Sentence examples for Computational intelligence models from inspiring English sources

Computational intelligence models [12] utilize logic tree [13], [14], neural networks [15], an ensemble learning approach [15] or evolutionary algorithms [16] to discover correlations between SNPs and hereditary disorders and provide potential biological insight for the observed correlation and/or causation.

The proposed approach is designed to address some of the problems that currently exist in the area of inferential modelling through the fusion of statistical and computational intelligence models.

Therefore, the ability and acceptable performance of using the MLP-ANN as an accurate model for estimating Hydrogen Sulfide solubility in ILs was showed versus other computational intelligence models.

To use computational intelligence models for the classification and identification of endophenotype (relationships between phenotype and genetic markers) in patients with rheumatoid arthritis and healthy controls from genetic information, primarily the DRB1 HLA (human leukocyte antigen) and the shared epitope theory.

In this paper, a comparison between two types of bio-inspired computational intelligence models including genetic programming (GP) and artificial neural network (ANN) models was implemented to estimate the velocity field within a constructed wetland (i.e., the Stormwater Treatment Area in South Florida) in the Everglades, Florida.

Recently, important research on dynamic networks and Intelligent Transportation Systems using computational intelligence modeling techniques has been done.

The book discusses real-world problems and exploratory research in computational intelligence and mathematical models.

The results presented are of theoretical and practical value to researchers and industrial practitioners working in the fields of artificial intelligence, collective computational intelligence, innovative business models, new digital and knowledge economy and, in particular, agent and multi-agent systems, technologies, tools and applications.

It is an excellent domain for testing new approaches in modeling, optimization, artificial intelligence, computational intelligence, and simulation.

To this end, many studies have been conducted including those concentrate on implementing computational intelligence methods to model the response of suction caissons under loading.

The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation.