Centro de Investigación Científica y de Educación Superior de Ensenada, Baja California
Año
Autores / Publicación
Echavarría Heras, H. A., Villa Diharce, E., Montesinos Lopez, A., & Leal Ramírez, C. (2024). An extended multiplicative error model of allometry: Incorporating systematic components, non-normal distributions, and piecewise heteroscedasticity. Biology Methods & Protocols, s/n(s/n), 10. doi: 10.1093/biomethods/bpae024. (ID: 29699)
Leal Ramírez, C., & Echavarría Heras, H. A. (2024). An Integrated Instruction and a Dynamic Fuzzy Inference System for Evaluating the Acquirement of Skills through Learning Activities by Higher Middle Education Students in Mexico. Mathematics, 12(7), 26. doi: 10.3390/math12071015. (ID: 29675)
Echavarría Heras, H. A., Leal Ramírez, C., Valencia Méndez, O., & Montiel Arzate, E. (2023). A Liebig's Principle of Limiting Factors based Single-Species Population Growth Model I: Qualitative Study of Trajectories and Fitting Results. Revista temporal DEP, 23(9), 25. https://journalspress.com/LJRS_Volume23/A-Liebigs-Principle-of-Limiting-Factors-based-Single-Species-Population-Growth-Model.pdf. (ID: 28845)
Carrillo Aguilar, L. A., Guerra Rosas, E., Álvarez Borrego, J., Echavarría Heras, H. A., & Hernández Muñoz, S. (2022). Identification of Shark Species Based on Their Dry Dorsal Fins through Image Processing. Applied Sciences. doi: 10.3390/app122211646. (ID: 28046)
Villa Diharce, E., Echavarría Heras, H. A., Montesinos Lopez, A., & Leal Ramírez, C. (2022). A Revision of the Traditional Analysis Method of Allometry to Allow Extension of the Normality-Borne Complexity of Error Structure: Examining the Adequacy of a Normal-Mixture Distribution-Driven Error Term. BioMed Research International, 2022(8310213), 31. doi: 10.1155/2022/8310213. (ID: 27903)
Leal Ramírez, C., Echavarría Heras, H. A., & Romero Escobar, H. M. (2022). A Mamdani Type-Fuzzy Inference - Alignment Matrix Method for Evaluation of Competencies Acquired by Students Enrolling at the Mexican Higher Middle Education System I: Formulation and Explanation Based on Simulation, and a Real but Incomplete Data Set. Computación y Sistemas, 2(2), 571-601. doi: 10.13053/CyS-26-2-4236. (ID: 27817)
Echavarría Heras, H. A., Leal Ramírez, C., Gomez, G., & Montiel Arzate, E. (2021). Principle of Limiting Factors-Driven Piecewise Population Growth Model I: Qualitative Exploration and Study Cases on Continuous-Time Dynamics. COMPLEXITY. doi: 10.1155/2021/5623783. (ID: 27216)
Leal Ramírez, C., & Echavarría Heras, H. A. (2021). On the Adequacy of a Takagi¿Sugeno¿Kang Protocol as an Empirical Identification Tool for Sigmoidal Allometries in Geometrical Space. In Castillo Oscar Melin Patricia (Eds.), Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications (pp. 315-336). Springer. (ID: 26896)
Leal Ramírez, C., Echavarría Heras, H. A., & Villa Diharce, E. (2020). Applying Fuzzy Logic to Identify Heterogeneity of the Allometric Response in Arithmetical Space. In Oscar Castillo Patricia Melin Janusz Kacprzyk (Eds.), Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications, Studies in Computational (pp. 11-34). Springer. (ID: 26027)
Echavarría Heras, H. A., Castro Rodriguez, J. R., Leal Ramírez, C., & Villa Diharce, E. (2020). Assessment of a Takagi-Sugeno-Kang fuzzy model assembly for examination of polyphasic loglinear allometry. PeerJ, 1(1), 50. doi: 10.7717/peerj.8173. (ID: 26026)
Echavarría Heras, H. A., Leal Ramírez, C., Villa Diharce, E., & Castro Rodriguez, J. R. (2019). A Generalized Model of Complex Allometry I: Formal Setup, Identification Procedures and Applications to Non-Destructive Estimation of Plant Biomass Units. Applied Sciences, 9(22), 42. doi: 10.3390/app9224965. (ID: 25144)
Echavarría Heras, H. A., Leal Ramírez, C., Villa Diharce, E., & Montesinos Lopez, A. (2019). Examination of the Effects of Curvature in Geometrical Space on Accuracy of Scaling Derived Projections of Plant Biomass Units: Applications to the Assessment of Average Leaf Biomass in Eelgrass Shoots. BioMed Research International, 2019(3613679), 23. doi: 10.1155/2019/3613679. (ID: 25146)
Montesinos Lopez, A., Villa Diharce, E., Echavarría Heras, H. A., & Leal Ramírez, C. (2018). Improved allometric proxies for eelgrass conservation. Journal of Coastal Conservation, 21. doi: 10.1007/s11852-018-0639-4. (ID: 23866)
Cazarez Castro, N. R., Odreman Vera, M., Cardenas Maciel, S., Echavarría Heras, H. A., & Leal Ramírez, C. (2018). Fuzzy Differential Equations as a Tool for Teaching Uncertainty in Engineering and Science. Computación y Sistemas, 22(2), 11. doi: 10.13053/CyS-22-2-2947. (ID: 23867)
Echavarría Heras, H. A., Leal Ramírez, C., Castro Rodriguez, J. R., Villa Diharce, E., & Castillo, O. (2018). A Takagi¿Sugeno-Kang Fuzzy Model Formalization of Eelgrass Leaf Biomass Allometry with Application to the Estimation of Average Biomass of Leaves in Shoots: Comparing the Reproducibility Strength of the Present Fuzzy and Related Crisp Proxies. In Oscar Castillo, Patricia Melin and Janusz Kacprzyk (Eds.), Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications (2 ed., pp. 329-362). Springer. (ID: 23868)