The article presents the results of the study of the possibilities of using neural networks to solve the problem of determining the active set of a wind farm (WF), taking into account the efficiency of each wind turbines (WT).
artificial neural networks
The automated translation, speech recognition and synthesis, object detection as well as emotion recognition are well known complex tasks that modern smartphone can solve. It became possible with intensive usage of algorithms of Artificial Intelligence and Machine Learning. Most popular now are implementations of deep neural networks and deep learning algorithms. Such algorithms are widely used in all verticals and need hardware accelerators as well as deep cooperation between both software and hardware parts.
The problems of information processing in solving the technological preparation of production were considered. For this purpose use the effective methods of multivariate statistical analysis and artificial neural networks. Compression algorithms in the original array of information by factor analysis methods, component analysis and multidimensional scaling, classification algorithms and pattern recognition methods of discriminate and cluster analysis, as well as algorithms for modeling of group account of arguments and artificial neural networks were implemented with software.
Two problems are analyzed in the paper: 1) prediction and identification of critical loads and concrete strength in compressed R/C columns, 2) identification of compaction characteristics in granular soils. The main goal of the paper is to compare the numerical efficiency of the Method of Gaussian Processes with the results obtained by means of other methods (Extended Back Propagation Neural Network, Semi Bayesian Neural Networks and Bayesian methods).
The purpose of research. The main purpose of research is to analyze the relief of various surfaces. For example, to select on the surface the individual sections of a certain form, such as slopes that are oriented in a given direction. The main aim of the article is the use of artificial neural networks (ANN). To solve the problem of classification a binary classifier was created and its work and its accuracy was studied. Method. The research was carried out on the certain section of the earth's surface. The digital model, presented by greed file, was created.