Determining Suitability of Locations for Installation of Solar Power Station Based on Probabilistic Inference

2010 Ninth International Conference on Machine Learning and Applications Pub Date : 2010-12-12 DOI:10.1109/ICMLA.2010.169
I. Colak, Ş. Sağiroğlu, M. Demirtaş, H. Kahraman
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引用次数: 1

Abstract

This paper presents a novel system is to develop to determine the suitability of a location for installation of solar power stations. Necessary data including speed and direction of wind, solar radiation and rainfall are received from a meteorology station, and data acquired are then converted to the labels. Finally, the labels are evaluated in a Naive Bayes algorithm to determine the suitability of the location for the installation and axial structure of a Solar Power Plant. This helps to determine complicated calculations by means of the support system developed.
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基于概率推理的太阳能电站选址适宜性确定
本文提出了一种新的系统来确定太阳能电站安装地点的适宜性。从气象站接收风速和风向、太阳辐射和降雨量等必要数据，然后将获取的数据转换为标签。最后，用朴素贝叶斯算法对标签进行评估，以确定太阳能发电厂安装位置和轴向结构的适用性。这有助于通过开发的支持系统确定复杂的计算。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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2010 Ninth International Conference on Machine Learning and Applications
2010 Ninth International Conference on Machine Learning and Applications
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