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HIERARCHICAL CONCEPT BASED NEURAL NETWORK MODEL FOR DATA CENTER POWER USAGE EFFECTIVENESS PREDICTION
HIERARCHICAL CONCEPT BASED NEURAL NETWORK MODEL FOR DATA CENTER POWER USAGE EFFECTIVENESS PREDICTION
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机译:基于分层基于概念的数据中心功率使用效果预测的神经网络模型
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摘要
Systems and methods for a predicting power usage effectiveness (PUE) of a computer room with an optimized parameter using a Deep Concept Aggregation Neural Network (DCANN) algorithm based on hierarchical concept include receiving input feature parameters of a plurality of components associated with a computer room, and predicting the PUE of the computer room using a trained neural network, which comprises a hierarchical concept layer having embedded domain knowledge of the plurality of components placed between an input layer and a hidden layer.
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