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预报值的英文

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"预报值"怎么读用"预报值"造句

英文翻译手机手机版

  • forecast value
  • predicted value

例句与用法

  • Residuals : generally , the difference between a measured value and the value predicted from a model
    偏差:通常指测量值和某典型的预报值之间的差值。
  • Both parameters and observed values are considered as grey in dam safety monitoring models . grey parameters are identified by the means of the grey system theory and then forecasting values are given hi the format of grey interval . 4
    将大坝安全监控模型中的参数和实测数据均视为灰色,利用灰色系统方法对灰参数进行了辨识,并对大坝的监测效应量给出了灰色区间预报值
  • To limit the predicting precision loss in a certain range , author presented a method of bayes modeling and predicting for dynamic errors based on standard value interpolation at intervals during the multi - step prediction after consulting a lot of papers at home and abroad
    为将预报精度损失控制在一定的范围之内,作者在查阅了国内外大量相关文献之后,提出了基于标准量插入的动态测量误差的贝叶斯建模预报理论,并根据贝叶斯理论给出了预报值的不确定度。
  • To determine influence of technical conditions on product diameter , the influences of concentrations , molar ratio , reaction temperature and time on average size were investigated by means of uniform design . the results of experiments indicated that product diameter was mostly influenced by reaction temperature , followed by molar ratio of reactant , concentration of reactants , and reaction time . the optimum conditions were c ( co ( no3 ) 2 6h2o ) = 0 . 35mol / l , n ( co ( nh2 ) 2 ) : n ( co ( no3 ) 2 6h2o ) = 3 . 53 : 1 , reaction temperature 94 and reaction time 3 . 53h
    以产物的平均粒径( nm )为优化指标,选择硝酸钴浓度、反应物摩尔比、反应温度和反应时间四个因素,运用均匀试验设计技术进行3 ~ 5 1 ~ 3因素优化试验,发现反应温度对产物的粒径影响最大,其次分别为反应物摩尔比、硝酸钴浓度以及反应时间,并确定最佳反应条件为:硝酸钴浓度0 . 35mol l ,反应物摩尔比为3 . 53 : 1 ,反应温度94 ,反应时间3 . 53h ,预报值粒径y _ 1 = 19 . 57nm ,在此优化条件下制得的纳米co _ 3o _ 4平均粒径为22nm 。
  • In the final part of the paper , the feasibility of applying neural networks to evaluate the performance of the columns is investigated . a three - layer back - propagation network is trained using the earthquake - resistant behavior experimental data of the columns to predict the ductility of the columns . the predicted results agree well with the test results
    在论文的最后,探索应用人工神经网络对核心柱的力学性能进行评估的可能性,利用该柱抗震性能试验的结果,训练一个三层bp网络,进行了柱抗震延性的预报,预报值和试验值吻合良好。
  • As in many cases , people pay more attention to the relative error between actual output values and the idea output values , in this paper , an improved bp algorithm based on the smallest square sum of the relative error is proposed , which looks on the square sum of relative error between the idea output and the actual output as the object function
    考虑到在很多情况下,人们更关心预报模型的预报值与实际值的相对误差情况,从而本文采用实际输出与希望输出的相对误差的平方和作为目标函数,给出了一种基于相对误差平方和为最小的bp算法。
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