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Modeling of Cement Decomposing Furnace Production Process Based on Flexible Neural Tree

机译:基于柔性神经树的水泥分解炉生产工艺建模

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The paper introduces that cement decomposing furnace plays an important role in the pre-decomposing system. To make clear the complex relation among its related factors and control its production process better, the paper presents a method of making use of flexible neural tree (FNT) to construct its production process model. The FNT model’s structure and parameters are optimized by probabilistic incremental program evolution (PIPE) and simulation annealing (SA) respectively. The paper gives a detailed description of the process of constructing the FNT model, and tests the performance of the optimized model. The result demonstrates that the put forward method is effective for solving the problem. At last, comparing with other methods, the distinct advantage is that it is capable of handing the task automatically. The successful application of the method in cement decomposing production process will opens up a new research direction for cement industry production process modeling, it even has a great influence on the whole fluid industry.
机译:本文介绍了水泥分解炉在预分解系统中起着重要作用。为了明确其相关因素之间的复杂关系,并更好地控制其生产过程,介绍了利用柔性神经树(FNT)来构建其生产过程模型的方法。 FNT模型的结构和参数分别通过概率增量节目演化(管道)和仿真退火(SA)进行了优化。本文给出了构建FNT模型的过程的详细描述,并测试了优化模型的性能。结果表明,提出的方法对于解决问题是有效的。最后,与其他方法相比,明确的优点是它能够自动处理任务。该方法在水泥分解生产过程中的成功应用将对水泥行业生产过程建模开辟新的研究方向,甚至对整个流体工业有很大影响。

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