Intelligent control system of aluminum containers drying process
DOI:
https://doi.org/10.31548/energiya2022.05.023Abstract
The relevance is the wide use of aluminum containers in the food industry. The high quality of products is reached by keeping clear technological standards and using materials of the highest class in the manufacture of aluminum containers for long-term and safe storage of food products. Water-based paints and varnish are used for production, which helps to avoid the negative influence of the printing and varnishing process on the environment.
A neural network (also called an artificial neural network) is an adaptive system that learns by using interconnected nodes or neurons in a layered structure that resembles a human brain. A neural network can learn from data—so it can be trained to recognize patterns, classify data, and forecast future events. A neural network breaks down the input into layers of abstraction. It can be trained using many examples to recognize patterns in speech or images, for example, just as the human brain does. Its behavior is defined by the way its individual elements are connected and by the strength, or weights, of those connections. These weights are automatically adjusted during training according to a specified learning rule until the artificial neural network performs the desired task correctly. Neural networks are especially suitable for modeling non-linear relationships, and they are typically used to perform pattern recognition and classify objects or signals in speech, vision, and control systems. [2] In our case is control system of the temperature in the drying oven.
Key words: neural network; adaptive system, control system, intelligent control system
References
Lysenko, V. P., Reshetyuk, V. M., Shtepa, V. M., Zayets, N. A. (2014). Artificial intelligence systems: fuzzy logic, neural networks, fuzzy neural networks, genetic algorithm. Kyiv: NUBIP of Ukraine.
Neural Networks. The MathWorks, Inc, 1994-2022.
Lysenko, V., Zayets, N., Gachkovska, M., Savchuk, O. (2019). Intelligent systems for managing biotechnical objects. Kyiv: KomPrint.
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