Combining principal component regression and artificial neural network to predict chlorophyll-a concentration of Yuqiao Reservoir's outflow

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作者：

College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China ^{[1
]}

不详 ^{[2
]}

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来源：

Trans. Tianjin Univ. | / 6卷 / 467-472期

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Compendex;

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摘要：

Neural networks

引用

共 32 条

[1] Combining Principal Component Regression and Artificial Neural Network to Predict Chlorophyll-a Concentration of Yuqiao Reservoir’s Outflow
张旋
王启山
于淼
吴京
Transactions of Tianjin University, 2010, (06) : 467 - 472
[2] Combining principal component regression and artificial neural network to predict chlorophyll-a concentration of Yuqiao Reservoir's outflow
Zhang X.
Wang Q.
Yu M.
Wu J.
Transactions of Tianjin University, 2010, 16 (6) : 467 - 472
[3] Combining Principal Component Regression and Artificial Neural Network to Predict Chlorophyll-a Concentration of Yuqiao Reservoir’s Outflow
张旋
王启山
于淼
吴京
Transactions of Tianjin University, 2010, 16 (06) : 467 - 472
[4] Prediction of chlorophyll-a concentration in Dahuofang reservoir based on BP neural network
Meng, W. (mengwei012345@sina.com), 1792, Northeast University (34):
[5] Determination of the Optimal Training Principle and Input Variables in Artificial Neural Network Model for the Biweekly Chlorophyll-a Prediction: A Case Study of the Yuqiao Reservoir, China
Liu, Yu
Xi, Du-Gang
Li, Zhao-Liang
PLOS ONE, 2015, 10 (03):
[6] Prediction of chlorophyll-a in the Daning River of Three Gorges Reservoir by principal component scores in multiple linear regression models
Wang Liping
Zheng Binghui
WATER SCIENCE AND TECHNOLOGY, 2013, 67 (05) : 1150 - 1158
[7] Identification and Quantification of Physicochemical Parameters Influencing Chlorophyll-a Concentrations through Combined Principal Component Analysis and Factor Analysis: A Case Study of the Yuqiao Reservoir in China
Chen, Ran
Ju, Meiting
Chu, Chunli
Jing, Weiqiang
Wang, Yuqiu
SUSTAINABILITY, 2018, 10 (04)
[8] Principal Component Regression with Artificial Neural Network to Improve Prediction of Electricity Demand
Ismail, Noor
Abdullah, Syamnd
INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2016, 13 (1A) : 196 - 202
[9] A novel approach to predict chlorophyll-a in coastal-marine ecosystems using multiple linear regression and principal component scores
Franklin, Jayaseelan Benjamin
Sathish, Thadikamala
Vinithkumar, Nambali Valsalan
Kirubagaran, Ramalingam
MARINE POLLUTION BULLETIN, 2020, 152
[10] PRINCIPAL COMPONENT ANALYSIS (PCA) FOR ESTIMATING CHLOROPHYLL CONCENTRATION USING FORWARD AND GENERALIZED REGRESSION NEURAL NETWORKS
Zounemat-Kermani, Mohammad
APPLIED ARTIFICIAL INTELLIGENCE, 2014, 28 (01) : 16 - 29

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