The conceptual model of agroecological properties of land. Methods

To solve the problem of automating the agroecological land estimation (natural resource potential) and creating intelligent information systems for their further programming, the necessary stage is the conceptualization of the domain knowledge (DK), or conceptual modelling. In this work, the conceptual model of DK “Agroecological properties of land”, developed on the basis of the abstract logical language UML and proposed in the previous part of the series of articles by the authors, is supplemented by the type of abstract objects “method”. The methods in UML reflect the types of relationships between data of various nature and are designed to distinguish the ways with which it is possible to fill in the missing data and information when solving practical problems in the framework of designing and building adaptive landscape farming systems. UML methods are considered for one of DK abstract classes – class “Relief”. In this class, 31 groups of input datasets and 23 groups of output datasets are suggested. All 54 datasets are based on the "method – attribute" connection that operate within this class or by abstract relationships between classes previously built into the conceptual model. This means that a class method as an abstract object defines a set of dependencies between data associated with the given class attributes, as input dataset, and data associated with the given or related class attributes, as output dataset. The elements of such set of dependencies can be deterministic or stochastic algorithms, statistical and other data processing methods, data analysis and artificial intelligence methods, as well as specific mathematical formulas. The technology of building a knowledge base by UML methods of class “Relief” is shown, containing 713 groups of UML methods classified by seven types, and also examples of UML methods of three different types are given.

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