A comprehensive survey on higher order neural networks and evolutionary optimization learning algorithms in financial time series forecasting
The financial market volatility has been a focus of study for experts over past decades. While
stockbrokers and investors expect reliable projections of future stock indices, it instead …
stockbrokers and investors expect reliable projections of future stock indices, it instead …
High-performance time series prediction with predictive error compensated wavelet neural networks
Machine learning (ML) algorithms have gained prominence in time series prediction
problems. Depending on the nature of the time series data, it can be difficult to build an …
problems. Depending on the nature of the time series data, it can be difficult to build an …
Neural network techniques for time series prediction: A review
It is important to predict a time series because many problems that are related to prediction
such as health prediction problem, climate change prediction problem and weather …
such as health prediction problem, climate change prediction problem and weather …
Quadratic residual multiplicative filter neural networks for efficient approximation of complex sensor signals
MU Demirezen - IEEE Access, 2023 - ieeexplore.ieee.org
In this research, we present an innovative Quadratic Residual Multiplicative Filter Neural
Network (QRMFNN) to effectively learn extremely complex sensor signals as a low …
Network (QRMFNN) to effectively learn extremely complex sensor signals as a low …
A novel error-output recurrent neural network model for time series forecasting
It is a well-known fact that improving forecasting accuracy is an important yet often
challenging issue. Extensive research has been conducted using neural networks (NNs) to …
challenging issue. Extensive research has been conducted using neural networks (NNs) to …
[PDF][PDF] A novel job-shop scheduling strategy based on particle swarm optimization and neural network
Z Zhang, ZL Guan, J Zhang, X ** capability. Ridge polynomial neural network (RPNN) is an important kind …
Using new artificial bee colony as probabilistic neural network for breast cancer data classification
H Shah - Frontiers in Engineering and Built Environment, 2021 - emerald.com
Purpose Breast cancer is an important medical disorder, which is not a single disease but a
cluster more than 200 different serious medical complications. Design/methodology …
cluster more than 200 different serious medical complications. Design/methodology …
Nonlinear autoregressive moving-average (narma) time series forecasting using neural networks
In this paper, a one-step forecasting comparison using a simulated nonlinear autoregressive
moving-average time series (NARMA) was conducted between two groups of neural …
moving-average time series (NARMA) was conducted between two groups of neural …