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Prediction and fusion algorithm for meat moisture content measurement based on loss-on-drying method

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International Journal of Agricultural and Biological Engineering 2020年第4期13卷 198-204页

作者： Jing ling Jie Xu haijun lin Jinyuan lin School of Physics and Electronic-Electrical Engineering Ningxia UniversityYinchuan 750021China Department of Food Science and Technology The Ohio State UniversityColumbusOH43210USA College of Polytechnic Hunan Normal UniversityChangsha 410081China

The loss-on-drying method has been widely used as a standard approach for measuring the moisture content of high-moisture materials such as solid and semi-solid ***-on-drying method provides reliable results,whilst usually labor-intensive and *** paper presents a novel algorithm for predicting the moisture content of meats based on the loss-on drying *** proposed approach developed a drying kinetics model of meats based on Fick’s Second Law and designed a prediction algorithm for meat moisture content using the least-squares *** predicted results were compared with the official method recommended by the Association of Official Analytical Chemists(AOAC).When the moisture content of meat samples(beef and pork)was varied from 69.46%to 74.21%,the relative error of the meat moisture content(MMC)calculated by the proposed algorithm was 0.0017-0.0117,the absolute errors were less than 1%.The testing time was about 40.18%-56.87%less than the standard detection procedure.

关键词： meat moisture content loss-on-drying method Fick’s Second Law fusion algorithm measurement prediction

基于Slepian和Parzen互卷积窗插值FFT的电力系统谐波分析方法

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电测与仪表 2024年第8期61卷 172-178页

作者：曹远远李建闽林海军杨宇祥卢笑张甫湖南师范大学工程与设计学院长沙410081

谐波是电力系统中最为突出的电能质量问题之一。谐波参数的准确估计是电力企业和用户评价电能质量的重要参考依据。目前,电网谐波参数的估计方法主要基于傅里叶变换算法,但该算法在分析和处理信号时需要对原始信号进行截断和离散化处理... 详细信息

谐波是电力系统中最为突出的电能质量问题之一。谐波参数的准确估计是电力企业和用户评价电能质量的重要参考依据。目前,电网谐波参数的估计方法主要基于傅里叶变换算法,但该算法在分析和处理信号时需要对原始信号进行截断和离散化处理,会不可避免地导致频谱泄露和栅栏效应,从而严重影响电网谐波参数的准确测量。而具有优良旁瓣特性的窗函数以及插值算法可有效改善因频谱泄露和栅栏效应所带来的参数估计误差。为此,文中提出一种基于Slepian窗和Parzen窗的新型互卷积窗(slepian and parzen mutual convolution window,SPMCW)插值FFT的谐波分析方法。SPMCW具有较低的旁瓣电平和快速的旁瓣衰减速率,因而可有效抑制频谱泄露,进而实现弱谐波幅值的检测。在MATLAB下的仿真实验验证了文中算法的准确性和可靠性。实际构建的硬件平台验证了算法的有效性和可行性。

关键词： Slepian窗 Parzen窗互卷积窗插值FFT 谐波分析电力系统

基于混合扫描的碳足迹采集终端可测性设计及融合诊断

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电测与仪表 2024年第8期61卷 39-46页

作者：赵雪松尹仕红谢倩娴侯婧林海军陈寅生深圳供电局有限公司计量管理所广东深圳518133 哈尔滨理工大学哈尔滨150080

在“双碳”战略的背景下,针对国内对碳足迹采集终端及系统的迫切需求,提出了基于电力采集终端及通信系统的解决方案,并利用混合边界扫描技术提出了具体的“虚拟探针”可测性设计方案。还针对基于单一类型故障特征进行非线性“簇”电路... 详细信息

在“双碳”战略的背景下,针对国内对碳足迹采集终端及系统的迫切需求,提出了基于电力采集终端及通信系统的解决方案,并利用混合边界扫描技术提出了具体的“虚拟探针”可测性设计方案。还针对基于单一类型故障特征进行非线性“簇”电路故障诊断准确率低的难题,在研究小波包变换、PCA及Volterra核特征提取的基础上,提出了小波包变换与PCA特征层融合,并与基于Volterra核特征的初级诊断结果进行决策层融合的故障诊断方法。实验表明,该方法可以有效提高故障诊断的准确率。

