Simple and multiple regression: application in the prediction of natural variables related to microalgae growing process


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Bibliographic Details
Authors: Carrasquilla-Batista, Arys, Chacón-Rodríguez, Alfonso, Núñez-Montero, Kattia, Gómez-Espinoza, Olman, Valverde-Cerdas, Johnny, Guerrero-Barrantes, Maritza
Format: artículo
Status:Versión publicada
Publication Date:2016
Description:Nowadays, there is a growing need in various research fields and in the industry of precision agriculture to record and process data from multiple sensors, sensors sometimes located in remote areas, miles apart from each other. The usual approach to sensor data recording implies measurement of each variable in separate equipment, making it difficult and expensive to integrate and process jointed data. The possibility of incorporating the theme of Internet of Things (I.oT.) in research is being analyzed to take advantage of the ubiquitous computing capabilities available today. This article is about simple regression and multiple regression models, which offer the bases to explore the relationship between variables associated to microalgae kinetic growth: temperature, light, pH and dissolved oxygen. Recorded data will provide new approaches to present works; in this way, researchers will perform various data analysis online.
Institution:Instituto Tecnológico de Costa Rica
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Access Level:acceso abierto
Keyword:Microalgae; simple regression; multiple regression; predictive variables
Microalgas; regresión simple; regresión múltiple; variables predictivas