Abstract
Nephogram could provide important information for meteorological business, and nephogram recognition is a kind of challenge in the meteorological industry. In this paper, a selective neural network ensemble method based on K-means and Hadoop processing technology is proposed. This method combines the neural network, K-means clustering and AdaBoost in cloud environment. The experimental results show that the recognition precision of the method proposed by this paper is higher than that of traditional method in a stand-alone environment.
Highlights
In recent years, with the wide application of data mining and image recognition technology, more and more applications based on image processing technology have appeared in people’s daily life
Model description we propose a nephogram recognition technology based on cloud computing platform, which is composed of cloud platform and a nephogram recognition algorithm based on selective neural network
We propose a nephogram recognition algorithm based on selective neural network integration which can effectively solve the problem of low recognition model accuracy
Summary
With the wide application of data mining and image recognition technology, more and more applications based on image processing technology have appeared in people’s daily life. Because of the rapid rise in the volume of data, faster and more efficient computational techniques are required. A major benefit of big data is to provide timely information and proactive services for humans [6]. The advantages of cloud computing in data processing are obvious. It can meet different levels of requirements such as system changes, user needs and environmental changes. Cloud computing is an increase, use, and delivery model of Internetbased related services. Cloud computing is to calculate, transform, and store all resources to form a giant cloud network data storage platform. Storage and computing tasks are ideal for recognizing algorithms [7–9]
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