Fuzzy logic model of assessment soil salinatization

• Main Authors: Muhamediyeva, Dilnoz, Samijonov, Abdurashid, Bakhtiyorov, Shakhzodbek, Alimbaev, Kamal
• Format: Conference Proceeding
• Language: English
• Subjects: Fuzzy logic; Fuzzy set theory; Fuzzy sets; Land management; Salinity; Soils
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0210432

The article discusses the construction of a fuzzy logic model for assessing soil population. The developed model for assessing soil salinity, based on the Mamdani fuzzy logic apparatus, represents a significant step in solving the problem of classifying and assessing the degree of soil salinity. Fuzzy logic allows for uncertainty and fuzziness in data and rules to be taken into account, which is especially important in areas where precise numerical values can be difficult to determine. The model works with linguistic data, such as “low” or “medium” salinity, which makes the results more visual and understandable for users. The "black box" characterization of the model makes it easy to interpret results without the need for deep mathematical knowledge, making it accessible to a wide range of users. The model’s flexibility and adaptability allow rules and inputs to be quickly changed to adapt to different situations and conditions. It is important to note that the model not only provides qualitative estimates, but also allows you to obtain quantitative results in a fuzzy form, which enriches the information and increases the accuracy of the conclusions. The use of fuzzy set theory provides a scientific basis for the model, making it more consistent and reliable. These advantages make the Mamdani fuzzy logic model a powerful tool for estimating soil salinity. It can be useful in various fields, including agriculture, ecology and land management, where the analysis and recording of soil salinity is important for decision-making and improving the quality of land resources.