ELM在虫害预测中的应用研究

ELM(极限学习机)简单、易用,学习速度快且泛化性好,故将ELM引入虫害预测中。为了更好地提高ELM的效率和精度,首先采用模糊聚类对所有样本进行预处理,再把处理后的数据作为ELM的输入数据进行训练和预测。仿真实验结果表明,经过模糊聚类处理后,ELM预测精度较高,泛化性好,能够满足虫害预测对准确率和实时性的要求。通过实例,为虫害预测的应用提供一种新方法。

Applied Research of ELM in the Pest Forecast

ELM (Extreme Learning Machine) is easy to use. It has fast learning speed and good generalization. This paper researches pests forecast based on ELM. In order to improve the efficiency and accuracy of ELM ,this paper uses ELM to pretreat all samples and then traines, forecasts the processed data as the input data of the ELM.Simulation Experimental results show that ELM has high accuracy and good generalization which meets the requirements about accuracy and real-time. This paper supplies a new method to forecast pests according to the instance.