Identification of the Optimal Parameters for Forecasting the State of Technical Objects Based on the Canonical Random Sequence Decomposition

Author(s):  
Igor Atamanyuk ◽  
Vyacheslav Shebanin ◽  
Yuriy Kondratenko ◽  
Valerii Havrysh ◽  
Vadim Lykhach ◽  
...  
2021 ◽  
Vol 5 (4) ◽  
pp. 5-9
Author(s):  
Svitlana Gavrylenko ◽  
Oleksii Hornostal

The subject of the research is methods and means of identifying the state of a computer system . The purpose of the article is to improve the quality of computer system state identification by developing a method based on ensemble classifiers. Task: to investigate methods for constructing bagging classifiers based on decision trees, to configure them and develop a method for identifying the state of the computer system. Methods used: artificial intelligence methods, machine learning, ensemble methods. The following results were obtained: the use of bagging classifiers based on meta-algorithms were investigated: Pasting Ensemble, Bootstrap Ensemble, Random Subspace Ensemble, Random Patches Ensemble and Random Forest methods and their accuracy were assessed to identify the state of the computer system. The research of tuning parameters of individual decision trees was carried out and their optimal values were found, including: the maximum number of features used in the construction of the tree; the minimum number of branches when building a tree; minimum number of leaves and maximum tree depth. The optimal number of trees in the ensemble has been determined. A method for identifying the state of the computer system is proposed, which differs from the known ones by the choice of the classification meta-algorithm and the selection of the optimal parameters for its adjustment. An assessment of the accuracy of the developed method for identifying the state of a computer system is carried out. The developed method is implemented in software and investigated when solving the problem of identifying the abnormal state of the computer system functioning. Conclusions. The scientific novelty of the results obtained lies in the development of a method for identifying the state of the computer system by choosing a meta-algorithm for classification and determining the optimal parameters for its configuration.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jacek Grosel ◽  
Monika Podwórna

Abstract The paper focuses on the problem of optimising the cooperation between a dynamic vibration absorber (DVA) and a structure. The authors analyse a road beam bridge equipped with a working platform (deck) used to service pipelines installed on the structure. The paper studies the problem of choosing the optimal parameters for damping absorbers that reduce the random vibration of a beam subjected to a random sequence of moving forces with a constant velocity. The stochastic properties of the load are modelled by means of a filtering Poisson process. A single-degree-of-freedom (SDOF) absorber model with a multi-degree-of-freedom (MDOF) primary structure model are is considered.


Author(s):  
T. A. Welton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.


1980 ◽  
Vol 11 (2) ◽  
pp. 85-94 ◽  
Author(s):  
Jack Damico ◽  
John W. Oller

Two methods of identifying language disordered children are examined. Traditional approaches require attention to relatively superficial morphological and surface syntactic criteria, such as, noun-verb agreement, tense marking, pluralization. More recently, however, language testers and others have turned to pragmatic criteria focussing on deeper aspects of meaning and communicative effectiveness, such as, general fluency, topic maintenance, specificity of referring terms. In this study, 54 regular K-5 teachers in two Albuquerque schools serving 1212 children were assigned on a roughly matched basis to one of two groups. Group S received in-service training using traditional surface criteria for referrals, while Group P received similar in-service training with pragmatic criteria. All referrals from both groups were reevaluated by a panel of judges following the state determined procedures for assignment to remedial programs. Teachers who were taught to use pragmatic criteria in identifying language disordered children identified significantly more children and were more often correct in their identification than teachers taught to use syntactic criteria. Both groups identified significantly fewer children as the grade level increased.


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