With the continuous development and progress of science and technology, agricultural production has entered the information age. In the tide of agricultural informatization, digital decision-making and intelligent automatic management are proposed. This paper follows the pace of the times, and also proposes the design of intelligent agricultural decision-making system based on machine learning, with the aim of improving the precision marketing and cultivation of agriculture. This paper mainly uses the analytic hierarchy process (AHP) and comparative method to analyze the intelligent agriculture decision-making system through systematic experiments. The experimental results show that the accuracy and safety coefficient of the system are more than 90%, which can be normally used in agricultural decision-making system.

Dahai Tan. Intelligent Agriculture Decision System Based on Machine Learning. Machine Learning Theory and Practice (2022), Vol. 3, Issue 3: 1-9. https://doi.org/10.38007/ML.2022.030301.

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