5 research outputs found
NARX neural networks for sequence processing tasks
This project aims at researching and implementing a neural network architecture system for the NARX
(Nonlinear AutoRegressive with eXogenous inputs) model, used in sequence processing tasks and particularly in
time series prediction. The model can fallback to different types of architectures including time-delay neural
networks and multi layer perceptron. The NARX simulator tests and compares the different architectures for
both synthetic and real data, including the time series of BSE30 index, inflation rate and lake Huron water level.
A guideline it's provided for any specialist in the fields of finance, weather forecasting, demography, sales,
physics, etc. in order for him to be able to predict and analyze the forecast for any numerical based statistic
A free trade area between the Repbulic of Moldova and the European Union: feasibility, perspectives and potential impact.
This publication has been launched within the project “European Union – Republic of Moldova Trade Relations: Current Situation and Perspectives for Enhancement”. The project is sponsored by the Moldova-Soros Foundation. The major goal of this project is to help Moldovan government formulate and adopt balanced and sound positions for the future negotiations with the European Commission, so that an “enhanced trade regime” contributing to the economic modernization of the country and economic integration with EU is achieved.free trade agreement; feasibility study; Moldova; European Union;
NARX neural networks for sequence processing tasks
This project aims at researching and implementing a neural network architecture system for the NARX
(Nonlinear AutoRegressive with eXogenous inputs) model, used in sequence processing tasks and particularly in
time series prediction. The model can fallback to different types of architectures including time-delay neural
networks and multi layer perceptron. The NARX simulator tests and compares the different architectures for
both synthetic and real data, including the time series of BSE30 index, inflation rate and lake Huron water level.
A guideline it's provided for any specialist in the fields of finance, weather forecasting, demography, sales,
physics, etc. in order for him to be able to predict and analyze the forecast for any numerical based statistic
NARX neural networks for sequence processing tasks
This project aims at researching and implementing a neural network architecture system for the NARX
(Nonlinear AutoRegressive with eXogenous inputs) model, used in sequence processing tasks and particularly in
time series prediction. The model can fallback to different types of architectures including time-delay neural
networks and multi layer perceptron. The NARX simulator tests and compares the different architectures for
both synthetic and real data, including the time series of BSE30 index, inflation rate and lake Huron water level.
A guideline it's provided for any specialist in the fields of finance, weather forecasting, demography, sales,
physics, etc. in order for him to be able to predict and analyze the forecast for any numerical based statistic