Bogart Yail Márquez

Fuzzy Models for Complex Social Systems Using Distributed Agencies in Poverty Studies

There are several ways to model a complex social system, as is the poverty of an entity, the object of this paper is to present a methodology consisting of several techniques that offers to solve complex social problems with soft computing.

Methodology for Measuring the Quality of Education Using Fuzzy Logic

Fuzzy logic has been considered as a strategy to define the values of the complex realities that define every aspect of education and to demonstrate formalized educational issues. This is because the quality of education has awakened the interest of investigators worldwide because they can be the answer of Education problems, and because some countries spend more resources in funding education compared to others which leads to higher levels of growth. This article proposes a new methodology using fuzzy logic to measure the quality of education by using quantitative and qualitative values with the hopes to develop criteria for the quality of education in a way closer to the realities of Latin American countries.

On the Multi-Agent Modelling of Complex Knowledge Society for Business and Management System Using Distributed Agencies

This work is motivated by need for a model that addresses the study of Knowledge Society for Business and Management in situations where conventional analysis is insufficient in describing the intricacies of realistic social phenomena and social actors. We use Distributed Agency methodology that requires the use of all available computational techniques and interdisciplinary theories. We use Data Mining and Neuro-Fuzzy System as an approach to discover and assign rules on agents that represent real-world companies. The case study is based on several companies in the region of Baja California, Mexico and in the policies they implement to achieve greater competitiveness based on the development of knowledge.

Modeling the Employment Using Distributed Agenciesand Data Mining

There are several ways to model a complex social system, as is the employment. This work is motivated by need to establish a model for the study of social and economic systems in situations where conventional analysis is insufficient; this paper is to present a methodology applied to complex social problems with soft computing.

Tijuana’s Sustainability for Healthcare Measurement Using Fuzzy Systems

The proposed methodology is focus as an alternative to analyze and describe the most accurate social phenomena according our reality using different computational mathematical theories, which are not used conventionally in social sciences applications and this is a new approach to create new computer’s simulation architectures.

Comparing regression using artificial neural nets and intelligent hybrid method to achieve the higher learning preferences of students

This work compares an artificial neural net and computational intelligence hybrid method to describe the learning preferences of students from survey data. The final purpose is to give learning objects to students according to their learning style. We used a database form survey with answers from 1042 computational engineers students from two public Universities in Tijuana, Mexico. We also used the Fuzzy Inference System (FIS); the FIS is configured from survey data using the ANFIS method to discover the set up and fuzzy if-then rules of the system. The FIS describe learning objects preferences for learning styles; then we compared the results from ANN versus ANFIS, in order to retrieve the highest results to build learning objects.

Sustainable System Modelling for Urban Development Using Distributed Agencies

Developing a sustainable simulation system consists essentially of generating sustainable, artificial worlds with the capacity to produce results similar to those observed in the real world. This allows for varying parameters in a controlled, reusable experimental environment, something that cannot be easily achieved through mathematical models. The field of simulation is broad and multidisciplinary and has had an impressive growth since the 90’s. While the area of simulation has been expanding to new horizons in traditional systems research, there are yet a series of unsolved epistemological issues David et al. (2010).

eLearning Virtual Environments Multi-agent Model

The objective of this research is to propose a multi-agent model implemented in a virtual environment to assess and demonstrate how significant the learning of users has ehanced their aquired knowledge. This paper explains how to implement the use of multi-agents. It will discuss how the curriculum can be enriched by activities involving problem-based learning, case studies simulations and virtual reality. This new model provides multiple uses for exploring knowledge and supporting learning-by-doing. It engages users in the construction of knowledge, collaboration, and articulation of knowledge.