[1]
|
Prediction of earthquake based on artificial neural network technique
2ND INTERNATIONAL CONFERENCE FOR ENGINEERING SCIENCES AND INFORMATION TECHNOLOGY (ESIT 2022): ESIT2022 Conference Proceedings,
2024
DOI:10.1063/5.0190668
|
|
|
[2]
|
Proceedings of the International Field Exploration and Development Conference 2023
Springer Series in Geomechanics and Geoengineering,
2024
DOI:10.1007/978-981-97-0272-5_23
|
|
|
[3]
|
Earthquake forecasting in the Himalayan region using neural networks models
Sādhanā,
2024
DOI:10.1007/s12046-023-02398-4
|
|
|
[4]
|
Enhancing Precipitation Prediction in the Ziz Basin: A Comprehensive Review of Traditional and Machine Learning Approaches
E3S Web of Conferences,
2024
DOI:10.1051/e3sconf/202448904010
|
|
|
[5]
|
Data Intelligence and Cognitive Informatics
Algorithms for Intelligent Systems,
2024
DOI:10.1007/978-981-99-7962-2_24
|
|
|
[6]
|
A Global Earthquake Prediction Model Based on Spherical Convolutional LSTM
IEEE Transactions on Geoscience and Remote Sensing,
2024
DOI:10.1109/TGRS.2024.3380573
|
|
|
[7]
|
A Global Earthquake Prediction Model Based on Spherical Convolutional LSTM
IEEE Transactions on Geoscience and Remote Sensing,
2024
DOI:10.1109/TGRS.2024.3380573
|
|
|
[8]
|
Application value of artificial intelligence algorithm-based magnetic resonance multi-sequence imaging in staging diagnosis of cervical cancer
Open Life Sciences,
2024
DOI:10.1515/biol-2022-0733
|
|
|
[9]
|
Intelligent IT Solutions for Sustainability in Industry 5.0 Paradigm
Lecture Notes in Electrical Engineering,
2024
DOI:10.1007/978-981-97-1682-1_30
|
|
|
[10]
|
GIS, Applied Computing and Data Science for Water Management
Lecture Notes in Geoinformation and Cartography,
2024
DOI:10.1007/978-3-031-63038-5_12
|
|
|
[11]
|
Enhancing daily rainfall prediction in urban areas: a comparative study of hybrid artificial intelligence models with optimization algorithms
Applied Water Science,
2023
DOI:10.1007/s13201-023-02036-8
|
|
|
[12]
|
A Spatiotemporal Model for Global Earthquake Prediction Based on Convolutional LSTM
IEEE Transactions on Geoscience and Remote Sensing,
2023
DOI:10.1109/TGRS.2023.3302316
|
|
|
[13]
|
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences
Algorithms for Intelligent Systems,
2023
DOI:10.1007/978-981-19-8742-7_20
|
|
|
[14]
|
Cyber Security, Cryptology, and Machine Learning
Lecture Notes in Computer Science,
2023
DOI:10.1007/978-3-031-34671-2_11
|
|
|
[15]
|
A Spatiotemporal Model for Global Earthquake Prediction Based on Convolutional LSTM
IEEE Transactions on Geoscience and Remote Sensing,
2023
DOI:10.1109/TGRS.2023.3302316
|
|
|
[16]
|
Cyber Security, Cryptology, and Machine Learning
Lecture Notes in Computer Science,
2023
DOI:10.1007/978-3-031-34671-2_11
|
|
|
[17]
|
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences
Algorithms for Intelligent Systems,
2023
DOI:10.1007/978-981-19-8742-7_20
|
|
|
[18]
|
Earthquake alerting based on spatial geodetic data by spatiotemporal information transformation learning
Proceedings of the National Academy of Sciences,
2023
DOI:10.1073/pnas.2302275120
|
|
|
[19]
|
Disaster Risk Reduction in Agriculture
Disaster Resilience and Green Growth,
2023
DOI:10.1007/978-981-99-1763-1_22
|
|
|
[20]
|
Earthquake magnitude prediction using a VMD-BP neural network model
Natural Hazards,
2023
DOI:10.1007/s11069-023-05856-8
|
|
|
[21]
|
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences
Algorithms for Intelligent Systems,
2023
DOI:10.1007/978-981-19-8742-7_20
|
|
|
[22]
|
Applications of machine learning for earthquake prediction: A review
AL-KADHUM 2ND INTERNATIONAL CONFERENCE ON MODERN APPLICATIONS OF INFORMATION AND COMMUNICATION TECHNOLOGY,
2023
DOI:10.1063/5.0119623
|
|
|
[23]
|
Earthquake magnitude prediction using a VMD-BP neural network model
Natural Hazards,
2023
DOI:10.1007/s11069-023-05856-8
|
|
|
[24]
|
Artificial neural network approaches for disaster management: A literature review
