A new method for build NARMAX models based on metaheuristics. The algorithm uses a Binary hybrid Particle Swarm Optimization and Gravitational Search Algorithm with a new cost function to build parsimonious models.
New class for the BPSOGSA algorithm. New algorithms can be adapted in the Meta-MSS framework.
Future updates will add NARX models for classification and multiobjective model structure selection.
Added the new class AOLS to build NARX models using the Accelerated Orthogonal Least-Squares algorithm.
At the best of my knowledge, this is the first time this algorithm is used in the NARMAX framework. The tests I've made are promising, but use it with caution until the results are formalized into a research paper.
Added notebook with a simple example of how to use MetaMSS and a simple model comparison of the Electromechanical system.
Added notebook with a simple example of how to use AOLS
Added ModelInformation class. This class have methods to return model information such as max_lag of a model code.
added _list_output_regressor_code
added _list_input_regressor_code
added _get_lag_from_regressor_code
added _get_max_lag_from_model_code
Minor performance improvement: added the argument "predefined_regressors" in build_information_matrix function on base.py
to improve the performance of the Simulation method.
Pytorch is now an optional dependency. Use pip install sysidentpy['full']
Fix code format issues.
Fixed minor grammatical and spelling mistakes.
Fix issues related to html on Jupyter notebooks examples on documentation.
Updated Readme with examples of how to use.
Improved descriptions and comments in methods.
metaheuristics.bpsogsa (detailed description on code docstring)
v0.1.6
CONTRIBUTORS
MAJOR: Meta-Model Structure Selection Algorithm (Meta-MSS).
A new method for build NARMAX models based on metaheuristics. The algorithm uses a Binary hybrid Particle Swarm Optimization and Gravitational Search Algorithm with a new cost function to build parsimonious models.
New class for the BPSOGSA algorithm. New algorithms can be adapted in the Meta-MSS framework.
Future updates will add NARX models for classification and multiobjective model structure selection.
MAJOR: Accelerated Orthogonal Least-Squares algorithm.
Added the new class AOLS to build NARX models using the Accelerated Orthogonal Least-Squares algorithm.
At the best of my knowledge, this is the first time this algorithm is used in the NARMAX framework. The tests I've made are promising, but use it with caution until the results are formalized into a research paper.
Added notebook with a simple example of how to use MetaMSS and a simple model comparison of the Electromechanical system.
Added notebook with a simple example of how to use AOLS
Added ModelInformation class. This class have methods to return model information such as max_lag of a model code.
Minor performance improvement: added the argument "predefined_regressors" in build_information_matrix function on base.py to improve the performance of the Simulation method.
Pytorch is now an optional dependency. Use pip install sysidentpy['full']
Fix code format issues.
Fixed minor grammatical and spelling mistakes.
Fix issues related to html on Jupyter notebooks examples on documentation.
Updated Readme with examples of how to use.
Improved descriptions and comments in methods.
metaheuristics.bpsogsa (detailed description on code docstring)
FIX issue #52