Application of Neural Network and Fuzzy Logic in Modelling and Control of Fermentation Processes

In this paper we review various research of journal paper as Web Searching efficiency improvement. Some important method based on sequential pattern Mining. Some are based on supervised learning or unsupervised learning. And also used for other method such as Fuzzy logic and neural network

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Data-Driven Stability Assessment of Multilayer Long Short-Term Memory Networks

Applied Sciences ◽

10.3390/app11041829 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1829

Author(s):

Davide Grande ◽

Catherine A. Harris ◽

Giles Thomas ◽

Enrico Anderlini

Keyword(s):

Neural Network ◽

Network Architecture ◽

Short Term Memory ◽

Moving Average ◽

Machine Learning Algorithms ◽

Physical Models ◽

Data Driven ◽

The Stability ◽

And Control ◽

Nonlinear Autoregressive

Recurrent Neural Networks (RNNs) are increasingly being used for model identification, forecasting and control. When identifying physical models with unknown mathematical knowledge of the system, Nonlinear AutoRegressive models with eXogenous inputs (NARX) or Nonlinear AutoRegressive Moving-Average models with eXogenous inputs (NARMAX) methods are typically used. In the context of data-driven control, machine learning algorithms are proven to have comparable performances to advanced control techniques, but lack the properties of the traditional stability theory. This paper illustrates a method to prove a posteriori the stability of a generic neural network, showing its application to the state-of-the-art RNN architecture. The presented method relies on identifying the poles associated with the network designed starting from the input/output data. Providing a framework to guarantee the stability of any neural network architecture combined with the generalisability properties and applicability to different fields can significantly broaden their use in dynamic systems modelling and control.

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A fuzzy logic neural network algorithm for compressor crankshaft-rolling bearing system optimization

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189974 ◽

2021 ◽

pp. 1-7

Author(s):

Zheng Zhang ◽

Jianrong Zheng

Keyword(s):

Neural Network ◽

Fuzzy Logic ◽

Dynamic Analysis ◽

Weighted Average ◽

Rolling Bearing ◽

System Optimization ◽

Simulation Software ◽

Network Algorithm ◽

Neural Network Algorithm ◽

Bearing System

Taking the crankshaft-rolling bearing system in a certain type of compressor as the research objective, dynamic analysis software is used to conduct detailed dynamic analysis and optimal design under the rated power of the compressor. Using Hertz mathematical formula and the analysis method of the superstatic orientation problem, the relationship expression between the bearing force and deformation of the rolling bearing is solved, and the dynamic analysis model of the elastic crankshaft-rolling bearing system is constructed in the simulation software ADAMS. The weighted average amplitude of the center of the neck between the main bearings is used as the target, and the center line of the compressor cylinder is selected as the design variable. Finally, an example analysis shows that by introducing the fuzzy logic neural network algorithm into the compressor crankshaft-rolling bearing system design, the optimal solution between the design variables and the objective function can be obtained, which is of great significance to the subsequent compressor dynamic design.

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