Reglas de asociación y predicción utilizando series de tiempo.

The general objective of the development of this work of qualification is to support the productive activities of the small agricultural producers registered in the current system of the Ministry of Agriculture, through the development of an application based on the Rules of association and prediction using time series, which allows to establish base scenarios that evaluate the development of the data that are in the system, in order to help the planning and commercial management of different goods generated by small producers. At the market level, it provides them with certain competitive advantages, in front of the major marketers and intermediaries. This project, based on research and development, is designed, built and implemented an important reporting module for the system, using rules of association and prediction of sales performed; Data mining is used and to achieve this we help ourselves with WEKA, which is an open source library, issued under the GNU General Public License, which contains a collection of automatic learning algorithms, of which we use the a priori algorithm and the Support Vector Machine. Once the investigation about the properties, characteristics and operation of the library WEKA, proceeded to perform functional tests of association and prediction. For testing, dealing historical data real collected from the Ministry of Agriculture, implementing that information by way of rules as the basis of the results provided by the system developed.

• מחבר ראשי: Araujo Escobar, Eduardo Alfonso (author)
• פורמט: bachelorThesis
• שפה: spa
• יצא לאור: 2018
• נושאים: TECNOLOGÍA; INGENIERÍA; LENGUAJES DE PROGRAMACIÓN; PROGRAMACIÓN DE COMPUTADORAS
• גישה מקוונת: http://dspace.ups.edu.ec/handle/123456789/16017