Artificial intelligence, the latest chapter of the technological revolution, has a tremendous potential to change every area of our lives. This article has focused on a specific form of artificial intelligence, namely generative intelligence, which facilitates the generation of content in all...

The utilisation of Chat Generative Pre-Trained Transformer (ChatGPT) and generative artificial intelligence (GenAI) technologies has started to demonstrate its impact across several domains. The swift shift and widespread implementation of efficient artificial intelligence (AI) present distinct...

Emerging technologies are in the core focus of supra-national innovation policies. These strongly rely on credible data bases for being effective and efficient. However, since emerging technologies are not yet part of any official industry, patent or trademark classification systems, delineating...

A new algorithm for calibrating agent-based models is proposed, which employs a popular gradient boosting framework. Machine learning techniques are not used to develop a surrogate model, but rather assist in narrowing down the parameter space during the search for optimal parameters. Our...

This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning...

In ensemble machine learning we combine decisions of experts to derive at a decision that is better than the individual ones. The process of combining these decisions can be as simple as majority voting or simple averaging or it can be more complicated and involve multiple steps. In this paper...

This paper develops several efficient machine learning models and compare their performance in forecasting the value and direction of stock prices and indices from the ASEAN countries. Although all models adequately forecast the stock indices ranging from 40% to 95% accuracy and outperform...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

Statistical learning models have profoundly changed the rules of trading on the stock exchange. Quantitative analysts try to utilise them predict potential profits and risks in a better manner. However, the available studies are mostly focused on testing the increasingly complex machine learning...