In recent years, Bitcoin has become the most widely used blockchain platform in business
and finance. The goal of this work is to find a viable prediction model that incorporates and …

We discuss issues of modular learning in artificial neural networks and explore possibilities
of the partial use of modules when the computational resources are limited. The proposed …

The article presents the artificial neural networks performance optimization using wavelet
transform. The existing approaches of wavelet transform implementation in neural networks …

Ensuring an adequate food supply for humans remains a significant challenge for society.
Accurately forecasting rice yield is crucial for effective planning and decision-making by …

The goal of this paper is to predict electrical energy consumption using nonlinear
autoregressive (NAR) models. The practical section contains historical data on Iraq's annual …

Youth unemployment significantly impacts the socio-economic stability and growth of
developing countries, particularly Iraq. This study aims to predict the youth unemployment …

Forecasting economic indicators like Gross Domestic Product (GDP) is crucial for planning
and decision-making by policymakers, investors, and businesses. Traditional econometric …

This paper aims to enhance the accuracy and reliability of gas production predictions for Iraq
until 2030 by comparing traditional time series methods (ARIMA) with a hybrid artificial …

This paper focuses on population forecasting for Iraq until 2030, using artificial intelligence
techniques to align with the UN's Sustainable Development Goals (SDGs). It compares the …

Wavelet neural networks are a unique combination of wavelet analysis and neural network
architectures, thus providing the benefits of advanced signal processing. Unlike traditional …