关键词：碳足迹采集终端可测性设计信息融合故障诊断 Volterra核

Infrared drying kinetics and moisture diffusivity modeling of pork

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International Journal of Agricultural and Biological Engineering 2017年第3期10卷 302-311页

作者： ling Jing Teng Zhaosheng lin haijun Wen He College of Electrical and Information Engineering Hunan UniversityChangsha 410082China School of Physics and Electronic-Electrical Engineering Ningxia UniversityYinchuan 750021China College of Polytechnic Hunan Normal UniversityChangsha 410081China

This study investigated the drying kinetics of pork slice in infrared drying *** temperature,slice thickness and initial moisture content were selected as influencing factors on the drying characteristics and drying rate of pork *** curves obtained from the experimental data were fitted to semi theoretical and/or empirical thin layer drying *** effects of drying temperature and slice thickness on the model constants were evaluated by the multiple regression *** the models were compared according to three statistical indexes,i.e.,root mean square error,chi-square and modeling *** slice thickness,drying temperature and initial moisture content have significant influences on the effective diffusivity coefficient of *** results showed that the drying rate of pork slices increased with the increases of drying temperature and initial moisture *** decreases of slice thickness also led to an increase of drying *** Henderson and Pabis model can best describe the drying curves of pork.

关键词： infrared drying pork slice drying kinetics effective moisture diffusivity multiple regression analysis

Design and Analysis of a Water Quality Monitoring Data Service Platform

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Computers, Materials & Continua 2021年第1期66卷 389-405页

作者： Jianjun Zhang Yifu Sheng Weida Chen haijun lin Guang Sun Peng Guo College of Engineering and Design Hunan Normal UniversityChangsha410081China Zhaoyin Network Technology(Shenzhen)Co. Ltd.Shenzhen518057China Big Data Institute Hunan University of Finance and EconomicsChangsha410205China University Malaysia Sabah Sabah88400Malaysia

Water is one of the basic resources for human *** pollution monitoring and protection have been becoming a major problem for many countries all over the *** traditional water quality monitoring systems,however,generally focus only on water quality data collection,ignoring data analysis and data *** addition,some dirty data and data loss may occur due to power failures or transmission failures,further affecting data analysis and its *** order to meet these needs,by using Internet of things,cloud computing,and big data technologies,we designed and implemented a water quality monitoring data intelligent service platform in C#and PHP *** platform includes monitoring point addition,monitoring point map labeling,monitoring data uploading,monitoring data processing,early warning of exceeding the standard of monitoring indicators,and other functions *** this platform,we can realize the automatic collection of water quality monitoring data,data cleaning,data analysis,intelligent early warning and early warning information push,and other *** better security and convenience,we deployed the system in the Tencent Cloud and tested *** testing results showed that the data analysis platform could run well and will provide decision support for water resource protection.

关键词： Water quality monitoring data analysis big data tencent cloud

Application of Grey Model and Neural Network in Financial Revenue Forecast

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Computers, Materials & Continua 2021年第12期69卷 4043-4059页

作者： Yifu Sheng Jianjun Zhang Wenwu Tan Jiang Wu haijun lin Guang Sun Peng Guo College of Engineering and Design Hunan Normal UniversityChangsha410081China Big Data Institute Hunan University of Finance and EconomicsChangsha410205China University Malaysia Sabah Sabah88400Malaysia

There are many influencing factors of fiscal revenue,and traditional forecasting methods cannot handle the feature dimensions well,which leads to serious over-fitting of the forecast results and unable to make a good estimate of the true future *** grey neural network model fused with Lasso regression is a comprehensive prediction model that combines the grey prediction model and the BP neural network model after dimensionality reduction using *** can reduce the dimensionality of the original data,make separate predictions for each explanatory variable,and then use neural networks to make multivariate predictions,thereby making up for the shortcomings of traditional methods of insufficient prediction *** this paper,we took the financial revenue data of China’s Hunan Province from 2005 to 2019 as the object of ***,we used Lasso regression to reduce the dimensionality of the *** the grey prediction model has the excellent predictive performance for small data volumes,then we chose the grey prediction model to obtain the predicted values of all explanatory variables in 2020,2021 by using the data of 2005–***,considering that fiscal revenue is affected by many factors,we applied the BP neural network,which has a good effect on multiple inputs,to make the final forecast of fiscal *** experimental results show that the combined model has a good effect in financial revenue forecasting.

