A proposal for the genetic lateral tuning of linguistic fuzzy systems and its interaction with rule selection
R Alcalá, J Alcalá-Fdez… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
Linguistic fuzzy modeling allows us to deal with the modeling of systems by building a
linguistic model which is clearly interpretable by human beings. However, since the …
linguistic model which is clearly interpretable by human beings. However, since the …
SGERD: A steady-state genetic algorithm for extracting fuzzy classification rules from data
EG Mansoori, MJ Zolghadri… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
This paper considers the automatic design of fuzzy-rule-based classification systems from
labeled data. The performance of classifiers and the interpretability of generated rules are of …
labeled data. The performance of classifiers and the interpretability of generated rules are of …
Hierarchical fuzzy rule-based system optimized with genetic algorithms for short term traffic congestion prediction
Taking practical and effective traffic prediction and control measures to ease highway traffic
congestion is a significant issue in the research field of Intelligent Transportation Systems …
congestion is a significant issue in the research field of Intelligent Transportation Systems …
Expert system for power quality disturbance classifier
Identification and classification of voltage and current disturbances in power systems are
important tasks in the monitoring and protection of power system. Most power quality …
important tasks in the monitoring and protection of power system. Most power quality …
Intrusion detection using a fuzzy genetics-based learning algorithm
Fuzzy systems have demonstrated their ability to solve different kinds of problems in various
applications domains. Currently, there is an increasing interest to augment fuzzy systems …
applications domains. Currently, there is an increasing interest to augment fuzzy systems …
A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: Degree of ignorance and lateral position
Fuzzy Rule-Based Systems are appropriate tools to deal with classification problems due to
their good properties. However, they can suffer a lack of system accuracy as a result of the …
their good properties. However, they can suffer a lack of system accuracy as a result of the …
A multiobjective evolutionary approach to concurrently learn rule and data bases of linguistic fuzzy-rule-based systems
In this paper, we propose the use of a multiobjective evolutionary approach to generate a set
of linguistic fuzzy-rule-based systems with different tradeoffs between accuracy and …
of linguistic fuzzy-rule-based systems with different tradeoffs between accuracy and …
Data mining and machine learning for identifying sweet spots in shale reservoirs
P Tahmasebi, F Javadpour, M Sahimi - Expert Systems with Applications, 2017 - Elsevier
Due to its complex structure, production form a shale-gas formation requires more drillings
than those for the traditional reservoirs. Modeling of such reservoirs and making predictions …
than those for the traditional reservoirs. Modeling of such reservoirs and making predictions …
ARIMA model estimation based on genetic algorithm for COVID-19 mortality rates
This paper presents a forecasting model for the mortality rates of COVID-19 in six of the top
most affected countries depending on the hybrid Genetic Algorithm and Autoregressive …
most affected countries depending on the hybrid Genetic Algorithm and Autoregressive …
On the use of machine learning methods to predict component reliability from data-driven industrial case studies
The reliability estimation of engineered components is fundamental for many optimization
policies in a production process. The main goal of this paper is to study how machine …
policies in a production process. The main goal of this paper is to study how machine …