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The ASM Method is a practical and scientifically well-founded systems engineering method that bridges the gap between the two ends of system development: . the human understanding and formulation of real-world problems (requirements capture by accurate high-level modeling at the level of abstraction determined by the given application domain)
Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]
In any MDA approach we have essentially two kinds of models: initial models are created manually by human agents while derived models are created automatically by programs. For example, an analyst may create a UML initial model from its observation of some loose business situation while a Java model may be automatically derived from this UML ...
Abstraction inversion for an anti-pattern of one danger in abstraction; Abstract data type for an abstract description of a set of data; Algorithm for an abstract description of a computational procedure; Bracket abstraction for making a term into a function of a variable; Data modeling for structuring data independent of the processes that use it
A model is an abstraction of phenomena in the real world; a metamodel is yet another abstraction, highlighting the properties of the model itself. A model conforms to its metamodel in the way that a computer program conforms to the grammar of the programming language in which it is written.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
A deterministic abstract machine is a system in which a particular beginning state or condition always yields the same outputs. There is no randomness or variation in how inputs are transformed into outputs. [5] In contrast, a non-deterministic abstract machine can provide various outputs for the same input on different executions. [2]
H2O.ai is an open-source data science and machine learning platform; KNIME is a machine learning and data mining software implemented in Java. Massive Online Analysis (MOA) is an open-source project for large scale mining of data streams, also developed at the University of Waikato in New Zealand. Neural Designer is a data mining software based ...