International Journal of Disaster Risk Reduction,
2022
DOI:10.1016/j.ijdrr.2022.103276
|
|
|
[25]
|
Bagging–XGBoost algorithm based extreme weather identification and short-term load forecasting model
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.06.072
|
|
|
[26]
|
Artificial neural network approaches for disaster management: A literature review
International Journal of Disaster Risk Reduction,
2022
DOI:10.1016/j.ijdrr.2022.103276
|
|
|
[27]
|
Gated Recurrent Units Based Recurrent Neural Network for Forecasting the Characteristics of the Next Earthquake
Cybernetics and Systems,
2022
DOI:10.1080/01969722.2021.1981637
|
|
|
[28]
|
Multi-Step Forecasting of Earthquake Magnitude Using Meta-Learning Based Neural Networks
Cybernetics and Systems,
2022
DOI:10.1080/01969722.2021.1989170
|
|
|
[29]
|
Artificial neural network approaches for disaster management: A literature review
International Journal of Disaster Risk Reduction,
2022
DOI:10.1016/j.ijdrr.2022.103276
|
|
|
[30]
|
Correlating the Unconfined Compressive Strength of Rock with the Compressional Wave Velocity Effective Porosity and Schmidt Hammer Rebound Number Using Artificial Neural Networks
Rock Mechanics and Rock Engineering,
2022
DOI:10.1007/s00603-022-02992-8
|
|
|
[31]
|
EPM–DCNN: Earthquake Prediction Models Using Deep Convolutional Neural Networks
Bulletin of the Seismological Society of America,
2022
DOI:10.1785/0120220058
|
|
|
[32]
|
Bagging–XGBoost algorithm based extreme weather identification and short-term load forecasting model
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.06.072
|
|
|
[33]
|
Bagging–XGBoost algorithm based extreme weather identification and short-term load forecasting model
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.06.072
|
|
|
[34]
|
Bagging–XGBoost algorithm based extreme weather identification and short-term load forecasting model
Energy Reports,
2022
DOI:10.1016/j.egyr.2022.06.072
|
|
|
[35]
|
Attention-Based Bi-Directional Long-Short Term Memory Network for Earthquake Prediction
IEEE Access,
2021
DOI:10.1109/ACCESS.2021.3071400
|
|
|
[36]
|
Earthquake Prediction by Using Time Series Analysis
2021 9th International Symposium on Digital Forensics and Security (ISDFS),
2021
DOI:10.1109/ISDFS52919.2021.9486358
|
|
|
[37]
|
Earthquake Magnitude Prediction using Spatia-temporal Features Learning Based on Hybrid CNN- BiLSTM Model
2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS),
2021
DOI:10.1109/ICSPIS54653.2021.9729358
|
|
|
[38]
|
Case Studies in Building Constructions
Building Pathology and Rehabilitation,
2021
DOI:10.1007/978-3-030-55893-2_3
|
|
|
[39]
|
Intelligent Systems
Lecture Notes in Networks and Systems,
2021
DOI:10.1007/978-981-33-6081-5_41
|
|
|
[40]
|
Geoinformatics-based assessment of land deformation and damage zonation for Gorkha earthquake, 2015, using SAR interferometry and ANN approach
SN Applied Sciences,
2021
DOI:10.1007/s42452-021-04574-9
|
|
|
[41]
|
Latest Developments in Geotechnical Earthquake Engineering and Soil Dynamics
Springer Transactions in Civil and Environmental Engineering,
2021
DOI:10.1007/978-981-16-1468-2_21
|
|
|
[42]
|
Neural networks for long-term earthquake prediction using modified meta-learning
Journal of Intelligent & Fuzzy Systems,
2021
DOI:10.3233/JIFS-210173
|
|
|
[43]
|
DLEP: A Deep Learning Model for Earthquake Prediction
2020 International Joint Conference on Neural Networks (IJCNN),
2020
DOI:10.1109/IJCNN48605.2020.9207621
|
|
|
[44]
|
Earthquake Prediction using Seismic Information
International Journal of Scientific Research in Computer Science, Engineering and Information Technology,
2020
DOI:10.32628/CSEIT2063107
|
|
|
[45]
|
Application of Artificial Intelligence in Predicting Earthquakes: State-of-the-Art and Future Challenges
IEEE Access,
2020
DOI:10.1109/ACCESS.2020.3029859
|
|
|
[46]
|
Development of advanced artificial intelligence models for daily rainfall prediction
