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基于多传感器技术的原油含水率预测模型研究 总被引:8,自引:2,他引:8
通过多传感器技术对原油含水率测量有影响的多个参量进行测定,提出基于多元非线性回归和神经网络融合处理两种方法建立原油含水率预测模型,并采用分段建模的方法分别进行改进.评价结果表明:神经网络模型预测效果优于多元非线性回归模型,原油含水率分段预测模型效果优于统一模型.尤其是改进的神经网络分段预测模型具有网络结构简化、收敛速度快,泛化能力强的特点,取得很好的拟合精度和预测效果. 相似文献
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定额人工单价的主要影响因素与某一时期的劳动力市场供求关系、社会经济发展水平、物价增速、人口结构及就业偏好等因素有关。通过对定额人工单价影响因素的识别,确定影响建筑劳务单价的特征指标变量。结合特征指标变量标准化、适用性检验、提取主成分、主成分因子的计算等主成分分析法的实施,采用SPSS软件对选取的指标数据进行初步回归分析及多重共线性诊断,建立市场人工单价主成分回归预测模型并对2021年前三季度的市场人工单价进行预测。结果表明,预测值与实际值相对误差<3%,模型精度满足要求,该主成分回归预测模型可用于建筑行业市场劳务单价的预测工作。 相似文献
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随着采矿活动愈来愈深入地壳,岩层中岩石破坏造成的影响越来越大,准确获取岩石破坏时的强度对于指导工程施工和安全生产尤为重要。为了提高岩石在不同围压条件下三轴压缩破坏强度的预测精度,根据砂岩三轴强度曲线的非线性特征,利用回归预测方法推导建立了基于双曲线函数的岩石三轴压缩强度回归预测模型,对该模型进行了4个指标的检验,初步证明了其合理性;进一步将该预测模型与H-B准则和M-C准则进行比较,结果表明,该模型预测值的平均相对误差仅为5.15%,而H-B准则为11.44%,M-C准则为14.34%,显然该模型的预测精度更高。该岩石强度预测模型可为地下工程结构设计提供参考。 相似文献
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针对燃煤锅炉结渣特性的有限样本、非线性和高维数问题,提出了一种基于粒子群优化(PSO)和支持向量回归(SVR)的预测模型。对于支持向量回归机在建模中存在的参数选取问题,采用改进的粒子群算法(PSO)对模型参数进行优化,该方法结合了PSO的快速全局优化能力和SVR的结构风险最小化理论,精确地逼近非线性映射关系的能力。仿真结果表明:相比遗传算法(GA)SVR预测模型和模拟退火(SA)SVR预测模型,PSO-SVR模型预测燃煤锅炉结渣特性具有较高的准确率。 相似文献
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针对经典线性回归模型无法反映变量间的非线性关系,不适宜预测有模糊数的煤炭发热量的问题,提出了一种基于三角模糊数的多元非线性回归的煤炭发热量预测模型。以我国新疆伊犁地区煤炭工业分析为建模数据和模型检验数据,将计算模糊中心值和模糊幅度值的问题转化为约束非线性优化问题,采用MATLAB优化工具箱求解。最后对比分析了模糊非线性回归、经典线性回归、BP(Back Propagation)神经网络及支持向量机回归4种模型对测试煤样发热量的预测结果。结果表明,模糊非线性回归模型的线性拟合优度值为0.9997,调整后的非线性拟合优度值为0.9838,均方误差为0.4473;测试煤样的平均相对误差为0.0203,80%的测试煤样模糊隶属度大于0.5。模糊非线性回归模型具有很高的精确度和可靠性,可用来预测预报煤炭发热量。 相似文献
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本文依据陶瓷隧道窑热工测试数据和热平衡报告,采用多元回归和逐步回归统计理论,得到了陶瓷隧道窑单位重量热耗的多元回归数学模型和逐步回归数学模型。利用该数学模型可对单耗进行预测和控制。 相似文献
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分析采用回归分析方法在建立橡胶配方试验中考察因素和试验数据的二次多项式回归模型时存在的局限性,介绍应用偏最小二乘(PLS)回归方法建立二次多项式回归模型的技术,并通过实例演示PLS回归方法在橡胶配方设计中的应用。结果表明,PLS回归方法适应多因变量对多自变量的回归建模分析,结论可靠,整体性强。 相似文献
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Akshay Morey Soumyashis Pradhan Rahul Anil Kumar Venkata Vijayan S. Varun Jain 《Chemical Engineering Communications》2019,206(1):69-85
In this article, data-driven models are developed for real time monitoring of sulfur dioxide and hydrogen sulfide in the tail gas stream of sulfur recovery unit (SRU). Statistical [partial least square (PLS), ridge regression (RR) and Gaussian process regression (GPR)] and soft computing models are constructed from plant data. The plant data were divided into training and validation sets using Kennard-Stone algorithm. All models are developed from the training data set. PLS model is designed using SIMPLS algorithm. Three different ridge parameter selection techniques are used to design the RR model. GPR model is designed using four hyper parameter selection methods. The soft computing models include fuzzy and neuro-fuzzy models. Prediction accuracy of all models is assessed by simulation with validation dataset. Simulation results show that the GPR model designed with marginal log likelihood maximization method has good prediction accuracy and outperforms the performance of all other models. The developed GPR model is also found to yield better prediction accuracy than some other models of the SRU proposed in the literature. 相似文献
