Machine learning: a catalyst for green economy tranformation with implications for the Republic of Moldova

Objective: The modern world is witnessing a remarkable surge in the doption of machine learning (ML) techniques, driven by advancements in computational power and data availability. The aim of this article is to develop a conceptual model for transforming the economy of the Republic of Moldova into a green economy, using artificial intelligence (AI). This model aims to provide recommendations for the implementation of the National Development Strategy "European Moldova 2030" and the Energy Strategy of the Republic of Moldova until 2030 policies. In order to achieve the set goal, the following specific objectives are proposed: - Define machine learning (ML) algorithms to support the achievement of the objectives of the National Development Strategy "European Moldova 2030" and the Energy Strategy of the Republic of Moldova until 2030; - To exemplify how to apply the identified algorithms in order to facilitate the achievement of the strategic objectives in the following directions: energy efficiency, renewable energy, sustainable agriculture, waste management and smart transportation. Method: The techniques employed in this article include: logical-deductive reasoning, observation, analogy, comparative analysis, graphical and tabular methods, historical analysis, synthesis, modelling. Results: The result of the research entails the development of a conceptual model to facilitate the Republic of Moldova's transition to a green economy. It highlights opportunities for leveraging machine learning in pivotal domains, including energy, agriculture, waste, and transportation, in alignment with national development strategies. Originality: Our study presents an original approach to the integration of machine learning techniques in the context of the green economy of Moldova. While the application of machine learning in green economy initiatives has been explored in various contexts, our research focuses on its potential and relevance specifically in the Republic of Moldova.