Knowledge extracting system for non-expert miners

P. Ramya, S. Mohanavalli, S. Sasirekha
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引用次数: 2

Abstract

Argo is a global array of 3,000 free-drifting profiling floats that will measure the temperature, pressure and salinity of the upper 2000 m of the ocean. This will allow continuous monitoring of the climate state of the ocean, with all data being relayed and made publicly available within hours after collection. Conceptually, Argo builds on the existing upper-ocean thermal networks, extending their spatial and temporal coverage, depth range and accuracy, and enhancing them through addition of salinity and velocity measurements. Also the float reads its latitude and longitude values. All these information in combination called as dataset and processed with some pre-processing and mining strategies. Pre-processing technique allows to extract the features that are required to define the ocean behaviour. Mining defines the similar patterns present in the dataset. Extracted pattern describes the behaviour of saline water by giving the tsunami alerts and PFZ's.
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面向非专业矿工的知识提取系统
Argo是一个由3000个自由漂流剖面浮标组成的全球阵列,将测量海洋2000米以上的温度、压力和盐度。这将允许对海洋气候状况进行持续监测,所有数据在收集后数小时内被转发并公开。从概念上讲,Argo建立在现有的上层海洋热网络的基础上,扩展了它们的空间和时间覆盖范围、深度范围和精度,并通过增加盐度和速度测量来增强它们。此外,浮动读取其纬度和经度值。所有这些信息组合在一起称为数据集,并通过一些预处理和挖掘策略进行处理。预处理技术允许提取定义海洋行为所需的特征。挖掘定义数据集中出现的类似模式。提取的模式通过给出海啸警报和PFZ来描述咸水的行为。
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