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首页> 美国卫生研究院文献>Polymers >The Yield Prediction of Synthetic Fuel Production from Pyrolysis of Plastic Waste by Levenberg–Marquardt Approach in Feedforward Neural Networks Model
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The Yield Prediction of Synthetic Fuel Production from Pyrolysis of Plastic Waste by Levenberg–Marquardt Approach in Feedforward Neural Networks Model

机译：前馈神经网络模型中Levenberg-Marquardt方法预测塑料废料热解合成燃料的收率

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摘要

The conversion of plastic waste into fuel by pyrolysis has been recognized as a potential strategy for commercialization. The amount of plastic waste is basically different for each country which normally refers to non-recycled plastics data; consequently, the production target will also be different. This study attempted to build a model to predict fuel production from different non-recycled plastics data. The predictive model was developed via Levenberg-Marquardt approach in feed-forward neural networks model. The optimal number of hidden neurons was selected based on the lowest total of the mean square error. The proposed model was evaluated using the statistical analysis and graphical presentation for its accuracy and reliability. The results showed that the model was capable to predict product yields from pyrolysis of non-recycled plastics with high accuracy and the output values were strongly correlated with the values in literature.
机译：通过热解将塑料废物转化为燃料已被认为是商业化的潜在策略。每个国家/地区的废塑料量基本上不同，这通常是指不可回收的塑料数据；因此，生产目标也将有所不同。这项研究试图建立一个模型，以根据不同的非回收塑料数据预测燃料产量。通过Levenberg-Marquardt方法在前馈神经网络模型中开发了预测模型。根据均方误差的最低总数，选择隐藏神经元的最佳数量。使用统计分析和图形表示对所提出的模型的准确性和可靠性进行了评估。结果表明，该模型能够准确预测非回收塑料的热解产物收率，其输出值与文献中的值高度相关。

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