Abstract: The Indian farming level decreases step by step inferable from certain components like inordinate usage of pesticides, water level decrement, environment changes, and unpredicted precipitation, and so forth on the farming information, elucidating investigation is performed to comprehend the creation level. The creation of yields isn't expanded inferable from these issues that influences the economy of farming. By utilizing AI strategies, the harvest from given dataset need to foresee by farming areas for forestalling this issue. Yield forecast is of extraordinary importance for yield planning, crop market arranging, crop protection, and gather the executives. Data mining based deep learning is turning out to be progressively significant in crop yield forecast. This strip-mined information will be wont to inform promoting selections, improve sales and abate on prices that has been made in this field by utilizing AI, particularly the Deep Learning (DL) strategy. Profound learning-based models are extensively used to extricate critical yield highlights for forecast. However, these techniques could resolve the yield forecast issue there exist the accompanying insufficiencies: Unable to make a direct non-straight or straight planning between the crude information and harvest yield esteems accuracy; and the exhibition of those models profoundly depends on the nature of the separated elements. Profound deep learning gives guidance and inspiration for the previously mentioned deficiencies. In this paper, I proposed two deep learning models namely ANN and LSTM considering into account the following parameters such as temperature, humidity, pH, rainfall respectively in each model which in turn were compared based on their accuracy level by limiting the blunder and expanding the conjecture accuracy. From my proposed work, I found LSTM is the model that provides us with the better accuracy that that of the ANN. The accuracy of the ANN model is 96.93548387096774 that is approximately 97% and that of the LSTM is 100 % which is obviously the highest. Keywords: Crop yield prediction, Deep learning, Data mining, ANN, LSTM, Accuracy.
Analysing the Accuracy of Crop Yield Prediction Using Deep Learning Algorithm