自回归积分移动平均
人工神经网络
机器学习
人工智能
计算机科学
支持向量机
随机森林
逻辑回归
时间序列
作者
CMAK Zeelan Basha,N Bhavana,Ponduru Bhavya,V. Sowmya
出处
期刊:2020 International Conference on Electronics and Sustainable Communication Systems (ICESC)
日期:2020-07-01
卷期号:: 92-97
被引量:97
标识
DOI:10.1109/icesc48915.2020.9155896
摘要
In India, Agriculture is the key point for survival. For agriculture, rainfall is most important. These days rainfall prediction has become a major problem. Prediction of rainfall gives awareness to people and know in advance about rainfall to take certain precautions to protect their crop from rainfall. Many techniques came into existence to predict rainfall. Machine Learning algorithms are mostly useful in predicting rainfall. Some of the major Machine Learning algorithms are ARIMA Model(Auto-Regressive Integrated Moving Average), Artificial Neural Network, Logistic Regression, Support Vector Machine and Self Organizing Map. Two commonly used models predict seasonal rainfall such as Linear and Non-Linear models. The first models are ARIMA Model. While using Artificial Neural Network(ANN) predicting rainfall can be done using Back Propagation NN, Cascade NN or Layer Recurrent Network. Artificial NN is same as Biological Neural Networks.
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