人工智能方法在水利问题中的若干应用进展OA

As water conservancy enters a stage of high-quality development,the application of artificial intelligence quantitative calculation methods such as artificial neural networks,genetic algorithms in the field of water conservancy is becoming increasingly widespread,significantly promoting the in-depth development of smart water conservancy.Therefore,the research progress of the above methods are systematically reviewed in the modeling,optimization,qualitative empirical quantification,dialectical uncertainty relationship quantitative calculation,and stochastic simulation of complex water conservancy systems.Artificial neural networks can adaptively learn the input-output relationships of a system and are suitable for modeling complex water conservancy systems.Genetic algorithms possess robust population-based global optimization search capability and can be used to address optimization problems in complex water conservancy systems.Fuzzy mathematics transforms qualitative expert knowledge and relationships into quantitative operations using membership functions and fuzzy relations,promoting the theorization and scientification of hydrological and water-resources expertise.Set pair analysis can,through the identity-iscrepancy-contrary relationship and its operations,systematically describe and quantitatively characterize the dialectical uncertainty and the complex interconnections and transformations within water conservancy systems.Stochastic simulation can directly reproduce the complex features of real-world water conservancy systems and a variety of possible scenarios.The application and promotion of these artificial intelligence methods have effectively promoted the intelligent development of water conservancy engineering disciplines and provided important technical support for solving complex water conservancy problems.The above artificial intelligence methods are data-driven and directly simulate the functional mapping relationship between input and output of water conservancy problem system,without incorporating the mechanism of the variables studied in water conservancy problems.The actual application effect often lacks stability.In the field of smart water conservancy,the integration of"artificial intelligence methods+water conservancy professional models"is an important development trend.Only by coupling data-driven artificial intelligence methods with mechanism driven water conservancy professional models can we comprehensively utilize the relationship information of the three elements of research objects,research variables,and research objectives in water conservancy problems,and reveal the ternary structure principle of artificial intelligence methods by combining data analysis with physical analysis.