Hybrid Model for Making Decision Methods in Wireless Sensor Networks Through Neuro-Fuzzy Inference System
Abstract
Considering the complexity and multiple alternatives for technology decisions in Wireless Sensor Networks (WSNs), a multicriteria selection method (MCDM) is an appropriate approach for choosing the best option in technical projects. Purely quantitative decision-making procedures have currently been created based on client requirements and recommendations from industry professionals in many domains. In this context, implementation and operational costs could be increasing due to technical problems and additional processes. In order to prevent future difficulties and obtain a more accurate technology selection, a new method was being developed to involve qualitative and quantitative parameters taken from real scenarios and technical literature review and optimized with a Neuro-Fuzzy Inference Systems using Mamdani Approach (NFIS) design. This dissertation provides a detailed description of the Multicriteria Decision methods as AHP, ANP, Vikor, and others. In addition, the process to generate data for NFIS systems, and the Hybrid methodology designed, including the economic analysis, are explained.
Subject Area
Electrical engineering|Computer Engineering
Recommended Citation
Lozano, Martha Lucia Torres, "Hybrid Model for Making Decision Methods in Wireless Sensor Networks Through Neuro-Fuzzy Inference System" (2022). ETD Collection for University of Texas, El Paso. AAI29999650.
https://scholarworks.utep.edu/dissertations/AAI29999650