首页 | 本学科首页   官方微博 | 高级检索  
     

基于PSO-LSSVM的甘蔗破头率预测
引用本文:陈远玲,高骁卿,班成周,梁浩昌,周家嘉. 基于PSO-LSSVM的甘蔗破头率预测[J]. 农机化研究, 2022, 44(5): 163-168. DOI: 10.3969/j.issn.1003-188X.2022.05.030
作者姓名:陈远玲  高骁卿  班成周  梁浩昌  周家嘉
作者单位:广西大学 机械工程学院, 南宁 530004
基金项目:国家自然科学基金项目(51665004);广西科技开发重点项目(2018AB01002)。
摘    要:甘蔗收割机收割后的甘蔗宿根破头率是评价甘蔗收割质量的重要指标,破头率过高会严重影响下一年甘蔗产量及甘蔗收割机的广泛推广与应用,但甘蔗破头率的采集方式复杂、费时费力,是研究降低甘蔗破头率的控制策略中的一项难题.为此,提出了一种基于PSO-LSSVM的甘蔗破头率预测方法,通过在田间采集甘蔗收割机刀盘与行走子系统的工作压力、...

关 键 词:甘蔗收割机  破头率  粒子群算法  最小二乘支持向量机

A Prediction Method of Sugarcane Brocken Roots Rate Based on PSO-LSSVM
Chen Yuanling,Gao Xiaoqing,Ban Chengzhou,Liang Haochang,Zhou Jiajia. A Prediction Method of Sugarcane Brocken Roots Rate Based on PSO-LSSVM[J]. Journal of Agricultural Mechanization Research, 2022, 44(5): 163-168. DOI: 10.3969/j.issn.1003-188X.2022.05.030
Authors:Chen Yuanling  Gao Xiaoqing  Ban Chengzhou  Liang Haochang  Zhou Jiajia
Affiliation:(College of Mechanical Engineering,Guangxi University,Nanning 530004,China)
Abstract:The rate of sugarcane roots breakage after harvesting by sugarcane harvester is an important index to evaluate the harvesting quality of sugarcane. The high breaking rate will seriously affect the yield of sugarcane and the widespread promotion on of sugarcane harvester. However,the collection method of sugarcane head breakage rate is complicated and time-consuming,which is a difficult problem in the research of control strategy to reduce sugarcane head breakage rate.To solve this problem,this paper proposes a prediction method of sugarcane roots breakage rate based on PSO-LSSVM.By collecting the working pressure and rotational speed signals of the cutter subsystem and the walking speed of sugarcane harvester in the field,and taking these signals as the input data and the sugarcane breaking roots rate as the output,a prediction model of sugarcane roots breaking rate based on PSO-LSSVM was established.
Keywords:sugarcane harvester  brocken bennial roots rate  least squares support vector machine(LSSVM)  PSO-LSSVM
本文献已被 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号