A comprehensive review of deep neuro-fuzzy system architectures and their optimization methods
Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …
A comparative study on deep learning models for text classification of unstructured medical notes with various levels of class imbalance
Background Discharge medical notes written by physicians contain important information
about the health condition of patients. Many deep learning algorithms have been …
about the health condition of patients. Many deep learning algorithms have been …
Predicting the trend of stock market index using the hybrid neural network based on multiple time scale feature learning
Y Hao, Q Gao - Applied Sciences, 2020 - mdpi.com
In the stock market, predicting the trend of price series is one of the most widely investigated
and challenging problems for investors and researchers. There are multiple time scale …
and challenging problems for investors and researchers. There are multiple time scale …
SHO-CNN: A metaheuristic optimization of a convolutional neural network for multi-label news classification
News media always pursue informing the public at large. It is impossible to overestimate the
significance of understanding the semantics of news coverage. Traditionally, a news text is …
significance of understanding the semantics of news coverage. Traditionally, a news text is …
Increasing text filtering accuracy with improved LSTM
How to eliminate useless information in the vast network information and retain effective
information is a problem that needs to be continuously explored in the field of deep learning …
information is a problem that needs to be continuously explored in the field of deep learning …
Evolutionary algorithm-based convolutional neural network for predicting heart diseases
Convolutional neural networks (CNNs) have been commonly used in medical decision
support systems to predict and diagnose different diseases with good precision. CNNs are …
support systems to predict and diagnose different diseases with good precision. CNNs are …
Ponzi contracts detection based on improved convolutional neural network
Y Lou, Y Zhang, S Chen - 2020 IEEE International Conference …, 2020 - ieeexplore.ieee.org
As one of the leading blockchain systems in operation, Ethereum has numerous smart
contracts deployed to implement a variety of functions. Unfortunately, speculators introduce …
contracts deployed to implement a variety of functions. Unfortunately, speculators introduce …
Deep learning neural network prediction system enhanced with best window size in sliding window algorithm for predicting domestic power consumption in a …
D Tomar, P Tomar, A Bhardwaj… - Computational …, 2022 - Wiley Online Library
Buildings are considered to be one of the world's largest consumers of energy. The
productive utilization of energy will spare the accessible energy assets for the following …
productive utilization of energy will spare the accessible energy assets for the following …
Bird sound classification based on ECOC-SVM
X Han, J Peng - Applied Acoustics, 2023 - Elsevier
Birds are an important part of the ecosystem. Knowing the number of existing bird species is
important for maintaining ecological balance. The sounds of birds contain rich biological …
important for maintaining ecological balance. The sounds of birds contain rich biological …
Hybrid method to automatically extract medical document tree structure
MY Landolsi, L Hlaoua, LB Romdhane - Engineering Applications of …, 2023 - Elsevier
A huge and rapidly growing quantity of medical documents is available in an electronic
versions. These informing documents mostly have textual content in natural language …
versions. These informing documents mostly have textual content in natural language …