Principal Component Analysis Enhanced Multi-layer Perceptron for Multi-economic Indicators in Southern African Economic Prediction
Software Engineering Perspectives in Intelligent Systems: Proceedings of 4th …, 2020•Springer
Economic growth may be determined based on different economic parameters. The main
purpose of this research work is to predict economic growth based on several economic
indicators. In this study, an enhanced Multi-layer Perceptron (MLP) model is built and the
prediction performances are evaluated and compared with existing models. Using the
Principal Component Analysis technique, major contributing indicators where identified and
passed as input to tne MLP input layer. Results show a better performance by the PCA …
purpose of this research work is to predict economic growth based on several economic
indicators. In this study, an enhanced Multi-layer Perceptron (MLP) model is built and the
prediction performances are evaluated and compared with existing models. Using the
Principal Component Analysis technique, major contributing indicators where identified and
passed as input to tne MLP input layer. Results show a better performance by the PCA …
Abstract
Economic growth may be determined based on different economic parameters. The main purpose of this research work is to predict economic growth based on several economic indicators. In this study, an enhanced Multi-layer Perceptron (MLP) model is built and the prediction performances are evaluated and compared with existing models. Using the Principal Component Analysis technique, major contributing indicators where identified and passed as input to tne MLP input layer. Results show a better performance by the PCA enhanced MLP with consistent accuracy as time-step increases. Furthermore, drop in GDP over the first 3 time-step and improvement in the last 3 time-step can be observed.
Springer
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