Educational Alternatives ISSN 1314-7277, Volume 15, 2017 Journal of International Scientific Publications www.scientific-publications.net Page 181 FUZZY LOOK-UP TABLE FOR KNOWLEDGE MANAGEMENT AND DECISION MAKING Pascual Noradino Montes Dorantes 1,2 , Marco Aurelio Jiménez Gómez 2 , Adriana Mexicano Santoyo 2 , Gerardo Maximiliano Méndez 3 1 Universidad Autónoma del Noreste. División de Estudios de posgrado e investigación. Blvd. José Musa de León y General Medardo de la Peña S/N Col. Los Pinos, CP 25100, Saltillo, Coahuila, México. 2 Instituto Tecnológico de Ciudad Victoria/División de estudios de posgrado e investigación. Boulevard Emilio Portes Gil #1301 Pte. A.P. 175, C.P. 87010, Ciudad Victoria, Tamaulipas, México. Ph. (52) 834 153 2000 ext. 306. 3 Instituto Tecnológico de Nuevo León, Av. Eloy Cavazos 2001, Guadalupe, Nuevo León, México. Posgrado en Ingeniería Mecatrónica. Abstract The knowledge management is one of the most important tasks in education. The main problem presented in this process is the transmission of the knowledge and the understanding of the student. In this area, the interpretation produces variations of a concept and this condition produces errors. The use of the expert systems provides an interpretation with a degree of freedom to evaluate a concept and allows the knowledge management without expertise. The results obtained show that the expert approach provides an evaluation with a tolerable variation accepted by the principal organizations dedicated to measurement and standardization. Key words: knowledge management, uncertainty reduction, T1 SFLS, Fuzzy, Teaching-learning process 1. INTRODUCTION The knowledge management represents a challenge for the enterprises such as educational centers. The expert systems arise to contain and generate knowledge. In this sense there are some approaches as the evolutionary computing and its evolutionary strategies proposed by Rechenberg, I. (1973), the genetic algorithms (GA), proposed by Holland (1992), artificial neural networks (ANN) proposed by Mc Culloc & Pitts (1946), and the fuzzy logic (FL) proposed by Lofty Zadeh (1965) all of them well knowns as being capable of manage knowledge. Fuzzy logic is known as having the advantage of providing a chance to use linguistic in evaluation of knowledge. The knowledge management is generated via mathematical calculus in order to obtain a standardized response that is converted on a linguistic response after evaluation, this happens because the word means different things to different people (Mendel, 2001: 68; Mendel, 2007) see, fig. 1 and the uncertainties. In literature there are several examples of it on of these examples are the linguistic codification of the height of the people (Fig. 2). See, Mendel, (2001:25). Fig. 1. Variations in the interpretation of a concept, obtained by expert poll Source: Mendel, JM. (2007).