亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

A Comparison of Methods for Investigating the Quantitative Relationships Between Empoasca onukii Matsuda (Hemiptera: Cicadellidae) and its Natural Enemies

相似性(几何) 相关系数 灰色关联分析 统计 数学 排名(信息检索) 余弦相似度 亲密度 计算机科学 人工智能 图像(数学) 数学分析 聚类分析
作者
Shiyan Chen,Junjie Cai,Honghao Cheng,Yunding ZOU
标识
DOI:10.51963/jers.v25i1.2304
摘要

To systematically study the quantitative relationship between natural enemies and pests, this paper used grey relational analysis method, angular cosine coefficient method, fuzzy similarity priority ratio method and correlation coefficient method to analyze the closeness of the quantitative relationship between natural enemies and Empoasca onukii Matsuda in “Anjibaicha”, “Huangshandayezhong” and “Longjing 43” tea plantations. The conclusions obtained by the grey relational analysis method were used as a criterion to compare the sum of the rankings of the top three natural enemies, Plexippus paykulli, Tetragnatha squamata and Ebrechtella tricuspidata, thus comparing and discussing the similarities and differences between the conclusions obtained by the four research methods. The angular cosine coefficient method and grey relational analysis method yielded no major differences in conclusions, followed by the correlation coefficient method, with the fuzzy similarity priority ratio method yielding more varied results. According to the ranking analysis of the close relationship between the number of E. onukii and its natural enemies, Tetragnatha squamata, Hylyphantes graminicola and Ebrechtella tricuspidata are the first three natural enemies closely related to the number of E. onukii. This paper is an attempt to compare the consistency of research results of various research methods, which provides a reference for selecting research methods in analyzing the quantitative relationship between natural enemies and pests.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
9秒前
30秒前
35秒前
38秒前
46秒前
在水一方应助LucyMartinez采纳,获得10
49秒前
utopia完成签到,获得积分10
50秒前
59秒前
LucyMartinez发布了新的文献求助10
1分钟前
1分钟前
量子星尘发布了新的文献求助10
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
科研通AI2S应助ceeray23采纳,获得20
1分钟前
科研通AI6应助科研通管家采纳,获得10
1分钟前
2分钟前
2分钟前
酷波er应助LucyMartinez采纳,获得10
2分钟前
2分钟前
2分钟前
2分钟前
ceeray23发布了新的文献求助20
2分钟前
LucyMartinez发布了新的文献求助10
2分钟前
Panther完成签到,获得积分10
2分钟前
Lucas应助蓝色牛马采纳,获得10
2分钟前
chloe完成签到,获得积分10
2分钟前
Emma完成签到 ,获得积分10
2分钟前
Azure完成签到 ,获得积分10
3分钟前
3分钟前
思柔完成签到,获得积分10
3分钟前
蓝色牛马发布了新的文献求助10
3分钟前
3分钟前
桐桐应助朴素豪采纳,获得10
3分钟前
科研通AI6应助科研通管家采纳,获得10
3分钟前
科研通AI6应助科研通管家采纳,获得10
3分钟前
丘比特应助科研通管家采纳,获得10
3分钟前
Akim应助科研通管家采纳,获得10
3分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to strong mixing conditions volume 1-3 5000
Human Embryology and Developmental Biology 7th Edition 2000
The Developing Human: Clinically Oriented Embryology 12th Edition 2000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
Ägyptische Geschichte der 21.–30. Dynastie 1520
„Semitische Wissenschaften“? 1510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5739702
求助须知:如何正确求助?哪些是违规求助? 5388560
关于积分的说明 15339909
捐赠科研通 4882093
什么是DOI,文献DOI怎么找? 2624126
邀请新用户注册赠送积分活动 1572850
关于科研通互助平台的介绍 1529667