Prediction error analysis for intelligent management and predictive diagnostics systems
نویسندگان
چکیده
Random signal prediction is efficient for intelligent management and predictive diagnostics systems. Aim. The paper aims to analyse the error of random prediction. To develop recommendations selection extrapolator parameters. Methods . uses mathematics theory functions, formalization adopted in pulse systems, mathematical description extrapolators with Chebyshev polynomials orthogonal over a set equally spaced points. coefficients predicting polynomial are selected according minimal least squares. Results. describes model extrapolator. Design ratios were obtained assessments. maximum interval-averaged relative mean square extrapolation defined. authors processes defined by sum centred stationary process deterministic time function. Based on diverse calculations, that allow selecting parameters (degree extrapolating polynomial, number test points precede interval, discretisation interval function) under specified input models. Conclusion. use based method allows implementing procedure calculating predicted values required accuracy. Under models signal, was developed extrapolator’s (order, involved generation prediction, sample spacing) purpose ensuring
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ژورنال
عنوان ژورنال: ??????????
سال: 2023
ISSN: ['2765-5768', '2508-2809']
DOI: https://doi.org/10.21683/1729-2646-2023-23-2-12-18