Coarse-grained component models usually include support for asynchronous multi-threaded interactions, which loosens the temporal coupling of components.
粗粒度组件模型通常包括对异步多线程交互的支持，这样可以使组件的临时耦合松散化。
In this paper neural network partial least square (NNPLS) was used to establish a robust reaction model for a multi-component catalyst of methane oxidative coupling.
神经网络偏最小二乘法(NNPLS)被应用于一种甲烷氧化偶联多组分催化剂的鲁棒反应模型的建立。
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