radial basis function
neural network controllers for chaotic systems. This method requires few controlling …

This paper proposes functional networks as novel intelligence paradigm scheme for
landslide displacement prediction. They evaluate unknown neuron functions from given …

This work utilizes the capabilities of Data Mining and Computational Intelligence in the
prediction of two important petroleum reservoir characteristics, viz., porosity and …

The hybridization of two or more Computational Intelligence (CI) techniques to build a single
model has increased in popularity over the recent years. Such models that combine the best …

In recent years, functional networks have emerged as an extension of artificial neural
networks (ANNs). In this article, we apply both network techniques to predict the catches of …

The high-temperature aspects of the Casimir force between two neutral conducting walls are
studied. The mathematical model of" inert" ideal-conductor walls, considered in the original …