An Interval Type-2 Fuzzy LSTM Algorithm for Modeling Environmental Time-Series Prediction

A Safari, R Hosseini - Anthropogenic Pollution, 2022 - ap.ardabil.iau.ir
The statistical attributes of the non-stationary problems such as air quality and other natural
phenomena frequently changed. Type-2 fuzzy logic is a robust and capable model to cope …

[PDF][PDF] Evolutionary Interval Type-2 Fuzzy Rule Learning Approaches for Uncertain Time-Series Prediction

A Safari, R Hosseini - Signal Processing and Renewable Energy, 2023 - journals.iau.ir
Abstract This study presents Interval Type-2 Fuzzy Evolutionary models to manage
uncertainty in the process of uncertain time-series prediction. This study presents two type-2 …

[PDF][PDF] A Technical Review on Unsupervised Learning of Graph and Hypergraph Pattern Analysis

A Safari - Journal of Computer & Robotics, 2022 - journals.iau.ir
Graph and hypergraph matching are fundamental problems in pattern analysis problems.
They are applied to various tasks requiring 2D and 3D feature matching, such as image …

A Denoising Autoencoder Stacked Deep Learning Method for Clinical Trial Enrichment and Design Applied to Alzheimer's Disease

A Safari - Signal Processing and Renewable Energy, 2023 - oiccpress.com
In this research, we first present some background on the sample size estimation for
conducting clinical trials, discussing the necessity of a computational enrichment criterion …

[PDF][PDF] A State-of-the-Art Survey of Deep Learning Techniques in Medical Pattern Analysis and IoT Intelligent Systems

A Safari - Future Generation of Communication and Internet of …, 2023 - journals.iau.ir
Deep learning techniques have been concentrated on medical applications in recent years.
The proposed methodologies are inadequate while medical applications' evolutionary and …

[PDF][PDF] A Hybrid Type-2 Fuzzy-LSTM Model (HT2FLSTM) for Prediction of Environmental Temporal Patterns

A Safari, R Hosseini - journals.iau.ir
Computational intelligence methods, such as fuzzy logic and deep neural networks, are
robust models to solve real-world problems. In many dynamic and complex problems …

[PDF][PDF] A Denoising Autoencoder Stacked Deep Learning Method for Clinical Trial Enrichment and Design Applied to Alzheimer's

A Safari - journals.iau.ir
In this research, we first present some background on the sample size estimation for
conducting clinical trials, discussing the necessity of a computational enrichment criterion …