Elements realization of software-algorithmic system optimization of technological processes based on adaptive methods

Abstract

The paper examines a possibility to optimize complex technological processes of energy resources transfer and consumption. Notes the importance of unidentified and weakly formalized factors consideration, which influence quality of the described object classes functioning. Suggests use of fuzzy neural networks and controllers on their basis for implementation of technological processes optimization of energy resources transfer and consumption at the expense of its dynamic accuracy forecast improvement. Presents algorithmic realization, that later on configured in the MATLAB simulated environment. Quantitative and qualitative parameters, which characterize fuzzy neural controller’s usage quality, were received. Later, software environment elements are being described, which constructed on the basis of the suggested adaptive approach for complex technological processes optimization. Points out a possibility to conduct comparative study, and also simulation modeling implementation by way of presented solutions.

Neural fuzzy network configurator for calculating a residual life of production equipment

“…We pay special attention to intelligent techniques fault diagnosis: self-organising neural networks [4], dynamic wavelet neural networks [5], recurrent neural network [6,7], recurrent neural networks and neural-fuzzy inference systems [8], neural-fuzzy approach [9][10][11][12][13][14], hybrid intelligent methods [1], applied to estimation the different features of process equipment: remaining useful life [3], mean-residual-life [9], onset of a failure or predicting the time of ultimate failure [15].…”