摘要
针对阀厅连接金具的温升问题,提出基于模糊系统的温升预测策略,并用此方法对连接金具的温升进行预测。通过阀厅连接金具温升试验得到训练与测试数据。利用训练数据通过梯度下降算法训练模糊系统,建立相应温升模型,然后用测试数据进行测试,检验模型可靠性,相对误差平均值为8.04%,测试结果合理。用回归分析对阀厅连接金具的温升进行预测,并与模糊系统进行比较,模糊系统预测的相对误差平均值比回归分析降低了5.56%。预测与比较结果说明,模糊系统在阀厅连接金具温升预测方面具有优势。
The predicting strategy based on fuzzy system is developed for the rise of temperature of connection fitting in value hall. Training data and testing data are obtained from the experiment of the rise of temperature of connection fitting in value hall. By training data,fuzzy system is trained by gradient descent algorithm,the model of rise of temperature is found,then the testing data is used to carrying out the test of fuzzy system and obtained reasonable result,the mean value of relative error is 8. 04%. Regression analysis is used to predict the rise of temperature of connection fitting,the predicting effect of fuzzy system is compared with that of regression analysis,the mean value of relative error of fuzzy system is 5. 56% lower than that of regression analysis. The result of prediction and comparison shows that fuzzy system possesses superiority on the prediction for the rise of temperature of connection fitting in value hall.
出处
《河南理工大学学报（自然科学版）》
CAS
北大核心
2017年第1期107-113,共7页
Journal of Henan Polytechnic University（Natural Science）
基金
国家863高技术项目(2014AA051802)
国家电网科技研究项目(SGNXJX00YJJS1400105)
关键词
阀厅连接金具
模糊系统
训练数据
测试数据
connection fitting in value hall
fuzzy system
training data
testing data
