This article presents a review of the application of evolutionary computation methods to
solving financial problems. Genetic algorithms, genetic programming, multi-objective …

This paper reviews the application of artificial neural network (ANN) models to time series
prediction tasks. We begin by briefly introducing some basic concepts and terms related to …

A morphological neural network is generally defined as a type of artificial neural network that
performs an elementary operation of mathematical morphology at every node, possibly …

Fuzzy associative memories (FAMs) can be used as a powerful tool for implementing fuzzy
rule-based systems. The insight that FAMs are closely related to mathematical morphology …

This work presents an evolutionary morphological-rank-linear approach in order to
overcome the random walk dilemma for financial time series forecasting. The proposed …

A reasonable assessment of the hydrological regime alteration is a prerequisite for river
utilization, restoration, and protection. The hydrological alteration is quantified as changes in …

In this paper we propose a hybrid methodology to design morphological-rank-linear (MRL)
perceptrons in the problem of software development cost estimation (SDCE). In this …

In this paper, we present a method to overcome the random walk (RW) dilemma for financial
time series forecasting, called swarm-based translation-invariant morphological prediction …

Fuzzy associative memories (FAMs) belong to the class of fuzzy neural networks (FNNs). A
FNN is an artificial neural network (ANN) whose input patterns, output patterns, and/or …

Morphological associative memories (MAMs) are based on a lattice algebra known as
minimax algebra. In previous papers, we gained valuable insight into the storage and recall …