摘要
由一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报告的主题。据《新报》编辑从中国西安发回的新闻报道，“锂电池作为一种重要的储能装置，广泛应用于可再生汽车和可再生能源领域。相关的锂电池回收产业也迎来了一个黄金时期。”本报编辑引用了西京大学的一篇研究文章：“然而，锂电池回收成本高，难以准确评估其回收价值，严重制约了锂电池产业的发展，因此，将机器学习应用于锂电池回收经济效益分析领域。”在综合考虑社会和商业价值的基础上，设计了基于逐步回归反向传播神经网络的锂电池回收利用经济效益分析模型，实验结果表明，该模型的平均误差在10-6～10-7之间收敛，收敛速度提高了33%。在实际试验中，该模型预测了一批锂电池回收的实际经济效益，结果表明，预测结果与真值基本一致，因此，本研究提出的锂电池回收经济效益分析与预测模型具有精度高、运行速度快的优点。"为促进经济效益分析领域的创新提供了新的思路和工具."
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting originating from Xi'an, People's Republi c of China, by NewsRx editors, the research stated, "Lithium batteries, as an im portant energy storage device, are widely used in the fields of renewable vehicl es and renewable energy. The related lithium battery recycling industry has also ushered in a golden period of development." Our news editors obtained a quote from the research from Xijing University, "How ever, the high cost of lithium battery recycling makes it difficult to accuratel y evaluate its recycling value, which seriously restricts the development of the industry. To address the above issues, machine learning will be applied in the field of economic benefit analysis for lithium battery recycling, and backpropag ation neural networks will be combined with stepwise regression. On the basis of considering social and commercial values, a lithium battery recycling and utili zation economic benefit analysis model based on stepwise regression backpropagat ion neural network was designed. The experimental results show that the mean squ are error of the model converges between 10-6 and 10-7, and the convergence spee d is improved by 33%. In addition, in practical experiments, the mo del predicted the actual economic benefits of recycling a batch of lithium batte ries. The results show that the predictions are basically in line with the true values. Therefore, the economic benefit analysis and prediction model for lithiu m battery recycling proposed in the study has the advantages of high accuracy an d fast operation speed, providing new ideas and tools for promoting innovation i n the field of economic benefit analysis."
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