Design of wireless transmission digital thermometer

Che, Haitao; Zhuang, Shijie; Lianbo, Jiang; Hong, Hui; Zhang, Hongbing

doi:10.1145/2071639.2071643

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…Back Propagation (BP) is likely to search terminated at a local optimal solution. Generally speaking, the convergence can be accelerated by adjusting the learning step and momentum coefficient [5]. However, in order to find the global optimization solution, the calculation method, adjusting NN weights and threshold values depending on the grads, must be abandoned.…”

Section: Improvement Of Back Propagation Algorithmmentioning

confidence: 99%

An Neural Network Model for the Fe/SiO<sub>2</sub> Ratio in Copper Flash Smelting Slag Using Improved Back Propagation Algorithm

Lü

2012

AMR

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The Fe/SiO2 ratio in slag is one of the important control parameters for copper flash smelting process, but it is difficult to describe the complex relationship between the technological parameters and the Fe/SiO2 ratio in slag using accurate mathematic formulae, because the copper flash smelting process is a complicated nonlinear system. An neural network model for the Fe/SiO2 ratio in copper flash smelting slag was developed, whose net structure is 8-15-12-1, and input nodes include the oxygen volume per ton concentrate, the oxygen grade, the flux rate, the quantity of Cu, S, Fe, SiO2 and MgO in concentrate. In order to avoid local minimum terminations when the model is trained by back propagation (BP) algorithm, a new algorithm called GA-BP is presented by using genetic algorithm (GA) to determine the initial weights and threshold values. The results show that the model can avoid local minimum terminations and accelerate convergence, and has high prediction precision and good generalization performance. The model can be used to optimize the copper flash smelting process control.

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Section: Improvement Of Back Propagation Algorithmmentioning

confidence: 99%

An Neural Network Model for the Fe/SiO<sub>2</sub> Ratio in Copper Flash Smelting Slag Using Improved Back Propagation Algorithm

Lü

2012

AMR

View full text Add to dashboard Cite

show abstract

Design of wireless transmission digital thermometer

Cited by 1 publication

References 3 publications

An Neural Network Model for the Fe/SiO<sub>2</sub> Ratio in Copper Flash Smelting Slag Using Improved Back Propagation Algorithm

An Neural Network Model for the Fe/SiO<sub>2</sub> Ratio in Copper Flash Smelting Slag Using Improved Back Propagation Algorithm

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