N
Nibaldo Rodriguez
Researcher at Pontifical Catholic University of Valparaíso
Publications - 70
Citations - 567
Nibaldo Rodriguez is an academic researcher from Pontifical Catholic University of Valparaíso. The author has contributed to research in topics: Autoregressive model & Wavelet. The author has an hindex of 11, co-authored 70 publications receiving 499 citations. Previous affiliations of Nibaldo Rodriguez include Valparaiso University.
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Monthly catch forecasting of anchovy Engraulis ringens in the north area of Chile: Non-linear univariate approach
Juan Carlos Gutiérrez-Estrada,Claudio Silva,Eleuterio Yáñez,Nibaldo Rodriguez,Inmaculada Pulido-Calvo +4 more
TL;DR: In this article, the performance of computational neural networks (CNNs) models to forecast 1-month ahead monthly anchovy catches in the north area of Chile considering only anchovy catch in previous months as inputs to the models was analyzed.
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Collaborative particle swarm optimization with a data mining technique for manufacturing cell design
TL;DR: The computational results show that the PSO algorithm is able to find the optimal solutions in almost all instances, and its use in machine grouping problems is feasible.
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Neural networks for cost estimation of shell and tube heat exchangers
TL;DR: This model proved that neural networks are capable of reducing uncertainties related to the cost estimation of a shell and tube heat exchangers through the application of artificial neural networks.
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Anchovy (Engraulis ringens) and sardine (Sardinops sagax) abundance forecast off northern Chile: A multivariate ecosystemic neural network approach
Eleuterio Yáñez,Francisco Plaza,Juan Carlos Gutiérrez-Estrada,Nibaldo Rodriguez,M.A. Barbieri,Inmaculada Pulido-Calvo,Cinthya Bórquez +6 more
TL;DR: In this article, an evaluation of the performance of artificial neural networks (ANNs) to forecast monthly anchovy (Engraulis ringens) and sardine (Sardinops sagax) catches in northern Chile (18°21′S-24°S) is presented, using environmental variables, including anchovy and Sardine CPUE, fishing effort and catches.
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Application of Genetic Algorithms for the DARPTW Problem
TL;DR: This work applies data pre-processing techniques to reduce the search space to points that are feasible regarding time windows constraints, and shows competitive results on Cordeau & Laporte benchmark datasets while improving processing times.