Interval type-2 fuzzy neural networks for chaotic time series prediction: A concise overview
Chaotic time series widely exists in nature and society (eg, meteorology, physics,
economics, etc.), which usually exhibits seemingly unpredictable features due to its inherent …
economics, etc.), which usually exhibits seemingly unpredictable features due to its inherent …
[HTML][HTML] DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring
Credit scoring (CS) is an effective and crucial approach used for risk management in banks
and other financial institutions. It provides appropriate guidance on granting loans and …
and other financial institutions. It provides appropriate guidance on granting loans and …
Design of type-3 fuzzy systems and ensemble neural networks for COVID-19 time series prediction using a firefly algorithm
In this work, information on COVID-19 confirmed cases is utilized as a dataset to perform
time series predictions. We propose the design of ensemble neural networks (ENNs) and …
time series predictions. We propose the design of ensemble neural networks (ENNs) and …
Hybrid deep learning and empirical mode decomposition model for time series applications
Time series forecasting is important in many aspects of our lives, since it can be used to deal
with the uncertainty to further support the decision making. Despite many advanced …
with the uncertainty to further support the decision making. Despite many advanced …
Optimization using the firefly algorithm of ensemble neural networks with type-2 fuzzy integration for COVID-19 time series prediction
In this paper, the latest global COVID-19 pandemic prediction is addressed. Each country
worldwide has faced this pandemic differently, reflected in its statistical number of confirmed …
worldwide has faced this pandemic differently, reflected in its statistical number of confirmed …
A novel model for stock price prediction using hybrid neural network
The foremost challenge for investors is to select stock price by analyzing financial data
which is a menial task as of distort associated and massive pattern. Thereby, selecting stock …
which is a menial task as of distort associated and massive pattern. Thereby, selecting stock …
Fuzzy system for classification of nocturnal blood pressure profile and its optimization with the crow search algorithm
I Miramontes, P Melin, G Prado-Arechiga - Soft Computing Applications …, 2021 - Springer
Over time, different metaheuristics have been used for optimization in different soft
computing techniques, such as fuzzy systems and neural networks. In this work we focus on …
computing techniques, such as fuzzy systems and neural networks. In this work we focus on …
[HTML][HTML] Comparison of Interval Type-3 Mamdani and Sugeno Models for Fuzzy Aggregation Applied to Ensemble Neural Networks for Mexican Stock Exchange Time …
In this work, interval type-2 and type-3 fuzzy systems were designed, of Mamdani and
Sugeno types, for time series prediction. The aggregation performed by the type-2 and type …
Sugeno types, for time series prediction. The aggregation performed by the type-2 and type …
Particle swarm optimization of modular neural networks for obtaining the trend of blood pressure
I Miramontes, P Melin, G Prado-Arechiga - Intuitionistic and type-2 fuzzy …, 2020 - Springer
In this work, the optimization of a modular neural network for obtaining the trend of blood
pressure is presented. Three modules are used, the first for obtaining the systolic pressure …
pressure is presented. Three modules are used, the first for obtaining the systolic pressure …
Modular granular neural network optimization using the firefly algorithm applied to time series prediction
In this chapter the combination of modular neural network, granular computing, and a firefly
algorithm is presented to perform time series prediction. The Mackey–Glass time series is …
algorithm is presented to perform time series prediction. The Mackey–Glass time series is …