Abstract—Crude oil can have great uses and applications, to achieve this it must undergo a process of conversion of primary to secondary energy called refining. Refining is the set of processes that are applied to crude oil in order to separate its useful components and adapt its characteristics to the needs of society. Among these products obtained from the refining process is gasoline, which is obtained using various types of catalysts. In this paper, we propose to use the Parallel System of Classification based on the Ensemble of Mixture of Experts (PCEM) developed in C using MPI (Message Passing Interface) that guarantees the obtaining of results that reflect the performance of a set of evaluated catalysts and thus proceed to the election of one that meets the industrial requirements of this process or propose improvements to this based on their behavior in the process. To carry out this system, it is proposed to use the Data Mining process on a repository of data obtained from a Catalytic Cracking Microactivity Reactor. Within the process of Data Mining is the task of classification of data, which was selected to be the engine of operation of the system proposed in this paper. We implemented a series of classifiers to compare the operation of the PCEM, that can predict new data between three different types of gasoline grades, obtaining in all the tests that the PCEM high rates in the performance measures with respect to the traditional classifiers.
Index Terms—Catalysts, catalytic cracking, classification, classifiers, computational simulations, data mining, computational simulations, microactivity reactor, refining.
Benjamin Moreno-Montiel and René MacKinney-Romero are with the Universidad Autónoma Metropolitana – Unidad Iztapalapa, Departamento de Ingeniería Eléctrica, Mexico (e-mail: email@example.com, firstname.lastname@example.org).
Carlos-Hiram Moreno-Montiel, is with Universidad Tecnológica de México – Plantel Sur, Ingeniería en Sistemas Computacionales, Mexico (e-mail: email@example.com).
Miriam Moreno-Montiel is with Instituto Politécnico Nacional, Departamento de Ingeniería Química Petrolera – ESIQIE, Mexico (e-mail: firstname.lastname@example.org).
Cite: Benjamin Moreno-Montiel, Carlos-Hiram Moreno-Montiel, Miriam-Noemi Moreno-Montiel, and René MacKinney-Romero, "Data Mining on Data of Catalytic Cracking Microactivity Reactors Using PCEM," International Journal of Environmental Science and Development vol. 10, no. 11, pp. 380-388, 2019.Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).