计算机与现代化Issue(5)：33-37,45,6.DOI:10.3969/j.issn.1006-2475.2024.05.007
基于AFSPSO-ν-SVM的山洪灾害预测方法研究
Prediction Method of Mountain Flood Disaster Based on AFSPSO-ν-SVM
摘要
Abstract
With the development of science and technology,human engineering activities in mountainous areas are becoming in-creasingly frequent,which exacerbating the frequency of flash floods.Accurately and timely predicting the possibility of moun-tain flood disasters is of great significance for ensuring engineering safety,reducing economic losses,and improving personnel safety prevention capabilities.The application of artificial intelligence algorithms in predicting mountain flood disasters has be-come the focus of current researchers.In order to solve the problems of insufficient prediction accuracy caused by sensitivity dif-ferences in triggering factors of mountain floods,suboptimal model fitting effect caused by small sample data,and difficulty in determining nonlinear model parameters,the principal component analysis and ν support vector machines are combined for pre-dicting flash floods,using artificial fish swarm algorithm to expand the search range and speed of particles in particle swarm algo-rithm,and using improved particle swarm algorithm to optimize support vector machine parameters,AFSPSO-ν-SVM probabil-ity prediction model for mountain flood disasters is established.Through experiments,the proposed model was compared with BL models,ν-SVM model,PSO-ν-SVM model.The results of experiment show that the proposed model has the smallest error and the fastest speed.The paper provides a new approach for research in the field of flash flood forecasting and warning.关键词
人工鱼群算法/粒子群算法/支持向量机/山洪灾害/预测模型Key words
artificial fish swarm algorithm/particle swarm algorithm/support vector machine/mountain torrent disaster/pre-diction model分类
信息技术与安全科学引用本文复制引用
曹宁,徐根祺,张雯,许又文,何盼情,刘浩..基于AFSPSO-ν-SVM的山洪灾害预测方法研究[J].计算机与现代化,2024,(5):33-37,45,6.基金项目
陕西省自然科学基础研究计划项目(2023-JC-YB-464) （2023-JC-YB-464）
陕西省教育厅科学研究计划项目(23JP087) （23JP087）
国家自然科学基金资助项目(51578461) （51578461）
