This article describes the features of classification methods and technologies, analytics Big data. Described group of methods and technologies, analytics Big data that are graded according to the functional relationships and formal model of information technology. The problem of the definition of ontology concepts analytics Big data.
The architecture and self-learning method of hybrid neuro-fuzzy systems for big fuzzy clustering in on-line mode are proposed in this paper. The architecture of proposed system represents the hybrid of the fuzzy general regression neural network and clustering self-organizing network. During a learning procedure in on-line mode, the proposed system tunes both its parameters and its architecture. For tuning of membership functions parameters of neuro-fuzzy system the method based on competitive learning is proposed.
The paper presents a brief description of engineering and scientific problems which arise at the steel plant PJSC “ArcelorMittal Kryvyi Rih” when organizing a repair workshop to fix industrial equipment.
The attention is paid to innovative methods of repair process based on intelligent agents and Industry 4.0 principles.
In this paper the contemporary technology to big data processing is analyzed. The software solution on Hadoop is developed. And the comparative results of the time efficiency in big data processing with Spark or Hive are described. The approaches to implement the software systems for big data processing with Spark or Hive are suggested.
The problem that led to a Big database has been described in the article. The NoSQL databases features and categories are outlined. Big data model "entity-characterization" is introduced. This model allows to determin the distance between the source data on the availability of information about a particular entity.