Improving the Efficiency of the K-medoids Clustering Algorithm by Getting Initial Medoids. - Joaquín Pérez Ortega; Nelva Nely Almanza Ortega; Jessica Adams-López; Moisés González-García; Adriana Mexicano; Socorro Sáenz-Sánchez; José María Rodríguez-Lelis (WorldCIST (1), 2017)

A-means: improving the cluster assignment phase of k-means for Big Data. - Joaquín Pérez Ortega; Nelva Nely Almanza Ortega; Jorge A. Ruiz-Vanoye; Rodolfo A. Pazos Rangel; Socorro Sáenz-Sánchez; José María Rodríguez-Lelis; Alicia Martínez Rebollar (Int. J. Comb. Optim. Probl. Informatics, 2018)

Prediction of Diabetes Mortality in Mexico City Applying Data Science. - Joaquín Pérez Ortega; Andrea Vega-Villalobos; Nelva Nely Almanza Ortega; Rodolfo A. Pazos Rangel; José Crispín Zavala Díaz; José María Rodríguez-Lelis; Yasmín Hernández (IWAIPR, 2021)

Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine. - José Crispín Zavala Díaz; Joaquín Pérez Ortega; Nelva Nely Almanza Ortega; Rodolfo A. Pazos Rangel; José María Rodríguez-Lelis (Entropy, 2022)

A New Criterion for Improving Convergence of Fuzzy C-Means Clustering. - Joaquín Pérez Ortega; Carlos Fernando Moreno-Calderón; Sandra Silvia Roblero Aguilar; Nelva Nely Almanza Ortega; Juan Frausto Solís; Rodolfo A. Pazos Rangel; José María Rodríguez-Lelis (Axioms, 2024)