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ordered part中文是什么意思

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  • 例句与用法
  • Opn ordering part number
    分类零件号码
  • Parameter is the offset from the stack pointer to the high-order part of the value
    参数是距离值的高位部分堆栈指针的偏移量。
  • Parameter is the offset from the stack pointer to the low-order part of the value, and the
    参数是距离值的低位部分堆栈指针的偏移量,
  • When ordering parts, it is essential that the valve type, size, service and serial number be stated
    在订购部件时,务必说明阀门类型、通径、应用场合和系列号。
  • The following structure stores a signed 128-bit integer value as the constituent high-order and low-order parts
    下面的结构将有符号的128位整数值存储为高序部分和低序部分。
  • General motors created a service using soa patterns to enable automotive dealerships to order parts from a manufacturing facility using ebxml-based patterns and protocols
    generalmotors采用soa模式创建服务,让汽车代理商使用基于ebxml的模式和协议从生产厂家订购零部件。
  • For example, a service that orders parts from a vendor may require the ordering application to trust the vendor service and the vendor service to trust the ordering application
    例如,从供应商订购零件的服务可能要求订购应用程序信任供应商服务,并且供应商服务也信任订购应用程序。
  • 3 . the modeling method based on mechanism analysis and identification method always exits unmodeled high-order part and the modeling method based on neural networks usually has not good enough generalization capability . we fuse above two kinds of modeling method and put forward a hybrid modeling method based on mechanism analysis, identification and rbf neural networks . this paper proposed a hybr id modeling method based on mechanism analysis, identification and rbf neural networks . first, get a object's low-order model by the mechanism analysis and identification method . second, adopt rbf neural networks modeling method to compensate unmodeled high-order model . the sum of the low-order model and high-order model is the hybrid model . this kind of hybrid model has more accuracy than a model based on mechanism analysis and identification and has more generalization capability than a model based on neural networks
    针对基于机理分析和辨识的建模方法总是存在未建模的高阶部分,精度不够高和神经网络建模方法泛化能力差的缺点,将这两种建模方法进行融合,提出基于机理分析、系统辨识和rbf神经网络的混合建模方法,首先采用机理分析和辨识的方法得到工业对象的低阶模型,再用rbf神经网络建模方法补偿未建模高阶模型,这样得到的混合模型,比单纯基于机理分析和辨识的建模方法具有更高的精度,比单纯的神经网络的建模方法具有更好的泛化能力。
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Last modified time:Tue, 12 Aug 2025 00:29:56 GMT

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