The Forecast of Coal Demand Based on RoughSet and BP Neural Network Model

Cai, Zhenyu; Ma, Xingmin

doi:10.1109/icmss.2010.5577120

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…Compared with MFN, RBF has faster convergence speed and approximation accuracy because of its simpler network structure and more effective learning algorithm. We select the serial-parallel identification structure [13], and the established multiinput single-output RBF identification model is shown in Figure 5.…”

Section: Design Of Predictor Based On Rbf Neural Networkmentioning

confidence: 99%

Temperature Control Algorithm of Underground Air Conditioning in Station

Zheng

Zhao²,

Hu³

et al. 2022

Mathematical Problems in Engineering

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Aiming at the air-conditioning temperature control of underground station, the air-conditioning temperature controller of underground station is designed based on proportional-integral-differential neural network, the bat algorithm is used to select the initial weights, the radial basis function neural network prediction model is used to optimize the design of the predictor, and the designed control system is simulated on the MATLAB simulation platform. The simulation results show that the dynamic characteristics and steady-state characteristics of the PID controller optimized by bat algorithm are better than those of the PID controller tuned by conventional methods. After optimization by radial basis function neural network prediction model, the rapidity and stability of controller are effectively improved.

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Section: Design Of Predictor Based On Rbf Neural Networkmentioning

confidence: 99%

Temperature Control Algorithm of Underground Air Conditioning in Station

Zheng

Zhao²,

Hu³

et al. 2022

Mathematical Problems in Engineering

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Research on the Method of Warfare Simulation Data Analysis Based on BP Neural Network and RoughSet

Jun¹,

Yan-Hong²,

Wang

et al. 2013

2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications

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Preliminary exploration on simulation data mining with BP network and rough set method is made in advance.Then data mining method based on rough set theory and BP neural network is put up. Firstly, the redundant attributes in the decision-making table with rough set method is reduced, and the noise is filtered by BP neural network. Finally, rule set is generated by rough set from the reduction decision table. This method not only avoid the complexity of the rules extracted from training the neural network, but also improve the classification accuracy effectively. At last,the mining data by the experimental data of the troops marching warfare simulation system and the result with the actual reference value is obtained.

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The Forecast of Coal Demand Based on RoughSet and BP Neural Network Model

Cited by 2 publications

References 2 publications

Temperature Control Algorithm of Underground Air Conditioning in Station

Temperature Control Algorithm of Underground Air Conditioning in Station

Research on the Method of Warfare Simulation Data Analysis Based on BP Neural Network and RoughSet

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