Suchergebnisse - genetics algorithm‐backpropagation neural network*

Fusion of rough set theory, genetic algorithm-backpropagation neural networks and Shapley additive explanations for the design of bamboo furniture

Autoren: Zhongchen Huang Li Ye

Quelle: BioResources, Vol 20, Iss 3, Pp 7107-7133 (2025)

Schlagwörter: kansei engineering, bamboo furniture, bamboo chair, shapley additive explanations, genetic algorithm-backpropagation neural networks, TP248.13-248.65, rough set theory, Biotechnology

Zugangs-URL: https://doaj.org/article/6845f7fe5af04af490ceaa2eca5171b5

Intelligent Assessment of Urban Drainage Pipeline System based on Genetic Algorithm-Backpropagation Neural Network

Autoren: Shiran Zhang

Quelle: 2025 4th International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE). :1-8

Seafloor topography refinement from multisource data using genetic algorithm—backpropagation neural network

Autoren: Chunhong Wu Xinwen Su Chuang Xu et al.

Quelle: Geophysical Journal International. 238:1417-1428

Schlagwörter: 14. Life underwater, 01 natural sciences, 0105 earth and related environmental sciences

Constitutive Modeling of A286 Superalloy: Comparison of Improved Khan-Huang-Liang, Improved Johnson-Cook, and Genetic Algorithm-Backpropagation Artificial Neural Network Models

Autoren: Liang Tao Zhiguo Feng Yulian Jiang et al.

Quelle: Journal of Materials Engineering and Performance.

Prediction modeling of cigarette ventilation rate based on genetic algorithm backpropagation (GABP) neural network

Autoren: Jiaxin Wei Zhengwei Wang Shufang Li et al.

Quelle: EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-14 (2024)

Schlagwörter: Tobacco, Multiple linear regression, BP neural network, Genetics algorithm, Ventilation rate, Telecommunication, TK5101-6720, Electronics, TK7800-8360

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1687-6180

Zugangs-URL: https://doaj.org/article/916de498397e4dafb0505d24617d98ad

Enhanced backpropagation neural network accuracy through an improved genetic algorithm for tourist flow prediction in an ecological village

Autoren: Xiaolong Chen Cora Un In Wong Hongfeng Zhang et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-22 (2025)

Schlagwörter: Ourist flow prediction, BP neural network, Genetic algorithm, Ecological scenic area, Adaptive optimization, Nonlinear forecasting, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/1b24c6128b294fd395eb4efb58b11205

Constitutive Modeling of A286 Superalloy: Comparison of Improved Khan-Huang-Liang, Improved Johnson-Cook, and Genetic Algorithm-Backpropagation Artificial Neural Network Models.

Autoren: Tao, Liang Feng, Zhiguo Jiang, Yulian et al.

Quelle: Journal of Materials Engineering & Performance; Dec2025, Vol. 34 Issue 23, p28170-28182, 13p

Schlagwörter: GENETIC algorithms, ARTIFICIAL neural networks, YIELD stress, HEAT resistant alloys, MECHANICAL models, COMPUTER simulation

Optimizing phosphorus fertilizer application to balance potato yield and quality: A neural network analysis

Autoren: Shuo Kong Yonglin Qin Jing Yu et al.

Quelle: Scientia Horticulturae, Vol 355, Iss , Pp 114550- (2026)

Schlagwörter: Potato, Quality, Artificial neural networks, Phosphorus application rate, Genetic algorithm–backpropagation, Plant culture, SB1-1110

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0304423825005977; https://doaj.org/toc/1879-1018

Zugangs-URL: https://doaj.org/article/26163f49134942d9a95e6340c4c6ea6a

Optimized parameters for the preparation of silk fibroin drug‐loaded microspheres based on the response surface method and a genetic algorithm–backpropagation neural network model

Autoren: Xujing Zhang Yan Xu Jianping Zhou

Quelle: Journal of Biomedical Materials Research Part B: Applied Biomaterials. 109:6-18

Schlagwörter: Drug Carriers, Drug Compounding, Temperature, 02 engineering and technology, In Vitro Techniques, Microspheres, Drug Liberation, 03 medical and health sciences, 0302 clinical medicine, Models, Chemical, Isoniazid, Neural Networks, Computer, Particle Size, Fibroins, 0210 nano-technology

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/32748484
https://europepmc.org/article/MED/32748484
https://onlinelibrary.wiley.com/doi/10.1002/jbm.b.34676
https://www.ncbi.nlm.nih.gov/pubmed/32748484

Enhanced backpropagation neural network accuracy through an improved genetic algorithm for tourist flow prediction in an ecological village.

Autoren: Chen, Xiaolong Wong, Cora Un In Zhang, Hongfeng et al.

