Research on Intelligent Information Processing and Decision Support Methods in Modern Agricultural and Forestry Economic Management

With the rapid development of information technology, modern agroforestry economic management is gradually integrating intelligent information processing and decision support system to improve the efficiency and quality of decision making. In this study, a decision support system for the agroforestry economy is developed, which uses convolutional neural networks and an improved coordinated attention mechanism module (MA) as the intelligent information processing method. The algorithms such as fuzzy hierarchical analysis and entropy weight method are integrated to make a comprehensive judgment on economic decisions related to agroforestry. The system in this paper has a decision reasoning accuracy of 100% for integrated fostering and a decision accuracy of 98.47% for integrated decision making. For decision support of agroforestry projects, the comprehensive judgment results calculated by the system in this paper are consistent with the results given by experts. The intelligent information processing technology selected in this paper has an accuracy of 99.62% in predicting the yield of an agricultural and forestry cash crop in a specific area. The system in this paper can optimize the planting area of agroforestry cash crops with higher economic benefits. In conclusion, the decision support system using integrated intelligent information processing technology can improve the accuracy and efficiency of decision-making and promote the sustainable development of the agroforestry economy.