Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories
Bloat is an excess of code growth without a corresponding improvement in fitness. This is a
serious problem in Genetic Programming, often leading to the stagnation of the evolutionary …
serious problem in Genetic Programming, often leading to the stagnation of the evolutionary …
[PDF][PDF] An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross‐validation experiment
Global climate models (GCMs) are the primary tools to simulate multi-decadal climate
dynamics and to generate global climate change projections under different future emission …
dynamics and to generate global climate change projections under different future emission …
Examining feasibility of develo** a rock mass classification for hard rock TBM application using non-linear regression, regression tree and generic programming
A Salimi, J Rostami, C Moormann… - Geotechnical and …, 2018 - Springer
Geotechnical and geological parameters have the greatest impact on the performance of
hard rock tunnel boring machines (TBMs). This includes the rock and rock mass properties …
hard rock tunnel boring machines (TBMs). This includes the rock and rock mass properties …
Automatic feature extraction using genetic programming: An application to epileptic EEG classification
This paper applies genetic programming (GP) to perform automatic feature extraction from
original feature database with the aim of improving the discriminatory performance of a …
original feature database with the aim of improving the discriminatory performance of a …
Open issues in genetic programming
It is approximately 50 years since the first computational experiments were conducted in
what has become known today as the field of Genetic Programming (GP), twenty years since …
what has become known today as the field of Genetic Programming (GP), twenty years since …
Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology-Part 1: Concepts and methodology
A comprehensive data driven modeling experiment is presented in a two-part paper. In this
first part, an extensive data-driven modeling experiment is proposed. The most important …
first part, an extensive data-driven modeling experiment is proposed. The most important …
Prediction of soil–water characteristic curve using genetic programming
In this technical note, a genetic programming (GP) approach is employed to predict the soil–
water characteristic curve (SWCC) of soils. The GP model requires an input terminal set that …
water characteristic curve (SWCC) of soils. The GP model requires an input terminal set that …
Towards an ensemble based system for predicting the number of software faults
SS Rathore, S Kumar - Expert Systems with Applications, 2017 - Elsevier
Software fault prediction using different techniques has been done by various researchers
previously. It is observed that the performance of these techniques varied from dataset to …
previously. It is observed that the performance of these techniques varied from dataset to …
JCLEC: a Java framework for evolutionary computation
In this paper we describe JCLEC, a Java software system for the development of
evolutionary computation applications. This system has been designed as a framework …
evolutionary computation applications. This system has been designed as a framework …
Application of genetic programming to predict the uniaxial compressive strength and elastic modulus of carbonate rocks
The measures and estimates of the uniaxial compressive strength (UCS i) and elasticity
modulus (E i) of intact rock are regarded as the most widely used design parameters in the …
modulus (E i) of intact rock are regarded as the most widely used design parameters in the …