首页> 外文会议>Innovative Computing, Information and Control (ICICIC-2009), 2009 >An AI Estimator of Electric Contract Capacity for CATV System Based on QNN Model
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An AI Estimator of Electric Contract Capacity for CATV System Based on QNN Model

机译:基于QNN模型的有线电视系统电合同容量的AI估计

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In this paper, an AI estimator of electric contract capacity for community antenna television system (CATV) based on quantum neural network (QNN) is proposed. This intelligent estimator not only can make CATV company have a good planning on the development of TV network system and power demand, but also can greatly reduce the company's running cost. In this AI estimator, the neural model was used to execute the estimation of power demand. Due to the powerful learning capability of neural network, the nonlinear and complex relationships between power demand and its possible influencing factors could be automatically developed. Thus, such a well-trained neural model could be employed into the electricity demand estimation with high accuracy.
机译:本文提出了一种基于量子神经网络(QNN)的社区天线电视系统(CATV)电合同容量的AI估计器。这种智能的估算器不仅可以使CATV公司对电视网络系统的发展和电力需求进行良好的规划,而且可以大大降低公司的运营成本。在此AI估计器中,使用神经模型执行功率需求的估计。由于神经网络具有强大的学习能力,因此可以自动开发电力需求与其可能的影响因素之间的非线性和复杂关系。因此,可以将这种训练有素的神经模型高精度地用于电力需求估计中。

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