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Cognitive computing techniques based rainfall prediction — A study

机译:基于降雨预测的认知计算技术 - 一种研究

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The Primary source of agriculture in India is rainfall. Even though India has its own surplus fertile land, agriculture struggles a lot due to lack of efficient predictable rainfall technique which in turn leads to uncountable farmer's suicide activities. Nowadays, it becomes a back-breaking problem giving way to scarcity of food storage. Even Chennai faces a massive hit in 2015 december and 2016 december and flattens many residential areas and people started moving from their natives and starve for food with their small kids and old age people. So In this paper, cognitive computing prediction model methodologies, their outcomes and limitations are studied for the development of new hybrid cognitive model that supports the accuracy of prediction rate.
机译:印度的主要农业来源是降雨。尽管印度拥有自己的盈余土地,但由于缺乏有效的可预测的降雨技术,农业仍然困扰,这反过来导致不可数的农民的自杀活动。如今,它成为一种备份问题,让食物储存的稀缺。即使是钦奈也面临着2015年12月和2016年12月的大规模袭击,平稳许多住宅区和人们开始从他们的当地人迁移,并用他们的小孩子和老年人挨饿。因此,本文研究了认知计算预测模型方法,研究了支持预测率准确性的新混合认知模型的新的杂交认知模型。

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