天气预报数据收集中一种有效的模糊c均值图约简综合方法

Malathy Sathyamoorthy, Rakesh Kumar, C. Vanitha, B. Sharma, V. Syamraj, Subrata Chowdhury
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引用次数: 0

摘要

专门的、地理上分散的无线传感器网络跟踪和记录环境物理条件,并将收集到的信息传输到一个中心点,被称为无线传感器网络。简单地说,无线传感器网络是收集环境数据的传感器网络。无线传感器网络是需要收集数据的实时项目的理想选择。这些网络可以用于各种任务,例如监测温度和湿度,该系统将收集有关受影响区域的数据。地震来临时,要提前向居住在这些地区的人们发出警告。通过使用传感器网络,该设备将能够预测一个地区的洪水水平,并为生活在受影响地区的人们提供有用的预测。采用基于机器学习的模糊c均值算法作为提出的算法,并以数据集的形式输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient Integrated approach of Fuzzy C-Means Map Reduce for Weather Forecasting Data Collection
Networks of specialized, geographically scattered wireless sensors that track and record environmental physical conditions and transmit the gathered information to a central point are known as wireless sensor networks. Simply Wireless sensor networks are networks of sensors that collect data about the environment. Wireless sensor networks are ideal for real-time projects that require the collection of data. These networks can be deployed for various tasks such as monitoring temperature and humidity this system will collect data about the areas affected. By the earthquake to give warning in advance to these people living those areas. Through the use of sensors networks, device will be able to predict the level of flooding in an area and provide helpful forecasts to the people living in the affected areas. A machine learning-based fuzzy c-means algorithm is used as the proposed algorithm and input in the form of a dataset.
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