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Support Vector Machine (SVM) has advantages in small sample simulation prediction, but there is subjectivity in the selection of penalty factor C and kernel function parameter γ in SVM. Therefore, the Harris Hawks Optimization (HHO) algorithm was used to optimize C and γ in the SVM. And then the HHO-SVM mode was established to predict water quality in the Xiyuan tunnel section of Lake Dianchi Caohai. The results show that the prediction accuracy of the water quality prediction model based on HHO-SVM is higher than that of the SVM based on genetic algorithm (GASVM) and the SVM based on whale optimization algorithm (WOA-SVM). It is proved that the HHO is feasible to optimize the parameters in SVM, and HHO-SVM can be used in water quality prediction.

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支持向量机(SVM)在小样本模拟预测中具有优势,但其惩罚因子C和核函数参数γ的选取存在主观性,因此采用哈里斯鹰算法(HHO)对SVM的Cγ进行优化,建立基于HHO-SVM的水质预测模型,并应用于滇池草海西苑隧道断面的水质预测研究中。结果表明,HHO-SVM水质预测模型的预测精度高于基于遗传算法的支持向量机模型(GA-SVM)和基于鲸鱼算法的支持向量机模型(WOA-SVM),验证了HHO算法优化SVM参数的可行性,表明HHO-SVM可用于水质预测中。

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卢敏(1972-),女,副教授,研究方向为农业水土工程,E-mail:
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宋治岑(1995-),男,硕士研究生,研究方向为农业水土工程,E-mail:

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宋治岑(1995-),男,硕士研究生,研究方向为农业水土工程,E-mail:

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宋治岑(1995-),男,硕士研究生,研究方向为农业水土工程,E-mail:

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基于HHO-SVM的水质预测模型及应用
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宋治岑 , 张顺平 , 卢敏
水电能源科学 | 水文水资源与环境 2023,41(8): 70-72
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水电能源科学 | 水文水资源与环境 2023, 41(8): 70-72
基于HHO-SVM的水质预测模型及应用
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宋治岑 , 张顺平, 卢敏
作者信息
  • 云南农业大学水利学院,云南 昆明 650201
  • 宋治岑(1995-),男,硕士研究生,研究方向为农业水土工程,E-mail:

通讯作者:

卢敏(1972-),女,副教授,研究方向为农业水土工程,E-mail:
Water Quality Prediction Model Based on HHO-SVM and Its Application
Zhi-cen SONG , Shun-ping ZHANG, Min LU
Affiliations
  • School of Water Conservancy, Yunnan Agricultural University, Kunming 650201, China
出版时间: 2023-08-25 doi: 10.20040/j.cnki.1000-7709.2023.20221947
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支持向量机(SVM)在小样本模拟预测中具有优势,但其惩罚因子C和核函数参数γ的选取存在主观性,因此采用哈里斯鹰算法(HHO)对SVM的Cγ进行优化,建立基于HHO-SVM的水质预测模型,并应用于滇池草海西苑隧道断面的水质预测研究中。结果表明,HHO-SVM水质预测模型的预测精度高于基于遗传算法的支持向量机模型(GA-SVM)和基于鲸鱼算法的支持向量机模型(WOA-SVM),验证了HHO算法优化SVM参数的可行性,表明HHO-SVM可用于水质预测中。

哈里斯鹰算法  /  支持向量机  /  水质预测  /  应用

Support Vector Machine (SVM) has advantages in small sample simulation prediction, but there is subjectivity in the selection of penalty factor C and kernel function parameter γ in SVM. Therefore, the Harris Hawks Optimization (HHO) algorithm was used to optimize C and γ in the SVM. And then the HHO-SVM mode was established to predict water quality in the Xiyuan tunnel section of Lake Dianchi Caohai. The results show that the prediction accuracy of the water quality prediction model based on HHO-SVM is higher than that of the SVM based on genetic algorithm (GASVM) and the SVM based on whale optimization algorithm (WOA-SVM). It is proved that the HHO is feasible to optimize the parameters in SVM, and HHO-SVM can be used in water quality prediction.

Harris Hawks Optimization  /  Support Vector Machine  /  water quality prediction  /  application
宋治岑, 张顺平, 卢敏. 基于HHO-SVM的水质预测模型及应用. 水电能源科学, 2023 , 41 (8) : 70 -72 . DOI: 10.20040/j.cnki.1000-7709.2023.20221947
Zhi-cen SONG, Shun-ping ZHANG, Min LU. Water Quality Prediction Model Based on HHO-SVM and Its Application[J]. Water Resources and Power, 2023 , 41 (8) : 70 -72 . DOI: 10.20040/j.cnki.1000-7709.2023.20221947
2023年第41卷第8期
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doi: 10.20040/j.cnki.1000-7709.2023.20221947
  • 接收时间:2022-09-18
  • 首发时间:2026-01-28
  • 出版时间:2023-08-25
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  • 收稿日期:2022-09-18
  • 修回日期:2022-10-09
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    云南农业大学水利学院,云南 昆明 650201

通讯作者:

卢敏(1972-),女,副教授,研究方向为农业水土工程,E-mail:
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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