MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series Prediction
An ANFIS Model for Stock Price Prediction
Prediction of multidimensional time-series data using a recurrent neural network (RNN) trained by real-time recurrent learning (RTRL), unbiased online recurrent optimization (UORO), least mean squares (LMS), or multivariate linear regression. The optimal hyper-parameters are selected using grid search with parallel processing.
Generalized Implementation of RNNs for Chaotic Time Series Prediction
NESTORE is a MATLAB package capable to estimate, during ongoing of an aftershock sequence following a damaging earthquake, the likelihood of the occurrence of another strong earthquake.
Forecasting SARS-CoV-2 Next Wave in Iran and the World Using TSK Fuzzy Neural Networks
Multidimensional time-series data prediction with a recurrent neural network (RNN) trained by RTRL; 2nd repo in a series of 3 repos associated with the research article "Prediction of the motion of chest internal points using an RNN trained with RTRL for latency compensation in lung cancer radiotherapy" (Pohl et al, Comput Med Imaging Graph, 2021)
Machine Learning-based research for UPMC
Implementation of time series forecasting using some artificial neural networks from Mathworks MATLAB toolbox.
A MatLab package for System Identification using linear and nonlinear auto-regresive models (N)AR, (N)ARX and (N)ARMAX models
Forecasting the Euro Area Yield Curve Using the Heath-Jarrow-Morton Model
It is a sorting-out of gradually complicated models generated from base function. The best model is indicated by the minimum of the external criterion characteristic. Multilayered procedure is equivalent to the Artificial Neural Network with polynomial activation function of neurons.
The abstract Heath-Jarrow-Morton model: Calibration and forecasting the US daily Treasury yield curve rates
A MATLAB toolbox for HMMs, CHMMs & LSIMs in multi-channel data processing, modeling & classification
Future frame prediction in 2D cine-MR images using the PCA respiratory motion model and online learning algorithms for RNNs, and time series forecasting using the latter
D-FENSE is a repository for dengue data in Brazil, enabling predictive modeling, visualization, and public health support.
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