344 related articles for article (PubMed ID: 32609717)
1. The deformation monitoring of foundation pit by back propagation neural network and genetic algorithm and its application in geotechnical engineering.
Luo J; Ren R; Guo K
PLoS One; 2020; 15(7):e0233398. PubMed ID: 32609717
[TBL] [Abstract][Full Text] [Related]
2. Prediction of fetal weight based on back propagation neural network optimized by genetic algorithm.
Gao H; Wu C; Huang D; Zha D; Zhou C
Math Biosci Eng; 2021 May; 18(4):4402-4410. PubMed ID: 34198444
[TBL] [Abstract][Full Text] [Related]
3. The GA-BPNN-Based Evaluation of Cultivated Land Quality in the PSR Framework Using Gaofen-1 Satellite Data.
Liu S; Peng Y; Xia Z; Hu Y; Wang G; Zhu AX; Liu Z
Sensors (Basel); 2019 Nov; 19(23):. PubMed ID: 31771107
[TBL] [Abstract][Full Text] [Related]
4. Prediction model for the water jet falling point in fire extinguishing based on a GA-BP neural network.
Zhang C; Zhang R; Dai Z; He B; Yao Y
PLoS One; 2019; 14(9):e0221729. PubMed ID: 31483808
[TBL] [Abstract][Full Text] [Related]
5. Stability Analysis of Geotechnical Landslide Based on GA-BP Neural Network Model.
Xu J; Zhao Y
Comput Math Methods Med; 2022; 2022():3958985. PubMed ID: 35770123
[TBL] [Abstract][Full Text] [Related]
6. An Apple Fungal Infection Detection Model Based on BPNN Optimized by Sparrow Search Algorithm.
Zhao C; Ma J; Jia W; Wang H; Tian H; Wang J; Zhou W
Biosensors (Basel); 2022 Aug; 12(9):. PubMed ID: 36140077
[TBL] [Abstract][Full Text] [Related]
7. Prediction of the sorption efficiency of heavy metal onto biochar using a robust combination of fuzzy C-means clustering and back-propagation neural network.
Ke B; Nguyen H; Bui XN; Bui HB; Nguyen-Thoi T
J Environ Manage; 2021 Sep; 293():112808. PubMed ID: 34034129
[TBL] [Abstract][Full Text] [Related]
8. Prediction of the compressive strength of high-performance self-compacting concrete by an ultrasonic-rebound method based on a GA-BP neural network.
Du G; Bu L; Hou Q; Zhou J; Lu B
PLoS One; 2021; 16(5):e0250795. PubMed ID: 33939736
[TBL] [Abstract][Full Text] [Related]
9. A data-driven model for real-time water quality prediction and early warning by an integration method.
Jin T; Cai S; Jiang D; Liu J
Environ Sci Pollut Res Int; 2019 Oct; 26(29):30374-30385. PubMed ID: 31440975
[TBL] [Abstract][Full Text] [Related]
10. Enhancement predicting accuracy for elastin-like polypeptides temperature transition by back propagation neural network.
Huang KZ; Xiong XK; Zhang CM; Lai YY; Zou CN; Zhang GY; Hua ZC
Protein Pept Lett; 2014; 21(10):1065-72. PubMed ID: 24758491
[TBL] [Abstract][Full Text] [Related]
11. Application of artificial neural networks to assess pesticide contamination in shallow groundwater.
Sahoo GB; Ray C; Mehnert E; Keefer DA
Sci Total Environ; 2006 Aug; 367(1):234-51. PubMed ID: 16460784
[TBL] [Abstract][Full Text] [Related]
12. Application of Optimized GA-BPNN Algorithm in English Teaching Quality Evaluation System.
Zhu Y; Xu J; Zhang S
Comput Intell Neurosci; 2021; 2021():4123254. PubMed ID: 35003243
[TBL] [Abstract][Full Text] [Related]
13. [Near infrared spectroscopy quantitative analysis model based on incremental neural network with partial least squares].
Cao H; Li DH; Liu L; Zhou Y
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Oct; 34(10):2799-803. PubMed ID: 25739228
[TBL] [Abstract][Full Text] [Related]
14. [Multi-index optimization of extraction process of Fengyin Decoction based on BAS-GA-BP neural network combined with entropy weight method].
Lan JL; Ruan YP; Qiu LQ
Zhongguo Zhong Yao Za Zhi; 2020 Dec; 45(23):5686-5693. PubMed ID: 33496108
[TBL] [Abstract][Full Text] [Related]
15. Backpropagation neural network assisted concentration prediction of biconical microfiber sensors.
Zhang Y; Li M; Lin Z; Zhang X; Dai H; Liu J; Yu H; Wu Z; Pu J
Opt Express; 2020 Dec; 28(25):37566-37576. PubMed ID: 33379589
[TBL] [Abstract][Full Text] [Related]
16. Multi-sensor information fusion detection system for fire robot through back propagation neural network.
Zhang J; Ye Z; Li K
PLoS One; 2020; 15(7):e0236482. PubMed ID: 32706794
[TBL] [Abstract][Full Text] [Related]
17. Prediction of the roughness coefficient for drainage pipelines with sediments using GA-BPNN.
Sun B; Zheng W; Tong A; Di D; Li Z
Water Sci Technol; 2023 Aug; 88(4):1111-1130. PubMed ID: 37651341
[TBL] [Abstract][Full Text] [Related]
18. Application of hybrid artificial intelligence model to predict coal strength alteration during CO
Yan H; Zhang J; Zhou N; Li M
Sci Total Environ; 2020 Apr; 711():135029. PubMed ID: 31812377
[TBL] [Abstract][Full Text] [Related]
19. Prediction model of spontaneous combustion risk of extraction borehole based on PSO-BPNN and its application.
Wang W; Liang R; Qi Y; Cui X; Liu J
Sci Rep; 2024 Jan; 14(1):5. PubMed ID: 38168106
[TBL] [Abstract][Full Text] [Related]
20. Monitoring and Prediction of Horizontal Displacement of Underground Enclosure Piles in Subway Foundation Pits.
Dong Y; Luan Y; Wang F; Yang H; Jia Z; Luan H
ACS Omega; 2023 Jul; 8(26):23389-23400. PubMed ID: 37426226
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]