• These algorithms take into account load statistics based on the number of currently outstanding I/O operations of the server adapters in selecting the next path for an I/O operation.

    根据在为I/O操作选择下一个路径时服务器适配器当前杰出 I/O操作的数量,这些算法会考虑到加载统计数据。

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  • You can use a storage policy to set up a storage area farm to increase throughput by distributing the I/O load.

    可以使用存储策略建立一个存储区域场,通过分布I/O负载提高吞吐量。

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  • Differently from SEDA, it uses a simpler load-management mechanism for I/O because components are much more fine-grained and promises are used to receive results of operations.

    与SEDA不同的是,它对I/O使用了更加简单的负载管理机制,因为组件更加细粒度化并且 promise可用来接收操作结果。

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  • In traditional way, we use concentrate treatment to store all data into the database and then to deal with them, this method increases I/O load and need time to manage data.

    在传统的处理方式中,采用了集中处理方式,实时保存清分结果数据,极大地增加了系统的I/O负载和处理所需时间。

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  • The author has established the mechanical model of O-chain iron and U-chain iron respectively, obtained the computing formula of load and stress, and contrasted with example.

    本文分别建立了O形环与U形环的力学模型,推导出了载荷、应力分布的计算公式,并引用实例进行了对比分析。

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  • The O-cell pile testing (OPT) method is a new axial static load test of pile.

    自平衡试桩是一种新的静荷载试桩方法。

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  • After revamping, heat load was increased by 8.5% while the temperature in the furnace hearth was decreased. The objective o...

    改造后热负荷提高了8.5%,同时降低了炉膛温度,并能在高效率、大负荷下长周期安全运行。

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  • An analytical solution transformation method (ASTM) of transforming the data of the O-cell pile testing method into the conventional load-settlement is put forward.

    提出了一种自平衡试桩结果转化成传统静载试验曲线的解析法。

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  • By analyzing the data of O-cell pile testing, new load transfer models before and after post grouting are proposed.

    通过分析自平衡试桩数据,提出了注浆前后荷载传递函数模型。

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  • An improved model based on RBF neural network for medium and long-term load forecasting is presented. The feasibility and validity o...

    实际算例的分析表明,所提出的基于RBF神经网络的缺损数据处理方法和改进的中长期负荷预测模型是可行和有效的。

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  • O Load Multiple Samples…

    载入多个样本…

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  • O Load Multiple Samples…

    载入多个样本…

    youdao

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