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irn

  • 网络伊朗;中间路由选择节点;国际河网;信息资源网;国际河流网络
irnirn
  1. A Novel Rolling Work Fault Diagnosis Analysis Based on IRN Neural Network and its Application

    基于IRN网络的旋转件融合诊断方法与应用

  2. Vibration Fault Diagnosis of Hydroelectric Generation Sets Based on Spectrum Analysis and IRN Network

    基于频谱法和带偏差单元递归神经网络的水电机组振动故障诊断

  3. Ground Liquefaction Estimation Based on the Improved IRN Model

    基于一种改进的IRN模型的地基液化判别

  4. Forecast and control on temperature of massive concrete based on the irn model with the error unit

    基于带有偏差单元的IRN模型的大体积混凝土温度预测与控制

  5. Combining with concrete example , construct IRIS and IRN to organize information resources .

    结合实例,通过构造IRIS与IRN进行企业信息资源组织工作。

  6. The sulfur transformation during pyrolysis of used tires is studied in BFB reactor , and IRN neural network model is developed to test against observed behavior .

    对废轮胎在鼓泡流化床热解反应器中热解时硫的迁移行为进行了试验研究,并基于带偏差单元的IRN神经网络对其进行了预测。

  7. Objective To explore the clinical value of the immune rate nephelometry ( IRN ) in detecting the rate of serum κ and λ, and diagnosing multiple myeloma .

    目的探讨免疫速率散射比浊法测定血清κ/λ比值及其在多发性骨髓瘤中的临床价值。

  8. A radar emitter recognition algorithm based on Internally Recurrent Net ( IRN ) is presented . The latency incidence relation of radar parameters and radar threat type is studied .

    本文在研究带偏差单元内部回归神经网络(InternallyRecurrentNet,IRN)算法的基础上,分析了雷达特征参数和雷达威胁类型的内在联系;

  9. The limitation of the ground liquefaction estimation under the code empirical formula is analyzed and the concept of applying the improved Internally Recurrent Net ( IRN ) model to estimate ground liquefaction is brought out .

    分析了规范经验公式地基液化判别的局限性,提出应用改进的IRN模型进行地基液化判别的新思路。

  10. I was IRN the back ! Ooof a varn !

    我刚才在一个货车里面!

  11. Based on the internally recurrent net with deviation element , the computer simulation program of IRN is drawn up using Matlab , some simulation results of function approach and model distinguish are calculated , its capability is far away superior to that of BP algorithm .

    以一种带偏差单元的内部回归神经网络模型为基础,利用Matlab编制了IRN网络的仿真程序,给出了对函数逼近和模式识别方面的仿真算例,其学习收敛速度大大优于BP算法。