The classification of technical equipment states, using a neural nets approach

The Maser thesis is devoted to developing a model to technical state of gas turbine engine estimation. The approaches to preparation data, especially to handle unbalanced data were presented in the thesis. In order to efficient estimation of model performance, the special metric was chosen. Goal of the master thesis is analyzing of monitoring parameters data and developing a model of technical state of GTE estimation based on the data.

Handling the Problem of Unbalanced Data Sets in the Classification of Technical Equipment States

Questions of handling unbalanced data considered in this article. As models for classification, PNN and MLP are used. Problem of estimation of model performance in case of unbalanced training set is solved. Several methods (clustering approach and boosting approach) considered as useful to deal with the problem of input data.

World survey of agricultural machinery and equipment.

[1] Asia.--[2] Europe.--[3] South America.--[4-5] Africa, Australia-Oceania.--[6] North and Central America.

Profile equipment evaluation.

Texas Department of Transportation, Austin

Calibration services for pavement survey equipment. Executive summary. Final report.

Federal Highway Administration, Office of Engineering and Highway Operations Research and Development, Washington, D.C.

Development of transit coach bonded brake lining test equipment and test procedures. Progress report. Final report.

Urban Mass Transportation Administration, Washington, D.C.