水稻虫害预报模型数据

确定水稻品种，进行虫情预测。根据水稻当前物候期，基于历史经验数据，获取当地植保站水稻虫情预报信息，结合巡检人员巡检信息，对水稻可能发生或已经发生的虫情进行预报。1、数据采集：通过业务系统采集品种、水稻物候期、巡检虫害名称等信息；通过API调用当地植保站虫害名称等信息；通过虫情灯设备采集虫名称、数量数据，气象站监测温湿度、降雨量等数据。
2、数据处理：水稻虫害预报主要应用模糊推理算法中的多维模糊推理mdFMP进行数据处理。多维推理mdFMP，Ai，Ai’是论语Xi上的模糊集，Bi，Bi’是论域Y上的模糊集，i=1,2,…,n。存在一个X到[0,1]的有界函数F。利用FMP的算法进行运算得到结论B’（y）即为F（x）。得到结果值，包括虫害名称、危害虫态及危害状、发生规律、防治措施等。
3、数据应用：通过水稻虫害预报模型模拟预演，对水稻可能发生或已经发生的虫情进行预报，提醒农业主体提前做出防治措施，保障水稻的生产安全，以避免水稻遭受虫害侵袭。

Determine rice varieties and conduct pest situation prediction. Based on the current phenological stage of rice, historical empirical data, and local plant protection station's rice pest forecast information, combined with inspection information from patrol personnel, forecast the pest situation that may occur or has already occurred in rice.
1. Data Collection: Collect information such as rice varieties, rice phenological stages, and inspected pest names through the business system; call information such as local plant protection station's pest names via API; collect pest names and quantity data through pest light monitoring equipment, and monitor temperature, humidity, rainfall and other data via meteorological stations.
2. Data Processing: The rice pest forecast mainly uses the multi-dimensional fuzzy reasoning mdFMP in the fuzzy reasoning algorithm for data processing. For the multi-dimensional reasoning mdFMP, A_i and A'_i are fuzzy sets on the universe of discourse X_i, while B_i and B'_i are fuzzy sets on the universe of discourse Y, where i=1,2,…,n. There exists a bounded function F from X to [0,1]. Using the FMP algorithm to perform operations, the obtained conclusion B'(y) is exactly F(x). The obtained result values include pest names, harmful insect stages and damage symptoms, occurrence rules, control measures, etc.
3. Data Application: Through simulation and rehearsal of the rice pest forecast model, forecast the pest situation that may occur or has already occurred in rice, remind agricultural entities to take prevention and control measures in advance, and ensure the production safety of rice to avoid rice being attacked by pests.

搜集汇总

背景与挑战

背景概述

该数据集是用于水稻虫害预测的模型数据，包含97条记录，每日更新。数据涵盖水稻品种、物候期、环境因素（如温湿度、降雨量）和虫情监测信息，通过模糊推理算法处理，旨在预报虫害并提供防治建议，以保障水稻生产安全。数据集已进行知识产权登记和区块链存证，适用于农业虫情预警和决策支持。