关键词： Fiscal revenue lasso regression gray prediction model BP neural network

基于整体退火遗传小波网络的计量终端可靠性预测

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电测与仪表 2024年第2期61卷 179-184页

作者：徐宏伟丛中笑阳晓路周忠明陈寅生林海军贵州电网有限责任公司计量中心贵阳550002 哈尔滨理工大学哈尔滨150080

为了解决小波神经网络初值敏感性及收敛稳定性问题,以提高计量终端软件可靠性预测建模的效率及准确性。文章完善了整体退火遗传算法(WAGA),并验证了其具有极强的整体收敛和全局优化能力,利用其全局寻优能力,优化小波神经网络(WNN)的参数... 详细信息

为了解决小波神经网络初值敏感性及收敛稳定性问题,以提高计量终端软件可靠性预测建模的效率及准确性。文章完善了整体退火遗传算法(WAGA),并验证了其具有极强的整体收敛和全局优化能力,利用其全局寻优能力,优化小波神经网络(WNN)的参数,提出基于整体退火遗传小波神经网络(WAGA-WNN)的建模方法;用该方法建立计量终端的软件可靠性预测模型。实验结果表明,该方法可以解决小波神经网络初值敏感性及收敛稳定性难题,建立的软件可靠性预测模型效率和准确度较高。

关键词：整体退火遗传算法小波神经网络计量终端软件可靠性预测模型

Influence of sub-bandgap illumination on space charge distribution in CdZnTe detector

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Chinese Physics B 2021年第3期30卷 378-385页

作者： Rongrong Guo Jinhai lin Lili Liu Shiwei Li Chen Wang Feibin Xiong haijun lin Fujian Provincial Key Laboratory of Optoelectronic Technology and Devices Xiamen University of TechnologyXiamen 361024China

The space charge accumulation in CdZnTe crystals seriously affects the performance of high-flux pulse *** influence of sub-bandgap illumination on the space charge distribution and device performance in CdZnTe crystals were studied theoretically by Silvaco TCAD software *** sub-bandgap illumination with a wavelength of 890 nm and intensity of 8×10−8 W/cm2 were used in the simulation to explore the space charge distribution and internal electric field distribution in CdZnTe *** simulation results show that the deep level occupation faction is manipulated by the sub-bandgap illumination,thus space charge concentration can be reduced under the bias voltage of 500 V.A flat electric field distribution is obtained,which significantly improves the charge collection efficiency of the CdZnTe ***,premised on the high resistivity of CdZnTe crystal,the space charge concentration in the crystal can be further reduced with the wavelength of 850 nm and intensity of 1×10−7 W/cm2 *** electric field distribution is flatter and the carrier collection efficiency of the device can be improved more effectively.

关键词： CdZnTe detector sub-bandgap illumination space charge charge collection efficiency

融合Prophet与PCA技术的CNN-LSTM模型在水质预测中的应用

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计量科学与技术 2024年第10期68卷 38-44页

作者：肖克张建军谭文武王理宋玲毓林海军湖南省计量检测研究院湖南师范大学工程与设计学院天翼电子商务有限公司广东分公司

为了降低传统CNN-LSTM模型进行水质预测时可能会出现的错误发生率，提出了一种基于Prophet模型与PCA的CNN-LSTM水质预测方法。在水质监测数据清洗过程中采用Prophet模型进行异常值处理，使用PCA方法对影响变量进行降维，消除变量关联性... 详细信息

为了降低传统CNN-LSTM模型进行水质预测时可能会出现的错误发生率，提出了一种基于Prophet模型与PCA的CNN-LSTM水质预测方法。在水质监测数据清洗过程中采用Prophet模型进行异常值处理，使用PCA方法对影响变量进行降维，消除变量关联性，把处理结果作为CNN-LSTM模型输入，对水质总氮指标进行预测。通过实验对基于Prophet模型与PCA的CNN-LSTM水质预测方法进行验证，实验结果表明：该方法相对于CNN-LSTM模型在MAE、RMSE和MSE三种评价指标上都有了较大的提升，其中MSE提升了13%,RMSE提升了6.7%,MAE提升了5.6%。

关键词：计量学水质监测主成分分析 CNN LSTM 水质预测