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Soil Moisture Prediction using Deep Neural Network Approach

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dc.contributor.author Modha, Hiren J.
dc.contributor.author Kothari, Ashish M.
dc.date.accessioned 2023-05-03T09:20:09Z
dc.date.available 2023-05-03T09:20:09Z
dc.date.issued 2022-07
dc.identifier.citation Modha, H.J., & Kothari, A.M. (2022). Soil Moisture Prediction using Deep Neural Network Approach. NeuroQuantology, 20(8), 4217-4229. Doi 10.14704/nq.2022.20.8.NQ44456 en_US
dc.identifier.issn 4217-4229
dc.identifier.uri http://10.9.150.37:8080/dspace//handle/atmiyauni/858
dc.description.abstract Soil moisture content is the most significant element in fit farming output and circulation of water, and its accurate forecast is critical regarding water resource management. Mostly soil moisture is complicated through structural features in addition to climatic complications. It’s tough to come up with an optimal mathematical model for soil moisture since there are so many variables for calculation. Presented forecasting models have issues with prediction accuracy, generality, plus other factors like Prediction performance, as well as multi-feature processing capabilities etc. considering all these factors taking Gallipoli, Turkey as a reference site for developing a deep neural network model to forecast moisture with good accuracy and minimum error. The dataset contains entities since 2008 to 2021. Doing quite a bit of mathematical analysis and establishing the correlation between selected features with the spearman coefficient, the appropriate weather data is able to give proper weight to forecast soil moisture. The output of the proposed method proves that the deep learning approach is realistic as well as efficient for the prediction of moisture. Also, deep learning technique is able to make model generalizations with excellent accuracy and minimum errors which is used to save irrigation water with controlling drought. en_US
dc.language.iso en en_US
dc.publisher NeuroQuantology en_US
dc.subject Deep Neural Network en_US
dc.subject Machine Learning en_US
dc.subject Multilayer Layer Perceptron (MLP) en_US
dc.subject Support Vector Machine (SVM) en_US
dc.subject Rectified Linear Activation Function (ReLU) en_US
dc.title Soil Moisture Prediction using Deep Neural Network Approach en_US
dc.type Article en_US


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