Quelle: Scientific Reports; 10/15/2025, Vol. 15 Issue 1, p1-22, 22p

Schlagwörter: GENETIC algorithms, SUSTAINABLE tourism, TRAFFIC estimation, TOURISM, ARTIFICIAL neural networks, NONLINEAR theories, SUSTAINABLE communities

Comparative evaluation of backpropagation neural network and genetic algorithm-backpropagation neural network models for PM2.5 concentration prediction based on aerosol optical depth, meteorological factors, and air pollutants

Autoren: Jilin Gu Shuang Liang Qiao Song et al.

Quelle: Journal of Applied Remote Sensing. 18

Carbon Dioxide Emissions Prediction in China: A Genetic Algorithm-backpropagation Neural Network Approach

Autoren: Yan Du Hui Liu Mowen Xie et al.

Schlagwörter: 13. Climate action, 11. Sustainability, 7. Clean energy

Increasing the Accuracy of Soil Nutrient Prediction by Improving Genetic Algorithm Backpropagation Neural Networks.

Autoren: Liu, Yanqing Jiang, Cuiqing Lu, Cuiping et al.

Quelle: Symmetry (20738994). Jan2023, Vol. 15 Issue 1, p151. 15p.

Schlagwörter: *GENETIC algorithms, *ARTIFICIAL neural networks, *PREDICTION models, *SOIL acidity, *FORECASTING

Geografische Kategorien: CHINA

Optimized wind power prediction and energy storage scheduling using genetic algorithm and backpropagation neural network

Autoren: Peng Wu Zongze Li

Quelle: International Journal of Renewable Energy Development, Vol 14, Iss 1, Pp 146-157 (2025)

Schlagwörter: genetic algorithm, backpropagation neural network, support vector machine, wind power prediction, energy storage scheduling, Renewable energy sources, TJ807-830

Dateibeschreibung: electronic resource

Relation: https://ijred.cbiore.id/index.php/ijred/article/view/60434; https://doaj.org/toc/2252-4940

Zugangs-URL: https://doaj.org/article/029f1b8f7f5c4c7ab4aec0ab1e39b955

Prediction of Short-Term Winter Photovoltaic Power Generation Output of Henan Province Using Genetic Algorithm–Backpropagation Neural Network

Autoren: Dawei Xia Ling Li Buting Zhang et al.

Quelle: Processes. 12:1516

Schlagwörter: 13. Climate action, 11. Sustainability, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Porosity Characterization of Thermal Barrier Coatings by Ultrasound with Genetic Algorithm Backpropagation Neural Network

Autoren: Shuxiao Zhang Gaolong Lv Shifeng Guo et al.

Quelle: Complexity, Vol 2021 (2021)

Schlagwörter: Electronic computers. Computer science, 0103 physical sciences, QA75.5-76.95, 02 engineering and technology, 0210 nano-technology, 01 natural sciences

Dateibeschreibung: text/xhtml

Zugangs-URL: https://downloads.hindawi.com/journals/complexity/2021/8869928.pdf
https://doaj.org/article/de253953e566470190465f282e9d3a43
https://downloads.hindawi.com/journals/complexity/2021/8869928.pdf
https://philpapers.org/rec/ZHAPCO-3
https://ideas.repec.org/a/hin/complx/8869928.html
https://www.hindawi.com/journals/complexity/2021/8869928/
https://dblp.uni-trier.de/db/journals/complexity/complexity2021.html#ZhangLGZF21
http://downloads.hindawi.com/journals/complexity/2021/8869928.pdf

Parameter sensitivity analysis for diesel spray penetration prediction based on GA-BP neural network

Autoren: Yifei Zhang Gengxin Zhang Dawei Wu et al.

Quelle: Energy and AI, Vol 18, Iss , Pp 100443- (2024)

Schlagwörter: Machine learning, Genetic Algorithm-Backpropagation, Fuel spray penetration, Parametric sensitivity analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Computer software, QA76.75-76.765

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666546824001095; https://doaj.org/toc/2666-5468

Zugangs-URL: https://doaj.org/article/43ca6ba7e70e4fcc829677ad1337247b

The Application of Genetic Algorithm Backpropagation Neural Network Model on the Prediction and Optimization of Wastewater Treatment System

Autoren: Fu Quan Jia Zhu Jun Tian Zhang Wei He et al.

Quelle: Advanced Materials Research. :2525-2531

Schlagwörter: 11. Sustainability, 01 natural sciences, 6. Clean water, 0105 earth and related environmental sciences, 12. Responsible consumption, 3. Good health

Zugangs-URL: https://www.scientific.net/AMR.838-841.2525

Detecting coal content in gangue via machine vision and genetic algorithm-backpropagation neural network

Autoren: Chunlong Zhang Dongyang Dou Fengjie Sun et al.

Quelle: Measurement. 201:111739

Schlagwörter: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Climate change impacts on wildfire risk indices forecast based on an improved genetic neural network algorithm: a case study of Guangxi, China.

Autoren: Zhang, Shuo Pan, Mengya

Quelle: Earth Science Informatics. Mar2025, Vol. 18 Issue 3, p1-16. 16p.