2010
DOI: 10.1117/12.888304
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Abstract: In order to reduce energy consumption and improve the stability of cement burning system production, it is necessary to conduct in-depth analysis of the cement burning system, control the operation state and law of the system. In view of the rotary kiln consumes most of the fuel, we establish the simulation model of the cement kiln used to find effective control methods. It is difficult to construct mathematical model for the rotary cement kiln as the complex parameters, so we expressed directly using neural n… Show more

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Cited by 14 publications
(5 citation statements)
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“…BP neural network has the advantages of high prediction accuracy and strong generalization ability, and is one of the most widely used neural networks at present. The algorithm principle is to calculate the error between the output result and the ideal result, and continuously adjust the weight and threshold of the network according to the error backpropagation algorithm to achieve the effect of evolutionary learning [9][10]. The BP neural network consists of an input layer, a hidden layer, and an output layer.…”
Section: Principle Of Bp Neural Networkmentioning
confidence: 99%
See 1 more Smart Citation
“…BP neural network has the advantages of high prediction accuracy and strong generalization ability, and is one of the most widely used neural networks at present. The algorithm principle is to calculate the error between the output result and the ideal result, and continuously adjust the weight and threshold of the network according to the error backpropagation algorithm to achieve the effect of evolutionary learning [9][10]. The BP neural network consists of an input layer, a hidden layer, and an output layer.…”
Section: Principle Of Bp Neural Networkmentioning
confidence: 99%
“…However, this prediction method usually requires a high time cost, and it is difficult to meet the real-time prediction requirements of the high-speed train for the brake disc temperature. With the rapid development of machine learning, many scholars have obtained good prediction results by constructing neural network models instead of complex simulation calculations [5][6]. Therefore, building a neural network model to predict the temperature of the brake disc has the advantages of accuracy and speed, and can meet the requirements of trains for real-time thermal management technology.…”
Section: Introductionmentioning
confidence: 99%
“…Yang [17] et al constructed a model of cement rotary kiln firing system based on BP networks and achieved good fitting results with good generalization ability. Geng [18] et al constructed a dynamic soft measurement model of industrial process based on CNN network, which cleverly solved the influence of high nonlinearity and noise of industrial process data on soft measurement, and concluded that their method has certain superiority through comparison experiments.…”
Section: Related Workmentioning
confidence: 99%
“…Intelligent control is the main research topic in calcination zone temperature control of rotary kilns. These control methods include fuzzy control (Guo et al, 2010), neural networks (Yang and Ma, 2011), expert systems (Wang et al, 2012) and hybrid intelligent control strategies (Stadler et al, 2011; Zhang and Gao, 2013; Zhang et al, 2013), and so forth. Furthermore, the distributed control system applied in current rotary kiln production of alumina can only fulfill regular monitoring and certain simple control conditions, and the flame information is not fully used (Yi et al, 2013b; Zhang et al, 2008).…”
Section: Introductionmentioning
confidence: 99%