Application of Improved Back-Propagation Neural Network to the Technologic Processing of Korshunskite Whiskers

Qing Li Ren; Qiang Luo; Miao Miao Yang

doi:10.4028/www.scientific.net/KEM.602-603.312

Paper Titles

Morphology Controlling of CaCO₃ in 3D Bacterial Cellulose Nanofibres
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Surface Functionalization of Ordered Mesoporous Carbon by Immobilization of Diamine for Cobalt-Ion Adsorption
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Study on the Variety of Rheological Properties and Thermal Analysis of Modified Coal Tar Pitch with 1,4-Benzenedimethanol
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The Formation and its Related Mechanism of Lu₂Ti₂O₇ Octahedrons Grown from Molten Salt
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Application of Improved Back-Propagation Neural Network to the Technologic Processing of Korshunskite Whiskers
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High Temperature Micro Structural Evolution of ZrO₂ Fibers Thermal Insulation Materials
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Preparation of Industrial Watchcase of 5Y-Tetragonal ZrO₂ by Microwave Sintering
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The Effect of Nano-Al₂O₃ on Sintering Behavior and Mechanical Property of ZrO₂ Ceramics
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Synthesis of Mullite Using Low-Grade Bauxite and Coal Gangue
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HomeKey Engineering MaterialsKey Engineering Materials Vols. 602-603Application of Improved Back-Propagation Neural...

Application of Improved Back-Propagation Neural Network to the Technologic Processing of Korshunskite Whiskers

Abstract:

The korshunskite samples were prepared in precipitation by the one-step reaction method at atmospheric pressure. The three-layer structure back-propagation network model based on the non-linear relationship between the amount of the korshunskite whiskers and the technological factors, such as the adding amount of raw materials NaOH, MgCl₂, MgO, and reaction temperature, is established. And the results show that the improved back propagation neural networks model is very efficient for predication of the korshunskite whiskers preparation.