Intelligent data analysis for selecting suitable marine sites for mariculture: The use of Aidos intelligent system in Saudi Arabia as a case study

A severe shortage of fresh water, high evaporation, minimal annual rainfall, absence of rivers, and extreme heat force farmers in Saudi Arabian to cultivate fish, shellfish, shrimp, and other seafood in sea cages. The long coastline along the Arabian Peninsula, with favorable hydrological conditions that ensure stable sea temperatures and oxygen levels, as well as good water exchange, facilitates the implementation of mariculture projects at a lower cost. To ensure high productivity, a suitable marine site for mariculture must be selected. However, many factors are numerical and linguistic and could be vague and fuzzy, making it difficult to formalize the solution. This study aimed to apply automated systems-cognitive analysis to select a suitable marine site that will ensure high mariculture productivity. To achieve this goal, ten mathematical models were synthesized in the Aidos intelligent system, among which, the INF7 model demonstrated the highest identification reliability, and their validity was selected. Of the 120 marine areas included in the training set, 46 were deemed suitable for mariculture, 32 were deemed satisfactory, 25 were deemed poor, and 17 were deemed unacceptable. The results of this study can be used worldwide, as the Aidos system is freely available online, and the user interface can be customized to the most commonly used language.