ВИКОРИСТАННЯ ІНСТРУМЕНТІВ ШТУЧНОГО ІНТЕЛЕКТУ В ПРОЦЕСАХ АНАЕРОБНОГО ЗБРОДЖУВАННЯ

Anaerobic digestion (AD) is a process that has found increasing relevance for sustainable waste management and bioenergy production. Nevertheless, microbial interactions and process dynamics make it challenging to maximize and predict biogas production. Recent breakthroughs in artificial intelligence (AI), particularly in artificial neural networks (ANN), have provided new opportunities for solving these problems and drastically enhanced process optimization, predictive capability, as well as perpetual stability. This paper aims to provide a review of recent literature covering the application of AI, specifically Artificial Neural Networks (ANN), integrated with various optimization algorithms, including Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), in anaerobic digestion systems from 2022 to 2024. The results of the evaluation demonstrate that ANN models exhibit a significant improvement over conventional kinetic-based approaches, characterized by lower prediction errors, higher biogas production, and greater robustness.