title: An evolutionary morphological approach for software development cost estimation.
abstract: In this work we present an evolutionary morphological approach to solve the software development cost estimation (SDCE) problem. The proposed approach consists of a hybrid artificial neuron based on framework of mathematical morphology (MM) with algebraic foundations in the complete lattice theory (CLT), referred to as dilation-erosion perceptron (DEP). Also, we present an evolutionary learning process, called DEP(MGA), using a modified genetic algorithm (MGA) to design the DEP model, because a drawback arises from the gradient estimation of morphological operators in the classical learning process of the DEP, since they are not differentiable in the usual way. Furthermore, an experimental analysis is conducted with the proposed model using five complex SDCE problems and three well-known performance metrics, demonstrating good performance of the DEP model to solve SDCE problems.
authors.affiliation: Informatics Center, Federal University of Pernambuco, Recife, PE, Brazil. raa@cin.ufpe.br
authors.forename: Ricardo de A
authors.initials: Rde A
authors.lastname: Araújo
authors.forename: Adriano L I
authors.initials: AL
authors.lastname: Oliveira
authors.forename: Sergio
authors.initials: S
authors.lastname: Soares
authors.forename: Silvio
authors.initials: S
authors.lastname: Meira
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003365:Costs and Cost Analysis / Q000379:methods*; D016208:Databases, Factual; D008957:Models, Genetic; D015233:Models, Statistical; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D012984:Software / Q000191:economics*