AI-BASED DATA ANALYSIS OF A FRACTAL-FRACTIONAL ORDER CONTAMINATION TRANSPORTATION AND SEDIMENTATION MODEL FOR RIVERS

Analysis of the water quality in rivers is important for people from all walks of life. The level of contamination is affecting human lives, animals, plants and ecosystem. In this paper, we consider the contamination transportation in rivers and sedimentation by the help of mathematical modeling, qualitative theoretical analysis, simulations and artificial intelligence. The model is composed of four classes of variables. The first variable is [Formula: see text], representing contamination concentration in the water, the second one [Formula: see text] is sediment concentration, The third variable [Formula: see text] is velocity of the fluid and the fourth one [Formula: see text] is the decay rate. The model is considered in the Fractal-Fractional (FF) sense of derivative of FF-orders [Formula: see text] and investigated for the mathematical results including the existence of solution, uniqueness of solution, stability of Hyers–Ulam types, numerical simmulations, and finally, AI is applied for the analysis of the accuracy of the results and error in the patterns of the computational data, as a process innovation.