均方误差
平均绝对百分比误差
平均绝对误差
灌溉
农业
水分
含水量
农业工程
统计
环境科学
数学
土壤科学
水文学(农业)
气象学
工程类
农学
地理
岩土工程
考古
生物
作者
Sukhwinder Singh,Sanmukh Kaur,Parteek Kumar
出处
期刊:Lecture notes in electrical engineering
日期:2019-11-30
卷期号:: 145-156
被引量:3
标识
DOI:10.1007/978-981-15-0313-9_11
摘要
Precision agriculture is a technique that is incorporated to produce high crop yield with the best utilization of available resources. Traditional farming is adversely affected due to improper resource management. In order to overcome the efforts of a farmer, a model for the soil moisture forecasting has been proposed in this manuscript to deliver better after-effects of farming. The proposed model uses long short-term memory (LSTM) to predict soil moisture. The model is trained on a dataset acquired from IIT Kanpur agricultural site. For analyzing the performance of the model mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), and root mean squared error (RMSE) has been used as performance metrics. This paper is paving way for the early prediction of the soil moisture that can be used with other advanced innovative irrigation techniques.
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