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Abstract The detection of a change from a constant level to a monotonically increasing (or decreasing) regression is of special interest for the detection of outbreaks of epidemics but is also of interest in other areas. A maximum likelihood ratio statistic for the sequential surveillance of an “outbreak” situation is derived. The method is semiparametric in the sense that the regression model is nonparametric whereas the distribution belongs to the regular exponential family. The method is evaluated with respect to timeliness and predicted value in a simulation study that imitates the influenza outbreaks in Sweden. To illustrate its performance, the method is applied to Swedish influenza data for 6 years. The advantage of this semiparametric surveillance method, which does not rely on an estimated baseline, is illustrated by a Monte Carlo study. The advantage of information accumulation is illustrated. 相似文献
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借助SPSS统计分析软件,以主机螺杆转速和加料量为自变量建立了啮合同向双螺杆挤出机功率消耗的二元线性和非线性数学模型,探讨了主机螺杆转速和加料量对挤出机功耗的影响。通过实验得到的数据和模型预测数据进行对比。结果表明,二元线性回归模型完全可以用来对挤出机功耗进行预测。 相似文献
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本文采用单纯形回归设计的方法,试验研究了研磨片用胶(底胶)的配方模型。经重复试验证明,该模型基本符合所讨论的研磨片用胶粘剂的粘结强度与配方组成的关系。作者认为,该方法可以推厂应用于其它多因素纯配方性试验的数据处理与优化设计。 相似文献
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通过线性回归技术在抚顺石油二厂90^#无铅汽油调和中的应用,极大的降低了调和成本,利用线性回归技术是优化生产的有效手段。 相似文献
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Grindability index of coal is usually determined by Hardgrove Grindability Index (HGI). The correlation between the proximate analysis of Chinese coal and HGI was studied. It was found from statistical analysis that, the higher the moisture and the volatile matter content in coal, the less the HGI will be. On the contrary, the higher the ash and the fixed carbon content in coal, the higher the HGI will be. But the correlation between proximate analysis and HGI in coals is nonlinear. The prediction equation of HGI reported in literature, which is based on proximate analysis of coal and linear regression method, is not correct for coals in China. In this paper, the generalized regression neural network (GRNN) method was used to predict the HGI. A higher precision in the prediction result was obtained through such new method. By this method, the HGI can be estimated indirectly from the proximate analysis of coal when the HGI measurement equipment is not available. 相似文献