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Modeling the thermal environment of data centers, including prediction of the air flow and temperature distributions can be computationally intensive using CFD. Reduced order models or data-driven meta-models are necessary to provide real-time assessment of optimum operating conditions for data centers to reduce energy usage. Here, a simulation-based Artificial Neural Network (ANN) approach is employed...
In this paper, an ordinal optimization based approach is proposed to solve for a good enough schedule that minimizes expected sum of storage expenses and tardiness penalties of stochastic classical job shop scheduling problem using limited computation time. The proposed approach consists of exploration and exploitation stage. The exploration stage uses a genetic algorithm to select a good candidate...
According to the high missing report rate and high false report rate of existing intrusion detection systems, the paper proposed an anomaly detection model based on genetic neural network, which combined the good global searching ability of genetic algorithm with the accurate local searching feature of BP Networks to optimize the initial weights of neural networks. The practice overcame the shortcomings...
The number of interconnects in any VLSI system is very large. During high speed interconnect analysis, interconnect effects like signal delay, crosstalk, ground bound noise, ringing and distortion become more significant. These interconnect effects, also known as signal integrity effects, must be taken in to account during digital circuit design. It is predicted that interconnects will be responsible...
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