Prediction of bridge pier scour depth is essential for safe and economical bridge design. Keeping in mind the complex nature of bridge scour phenomenon, there is a need to properly address the methods and techniques used to predict bridge pier scour. Up to the present, extensive research has been carried out for pier scour depth prediction. Different modeling techniques have been applied to ach...

Clustering analysis is an effective method to discover and identify tumor classes. So, this paper proposes a Fuzzy C-Means clustering (FCM) algorithm based on Non-negative matrix factorization (NMF). Firstly, gene expression profiling (GEP) is simply processed through mean and variance of gene expression, which can then be mapped into a low dimensional space by NMF method. Finally, for discover...

Conventionally, many researchers have used both regression and black box techniques to estimate the unconfined compressive strength (UCS) of different rocks. The advantage of the regression approach is that it can be used to render a functional relationship between the predictive rock indices and its UCS. The advantage of the black box techniques is in rendering more accurate predictions. Gene ...

The traditional evolutionary algorithms dividing the complex networks community have some inevitable deficiencies such as low searching accuracy, high computing time complexity, local optimal solution and so on. To address this issue, this paper proposes a novel community structure partition algorithm based on multi-gene families (MGF). First, this algorithm respectively encodes the network ent...

The scour modelling in cohesive beds is relatively more complex than that in sandy beds and thus there is limited number of studies available on local scour at bridge abutments on cohesive sediment. Recently, a good progress has been made in the development of data-driven techniques based on artificial intelligence (AI). It has been reported that AI-based inductive modelling techniques are freq...

The problem we tackle concerns forecasting time series in financial markets. AutoRegressive Moving-Average (ARMA) methods and computational intelligence have also been used to tackle this problem. We propose a novel method for time series forecasting based on a hybrid combination of ARMA and Gene Expression Programming (GEP) induced models. Time series from financial domains often encapsulate d...

IMPORTANCE We report our experience with uveal melanoma-specific gene expression profile (GEP) testing on a series of choroidal metastatic tumors confirmed by cytopathology so that clinicians may be aware that receiving a class 1 or class 2 test result in nonmelanoma is possible. OBSERVATIONS Retrospective review of all cytopathology and DecisionDx-UM GEP reports between January 2012 to Decem...

Abstract The presence of emitters along the lateral, as well connectors manifold, causes additional local head losses other than friction losses. An accurate estimation is crucial importance for a correct design microirrigation systems. This paper presents procedure to assess caused by 6 lateral start 32- and 40-mm nominal diameter each under actual hydraulic working conditions based on artific...

Fly ash (FA) is a residual from thermal industries that has been effectively utilized in the production of FA-based geopolymer concrete (FGPC). To avoid time-consuming and costly experimental procedures, soft computing techniques, namely, random forest regression (RFR) gene expression programming (GEP), are used this study to develop an empirical model for prediction compressive strength FGPC. ...

The modeling and analysis of lifetimes is an important aspect of statistical work in a wide variety of scientific and technological fields. For the first time the Kum-GEP distribution is introduced and studied. This distribution can have a decreasing and upside-down bathtub failure rate function depending on the value of its parameters; it's including some special sub-model like exponentiated P...