There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …

The induction of decision trees is a widely-used approach to build classification models that
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …

We present an integrated algorithm for simultaneous feature selection (FS) and designing of
diverse classifiers using a steady state multiobjective genetic programming (GP), which …

D ynamic W orkflow S cheduling in F og C omputing (DWSFC) is an important optimisation
problem with many real-world applications. The current workflow scheduling problems only …

This paper investigates the use of genetic programming in automatized synthesis of
heuristics for the parallel unrelated machines environment with arbitrary performance …

This paper presents the development and verification of a new multi-stage genetic
programming (MSGP) technique, called MSGP-LASSO, which was applied for univariate …

The management and analysis of big data has been identified as one of the most important
emerging needs in recent years. This is because of the sheer volume and increasing …

Supervised learning problems can be faced by using a wide variety of approaches
supported in machine learning. In recent years there has been an increasing interest in …

Genetic Programming (GP) is gaining increased attention as an effective method for
inducing classifiers for data classification. However, the manual design of a genetic …

The objectives of this paper are to investigate the capability of genetic programming to select
and extract linearly separable features when the evolutionary process is guided to achieve …