About the Journal
Aim and Scope
IETI Transactions on Data Analysis and Forecasting (iTDAF) is a peer-reviewed open access journal that aims to publish manuscripts in all aspects of data analysis and forecasting. Research must be of high quality and context that would interest worldwide readership. This journal aims to contribute to theory and practice and bridge the gap between the academic ivory tower and the real world, making data analysis and forecasting useful for the future. The iTDAF covers all types of data analysis and forecasting, including but not limited to the following topics: big data, business, deep learning, machine learning, neural network, social sciences, sustainability, and time series; that are applied in different areas such as health, finance, economics, business, sustainability, climate change, environment, engineering and technology, management, tourism.
iTDAF is an Open Access Journal. Online readers don't have to pay any fee.
List of Topics/Keywords
- Big data analysis and forecasting
- Business data analysis and forecasting
- Climate change analysis and forecasting
- Computational social sciences and forecasting
- Computer simulation and prediction
- Data mining and deep learning
- Decision support systems
- Deep Learning
- Environment data analysis and forecasting
- Sustainability analysis forecasting
- Technology innovation analysis and forecasting
- Mathematical modeling, data analysis and business Mathematics
iTDAF is a quarterly journal.
iTDAF is the official journal of International Engineering and Technology Institute, Science Development Foundation under the President of the Republic of Azerbaijan, and China Biodiversity Conservation and Green Development Foundation.