Víctor M. Rivas

2.2k citations

23 papers · 1.6k indexed · 1 hit paper · h-index 10

Artificial Intelligence top 1%
Computational Theory and Mathematics top 1%
Information Systems top 5%
Computer Vision and Pattern Recognition top 5%
Management Science and Operations Research top 5%

Co-authors: María José del Jesús Juan Carlos Fernández Fernández Francisco Herrera Cristóbal Romero Josep M. Garrell Jaume Bacardit Salvador García José Otero
Topics: Neural Networks and Applications (12 papers)Evolutionary Algorithms and Applications (9 papers)Stock Market Forecasting Methods (5 papers)
Cited by: Artificial Intelligence Computational Theory and Mathematics Management Science and Operations Research
Journals: Journal of the American College of Cardiology Information Sciences Fuzzy Sets and Systems
Partner nations: Spain United States Mexico

In The Last Decade

Víctor M. Rivas

23 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

KEEL: a software tool to assess evolutionary algorithms for data mining problems

2008 1.2k citations María José del Jesús, Víctor M. Rivas et al. Soft Computing profile →

Peers

Countries citing papers authored by Víctor M. Rivas

Since Specialization

Citations

This map shows the geographic impact of Víctor M. Rivas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Víctor M. Rivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Víctor M. Rivas more than expected).

Fields of papers citing papers by Víctor M. Rivas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Víctor M. Rivas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Víctor M. Rivas. The network helps show where Víctor M. Rivas may publish in the future.

Co-authorship network of co-authors of Víctor M. Rivas

This figure shows the co-authorship network connecting the top 25 collaborators of Víctor M. Rivas. A scholar is included among the top collaborators of Víctor M. Rivas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Víctor M. Rivas. Víctor M. Rivas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	EDG-002, A NOVEL TARGETED SARCOMERE REGULATOR PRESERVES INTRINSIC MYOSIN-MOTOR FUNCTION, BLUNTS HYPERCONTRACTILITY AND ELIMINATES LVOT OBSTRUCTION IN CATS WITH HYPERTROPHIC CARDIOMYOPATHY: IN VITRO AND IN VIVO EVIDENCE 2023 ·Journal of the American College of Cardiology ·(unknown),(unknown),(unknown),(unknown),(unknown),Natalie A. Hawryluk,Stephen T. Schlachter,Víctor M. Rivas,(unknown),(unknown),Samantha P. Harris,(unknown),Carlos del Río,Alan J. Russell,Marc Evanchik	1
2	Time series forecasting using evolutionary neural nets implemented in a volunteer computing system 2017 ·Intelligent systems in accounting, finance and management ·Víctor M. Rivas,(unknown),J. J. Merelo,M. G. Arenas,P. García‐Fernández	8
3	Ranking the Performance of Compiled and Interpreted Languages in Genetic Algorithms 2016 ·J. J. Merelo,(unknown),Pedro Á. Castillo,G. Romero,Pablo García‐Sánchez,Víctor M. Rivas,Mario García-Valdéz,(unknown),(unknown)	1
4	A comparison of implementations of basic evolutionary algorithm operations in different languages 2016 ·J. J. Merelo,(unknown),Pedro Á. Castillo,G. Romero,Víctor M. Rivas,Mario García-Valdéz,(unknown),(unknown)	3
5	Open classroom: enhancing student achievement on artificial intelligence through an international online competition 2014 ·Journal of Computer Assisted Learning ·(unknown),T. J. Mateo Sanguino,J. J. Merelo,Víctor M. Rivas	27
6	NodEO, a multi-paradigm distributed evolutionary algorithm platform in JavaScript 2014 ·J. J. Merelo,Pedro Á. Castillo,Antonio M. Mora,Anna I. Esparcia-Alcázar,Víctor M. Rivas	7
7	Gonadal Steroids Differentially Modulate the Actions of OrphaninFQ/Nociceptin at A Physiologically Relevant Circuit Controlling Female Sexual Receptivity 2014 ·Journal of Neuroendocrinology ·(unknown),Víctor M. Rivas,Malika Kachani,Kevin Sinchak,Edward J. Wagner	13
8	Short, medium and long term forecasting of time series using the L-Co-R algorithm 2013 ·Neurocomputing ·(unknown),Víctor M. Rivas,M. G. Arenas,María José del Jesús	14
9	Coevolution of lags and RBFNs for time series forecasting: L-Co-R algorithm 2011 ·Soft Computing ·(unknown),M. G. Arenas,Víctor M. Rivas,María José del Jesús	6
10	Comparison of response surface methodology and artificial neural network applied to enzymatic hydrolysis of rapeseed straw 2010 ·Journal of Biotechnology ·Eulógio Castro,Cristóbal Cara,María José del Jesús,Víctor M. Rivas	1
11	Time series forecasting: Automatic determination of lags and radial basis neural networks for a changing horizon environment 2010 ·(unknown),Víctor M. Rivas	5
12	E-tsRBF: Preliminary Results on the Simultaneous Determination of Time-Lags and Parameters of Radial Basis Function Neural Networks for Time Series Forecasting 2009 ·(unknown),Víctor M. Rivas,María José del Jesús	1
13	EvRBF: evolving RBF neural networks for classification problems 2007 ·Víctor M. Rivas,M. G. Arenas,J. J. Merelo,A. Prieto	4
14	Finding a needle in a haystack using hints and evolutionary computation: the case of evolutionary MasterMind 2005 ·Applied Soft Computing ·J. J. Merelo,Pedro Á. Castillo,Víctor M. Rivas	9
15	Evolving two-dimensional fuzzy systems 2003 ·Fuzzy Sets and Systems ·Víctor M. Rivas	5
16	G-Prop-II: global optimization of multilayer perceptrons using GAs 2003 ·Pedro Á. Castillo,Víctor M. Rivas,J. J. Merelo,Jesús González,A. Prieto,G. Romero	9
17	G-Prop: Global optimization of multilayer perceptrons using GAs 2000 ·Neurocomputing ·Pedro Á. Castillo,J. J. Merelo,A. Prieto,Víctor M. Rivas,G. Romero	98
18	Evolving Multilayer Perceptrons 2000 ·Neural Processing Letters ·Pedro Á. Castillo,(unknown),J. J. Merelo,A. Prieto,Víctor M. Rivas,G. Romero	40
19	G-Prop-III: global optimization of Multilayer Perceptrons using an evolutionary algorithm 1999 ·Pedro Á. Castillo,Víctor M. Rivas,J. J. Merelo,Jesús González,A. Prieto,G. Romero	6
20	A neural net-based model for decision making in marketing 1998 ·J. J. Merelo,A. Prieto,Víctor M. Rivas,(unknown)	3

About Víctor M. Rivas

Víctor M. Rivas is a scholar working on Artificial Intelligence, Signal Processing and Management Science and Operations Research, having authored 23 papers that have together received 1.6k indexed citations. Recurring topics across this work include Neural Networks and Applications (12 papers), Evolutionary Algorithms and Applications (9 papers) and Stock Market Forecasting Methods (5 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computational Theory and Mathematics (385 citations) and Management Science and Operations Research (149 citations). Víctor M. Rivas has collaborated with scholars based in Spain, United States and Mexico. Frequent co-authors include María José del Jesús, Juan Carlos Fernández Fernández, Francisco Herrera, Cristóbal Romero, Josep M. Garrell, Jaume Bacardit, Salvador García, José Otero, Luciano Sánchez and Sebastián Ventura. Their work appears in journals such as Journal of the American College of Cardiology, Information Sciences and Fuzzy Sets and Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact