Research on Intelligent Agricultural Decision System Based on Machine Learning Algorithm

Firstly, the application status and problems of machine learning in modern intelligent agricultural production were introduced. A smart agricultural monitoring system design based on Internet of Things technology and machine learning algorithm was proposed. A sensor node for collecting agricultural environment information is designed, and a wireless sensor network composed of ZigBee nodes is used to sense and detect agricultural environment information. The application software system developed by Qt software technology can manage and display the agricultural environment information. Secondly, a smart agricultural decision system based on machine learning is constructed by using decision tree algorithm to analyze the problem. The communication method based on blackboard model is adopted to avoid the complicated communication design of session layer. In the decision-making process of knowledge, ontology is combined with the current mature rule-based reasoning technology. It is proved that this system can make timely and accurate decision according to the change of agricultural environment, and carry out dynamic adaptive learning according to historical data.