scholarly journals A fuzzy rule-based system to predict energy consumption of genetic programming algorithms

2018 ◽  
Vol 15 (3) ◽  
pp. 635-654 ◽  
Author(s):  
Josefa Álvarez ◽  
Franciso Chávez ◽  
Pedro Castillo ◽  
Juan García ◽  
Francisco Rodriguez ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Evolutionary Algorithms ◽  
Genetic Programming ◽  
Fuzzy Rule ◽  
Energy Awareness ◽  
Environmentally Conscious ◽  
Rule Based ◽  
Rule Based System ◽  
Proposed Model ◽  
Programming Algorithms

In recent years, the energy-awareness has become one of the most interesting areas in our environmentally conscious society. Algorithm designers have been part of this, particularly when dealing with networked devices and, mainly, when handheld ones are involved. Although studies in this area has increased, not many of them have focused on Evolutionary Algorithms. To the best of our knowledge, few attempts have been performed before for modeling their energy consumption considering different execution devices. In this work, we propose a fuzzy rulebased system to predict energy comsumption of a kind of Evolutionary Algorithm, Genetic Prohramming, given the device in wich it will be executed, its main parameters, and a measurement of the difficulty of the problem addressed. Experimental results performed show that the proposed model can predict energy consumption with very low error values.

scholarly journals Interpretability and Accuracy Analysis of Fuzzy Rule Based System Designed for Abalone

2020 ◽  
Vol 8 (5) ◽  
pp. 1335-1340
Keyword(s):  
Fuzzy Rule ◽  
Vital Role ◽  
Rule Based ◽  
Rule Based System ◽  
Proposed Model ◽  
Human Decision ◽  
Fuzzy Partitions ◽  
Accuracy Assessments ◽  
Improved Accuracy ◽  
Rule Based Systems

Fuzzy Rule Based Systems are playing vital role in the implementation of human decision making. The development of interpretable Fuzzy Rule Based Systems with improved accuracy is a crucial research aspect in fuzzy based systems. Mamdani type fuzzy rule based systems are used to implement the proposed model. In this manuscript a FRBS is implemented with Guaje Open-Access Java based software. The interpretability and accuracy assessments are recorded on the different experiments with various rule generation methods, like Fuzzy decision tree and Wang Mendel method. The results are found satisfactory and a trade-off is handled between interpretability and accuracy. The major concern of the experimentation is number and type of fuzzy partitions. K-means and Hierarchical Fuzzy Partitions are used in the experiments with three and five number of fuzzy partitions.

scholarly journals Genetic fuzzy rule-based system using MOGUL learning methodology for energy consumption forecasting

2019 ◽  
Vol 8 (1) ◽  
pp. 55
Author(s):  
Aria JOZI ◽  
Tiago PINTO ◽  
Isabel PRAÇA ◽  
Francisco SILVA ◽  
Brigida TEIXEIRA ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Rule Based System

scholarly journals A Fuzzy Rule-Based System for Classification of Diabetes

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8095
Author(s):  
Khalid Mahmood Aamir ◽  
Laiba Sarfraz ◽  
Muhammad Ramzan ◽  
Muhammad Bilal ◽  
Jana Shafi ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Early Diagnosis ◽  
Early Stage ◽  
Fuzzy Rule ◽  
Healthcare Sector ◽  
Diagnostic Process ◽  
Rule Based ◽  
Rule Based System ◽  
Proposed Model ◽  
Early Diagnosis Of Diabetes

Diabetes is a fatal disease that currently has no treatment. However, early diagnosis of diabetes aids patients to start timely treatment and thus reduces or eliminates the risk of severe complications. The prevalence of diabetes has been rising rapidly worldwide. Several methods have been introduced to diagnose diabetes at an early stage, however, most of these methods lack interpretability, due to which the diagnostic process cannot be explained. In this paper, fuzzy logic has been employed to develop an interpretable model and to perform an early diagnosis of diabetes. Fuzzy logic has been combined with the cosine amplitude method, and two fuzzy classifiers have been constructed. Afterward, fuzzy rules have been designed based on these classifiers. Lastly, a publicly available diabetes dataset has been used to evaluate the performance of the proposed fuzzy rule-based model. The results show that the proposed model outperforms existing techniques by achieving an accuracy of 96.47%. The proposed model has demonstrated great prediction accuracy, suggesting that it can be utilized in the healthcare sector for the accurate diagnose of diabetes.

A fuzzy rule-based system to assess e-government technical interoperability maturity level

2014 ◽  
Vol 8 (3) ◽  
pp. 335-356 ◽  
Author(s):  
Andreiwid Sheffer Corrêa ◽  
Alexandre de Assis Mota ◽  
Lia Toledo Moreira Mota ◽  
Pedro Luiz Pizzigatti Corrêa
Keyword(s):  
Fuzzy Rule ◽  
Assessment Process ◽  
Maturity Model ◽  
Maturity Level ◽  
Rule Based ◽  
Content Type ◽  
Management Level ◽  
Rule Based System ◽  
Brazilian Government ◽  
Information And Communication

Purpose – The purpose of this study is to present a system called NEBULOSUS, which is a fuzzy rule-based expert system for assessing the maturity level of an agency regarding technical interoperability. Design/methodology/approach – The study introduces the use of artificial intelligence and fuzzy logic to deal with the imprecision and uncertainty present in the assessment process. To validate the system proposed and demonstrate its operation, the study takes into account the Brazilian technical interoperability maturity model, based on the Brazilian Government Interoperability Framework (GIF). Findings – With the system proposed and its methodology, it could be possible to increase the assessment process to management level and to provide decision-making support without worrying about technical details that make it complex and time-consuming. Moreover, NEBULOSUS is a standalone system that offers an easy-to-use, open and flexible structuring database that can be adapted by governments throughout the world. It will serve as a tool and contribute to governments’ expectations for continuous improvement of their technologies. Originality/value – This study contributes toward filling a gap in general interoperability architectures, which is a means to provide an objective method to evaluate GIF adherence by governments. The proposed system allows governments to configure their technical models and GIF to assess information and communication technology resources.

Assessing flood vulnerability using a rule-based fuzzy system

2012 ◽  
Vol 66 (8) ◽  
pp. 1766-1773 ◽  
Author(s):  
J. Yazdi ◽  
S. A. A. S. Neyshabouri
Keyword(s):  
Fuzzy Rule ◽  
Vulnerability Analysis ◽  
Human Knowledge ◽  
Small Watershed ◽  
Flood Vulnerability ◽  
Rule Based ◽  
Rule Based System ◽  
Vulnerability Map ◽  
Flood Prone Areas

Population growth and urbanization in the last decades have increased the vulnerability of properties and societies in flood-prone areas. Vulnerability analysis is one of the main factors used to determine the necessary measures of flood risk reduction in floodplains. At present, the vulnerability of natural disasters is analyzed by defining the various physical and social indices. This study presents a model based on a fuzzy rule-based system to address various ambiguities and uncertainties from natural variability, and human knowledge and preferences in vulnerability analysis. The proposed method is applied for a small watershed as a case study and the obtained results are compared with one of the index approaches. Both approaches present the same ranking for the sub-basin's vulnerability in the watershed. Finally, using the scores of vulnerability in different sub-basins, a vulnerability map of the watershed is presented.

Sign in / Sign up

Export Citation Format

Share Document