Atmospheric Research,
2020
DOI:10.1016/j.atmosres.2020.104845
|
|
|
[47]
|
GNSS positioning accuracy improvement based on surface meteorological parameters using artificial neural networks
International Journal of Communication Systems,
2020
DOI:10.1002/dac.4373
|
|
|
[48]
|
Earthquake Prediction Based on Spatio-Temporal Data Mining: An LSTM Network Approach
IEEE Transactions on Emerging Topics in Computing,
2020
DOI:10.1109/TETC.2017.2699169
|
|
|
[49]
|
LSTM-based Models for Earthquake Prediction
Proceedings of the 3rd International Conference on Networking, Information Systems & Security,
2020
DOI:10.1145/3386723.3387865
|
|
|
[50]
|
Reliability optimization design method based on multi-level surrogate model
Eksploatacja i Niezawodność – Maintenance and Reliability,
2020
DOI:10.17531/ein.2020.4.7
|
|
|
[51]
|
LSTM-based Models for Earthquake Prediction
Proceedings of the 3rd International Conference on Networking, Information Systems & Security,
2020
DOI:10.1145/3386723.3387865
|
|
|
[52]
|
Earthquake prediction based on Bi-LSTM+CRF model and Spatio-Temporal Data
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC),
2020
DOI:10.1109/ITAIC49862.2020.9339192
|
|
|
[53]
|
LSTM-based Models for Earthquake Prediction
Proceedings of the 3rd International Conference on Networking, Information Systems & Security,
2020
DOI:10.1145/3386723.3387865
|
|
|
[54]
|
GNSS positioning accuracy improvement based on surface meteorological parameters using artificial neural networks
International Journal of Communication Systems,
2020
DOI:10.1002/dac.4373
|
|
|
[55]
|
Earthquake Magnitude Prediction Using Recurrent Neural Networks
The 2nd International Electronic Conference on Geosciences,
2019
DOI:10.3390/IECG2019-06213
|
|
|
[56]
|
Precursory Pattern based Feature Extraction Techniques for Earthquake Prediction
IEEE Access,
2019
DOI:10.1109/ACCESS.2019.2902224
|
|
|
[57]
|
Emerging Research in Computing, Information, Communication and Applications
Advances in Intelligent Systems and Computing,
2019
DOI:10.1007/978-981-13-5953-8_36
|
|
|
[58]
|
Short-term prediction of the earthquake through Neural Networks and Meta-Learning
2019 16th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE),
2019
DOI:10.1109/ICEEE.2019.8884562
|
|
|
[59]
|
Daily Peak Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm
Energies,
2018
DOI:10.3390/en11010163
|
|
|
[60]
|
Forecasting of Energy-Related CO2 Emissions in China Based on GM(1,1) and Least Squares Support Vector Machine Optimized by Modified Shuffled Frog Leaping Algorithm for Sustainability
Sustainability,
2018
DOI:10.3390/su10040958
|
|
|
[61]
|
Forecasting of Power Grid Investment in China Based on Support Vector Machine Optimized by Differential Evolution Algorithm and Grey Wolf Optimization Algorithm
Applied Sciences,
2018
DOI:10.3390/app8040636
|
|
|
[62]
|
Determining Neuronal Number in Each Hidden Layer Using Earthquake Catalogues as Training Data in Training an Embedded Back Propagation Neural Network for Predicting Earthquake Magnitude
IEEE Access,
2018
DOI:10.1109/ACCESS.2018.2870189
|
|
|
[63]
|
Daily Peak Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm
Energies,
2018
DOI:10.3390/en11010163
|
|
|
[64]
|
Forecasting of Energy-Related CO2 Emissions in China Based on GM(1,1) and Least Squares Support Vector Machine Optimized by Modified Shuffled Frog Leaping Algorithm for Sustainability
Sustainability,
2018
DOI:10.3390/su10040958
|
|
|
[65]
|
Forecasting of Power Grid Investment in China Based on Support Vector Machine Optimized by Differential Evolution Algorithm and Grey Wolf Optimization Algorithm
Applied Sciences,
2018
DOI:10.3390/app8040636
|
|
|
[66]
|
Snow Disaster Early Warning in Pastoral Areas of Qinghai Province, China
Remote Sensing,
2017
DOI:10.3390/rs9050475
|
|
|
[67]
|
Snow Disaster Early Warning in Pastoral Areas of Qinghai Province, China
Remote Sensing,
2017
DOI:10.3390/rs9050475
|
|
|