An ensemble random forest model for seismic energy forecasting Sukh Sagar Shukla, Jaya Dhanya, Praveen Kumar, Varun Dutt Natural Hazards and Earth System Sciences, 2025 Seismic energy forecasting is critical for hazard preparedness, but current models have limits in accurately predicting seismic energy changes. This paper fills that gap by introducing a novel ensemble-based random forest framework for seismic energy forecasting. Building on a previously established methodology, the global energy time series is decomposed into intrinsic mode functions (IMFs) using ensemble empirical mode decomposition for better representation. Following this approach, we split the data into stationary (IMF1) and non-stationary (sum of IMF2–IMF6) components for modelling. We acknowledge the inadequacy of IMFs in capturing seismic energy dynamics, notably in anticipating the final values of the time series. To overcome this limitation, the yearly seismic energy time series and the stationary and non-stationary parts are also fed as inputs to the developed models. In this study, we employ the support vector machine (SVM), random forest (RF), instance-based learning (IBk), ridge regression (RR), and multi-layer perceptron (MLP) algorithms for the modelling. Furthermore, the five models discussed above are suitably employed in a stacked regression ensemble using random forest as the meta-learner to arrive at the final predictions. The root mean squared error (RMSE) obtained in the training and testing phases of the validation model is 0.127 and 0.134, respectively. It is observed that the performance of the developed ensemble model is superior to those existing in the literature. Further, the developed algorithm is employed for the seismic energy prediction in the active Western Himalayan region for a comprehensively compiled catalogue, and the mean forecasted seismic energy for year 2024 is 7.21 × 1014 J. This work is a pilot project that aims to create a robust, scalable framework for forecasting seismic energy release globally and regionally. The findings of our investigation demonstrate the promise of the ensemble approach in delivering reliable seismic energy forecast, which can help with appropriate hazard preparedness.
ANN-based broadband modelling of Fourier amplitude spectra through physics-based simulations: application to 2023 Elbistan earthquake V Sharma, J Dhanya, M Gade, HK Arya Journal of Seismology 30 (1), 10 , 2026 2026
A New Crustal Velocity Model for North-Western Himalayas and Siwalik Basin using Kriging Interpolation V Sharma, M Gade, J Dhanya AGU25 , 2025 2025
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An ensemble random forest model for seismic energy forecasting SS Shukla, J Dhanya, P Kumar, V Dutt Natural Hazards and Earth System Sciences 25 (10), 3713-3736 , 2025 2025 Citations: 2
Regional earthquake forecast model for M 6 using strain rate and seismicity for Western Himalayas SS Shukla, J Dhanya, M Gade Natural Hazards 121 (17), 20285-20317 , 2025 2025
A transfer learning-based ground motion model for Western Himalayas R Choudhary, V Sharma, J Dhanya, M Gade Acta Geophysica 73 (4), 3123-3146 , 2025 2025 Citations: 3
of Mizoram State, India SS Shukla, J Dhanya, STG Raghukanth Seismic Hazard Analyses, Wave Propagation and Site Characterization: Select … , 2025 2025
Earthquakes and Its Application Toward R Choudhary, J Dhanya Seismic Hazard Analyses, Wave Propagation and Site Characterization: Select … , 2025 2025
ANN-Based Ground Motion and Physics-Based Broadband Models for Vertical Spectra V Sharma, M Gade, J Dhanya Pure and Applied Geophysics 182 (2), 637-665 , 2025 2025
Probabilistic Seismic Risk Assessment of Mizoram State, India SS Shukla, J Dhanya, STG Raghukanth International Conference on Recent Advances in Geotechnical Earthquake … , 2024 2024
Machine Learning-Based Ground Motion Model for Subduction Zone Earthquakes and Its Application Toward Hazard Estimation of Northeast India R Choudhary, J Dhanya International Conference on Recent Advances in Geotechnical Earthquake … , 2024 2024
An ensemble random forest model for seismic energy forecast SS Shukla, J Dhanya, P Kumar, Priyanka, V Dutt Natural Hazards and Earth System Sciences Discussions 2024, 1-40 , 2024 2024 Citations: 5
Spatial correlation analysis for ANN generated physics-based broadband response spectra: A case study for 2023 Turkey events V Sharma, J Dhanya, M Gade, R Choudhary Journal of Earth System Science 133 (4), 203 , 2024 2024 Citations: 2
A simplified vector valued PSHA using principal components for seismic slope displacement hazard estimation M Gade, J Dhanya, PS Nayek Arabian Journal of Geosciences 17 (7), 209 , 2024 2024
Machine Learning-Based V/H Spectral Ratio Model for the Himalayan Region R Choudhary, SS Shukla, J Dhanya Indian Geotechnical Conference, 127-144 , 2023 2023
Characteristics of Near-Field Pulse-Like Records for Turkey Twin Earthquakes V Sharma, M Gade, J Dhanya International conference on Mediterranean Geosciences Union, 443-446 , 2023 2023
Analyzing the performance of univariate and multivariate machine learning models in soil movement prediction: A comparative study P Kumar, P Priyanka, J Dhanya, KV Uday, V Dutt IEEE Access 11, 62368-62381 , 2023 2023 Citations: 27
Statistical kinematic source models for seismic hazard estimations J Dhanya, STG Raghukanth International Journal of Advances in Engineering Sciences and Applied … , 2023 2023
New generalized ANN-based hybrid broadband response spectra generator using physics-based simulations V Sharma, J Dhanya, M Gade, J Sivasubramonian Natural Hazards 116 (2), 1879-1901 , 2023 2023 Citations: 16
MOST CITED SCHOLAR PUBLICATIONS
Ground motion prediction model using artificial neural network J Dhanya, STG Raghukanth Pure and Applied Geophysics 175 (3), 1035-1064 , 2018 2018 Citations: 154
3D seismic wave amplification in the Indo-Gangetic basin from spectral element simulations S Jayalakshmi, J Dhanya, STG Raghukanth, PM Mai Soil Dynamics and Earthquake Engineering 129, 105923 , 2020 2020 Citations: 49
Neural network-based hybrid ground motion prediction equations for Western Himalayas and North-Eastern India J Dhanya, STG Raghukanth Acta Geophysica 68 (2), 303-324 , 2020 2020 Citations: 45
Ground motion estimation during 25th April 2015 Nepal earthquake J Dhanya, M Gade, STG Raghukanth Acta Geodaetica et Geophysica 52 (1), 69-93 , 2017 2017 Citations: 43
Soil stabilization using raw plastic bottles A Ashraf, A Sunil, J Dhanya, M Joseph, M Varghese, M Veena Proceedings of Indian Geotechnical Conference, 15-17 , 2011 2011 Citations: 39
A new neural network–based prediction model for Newmark’s sliding displacements M Gade, PS Nayek, J Dhanya Bulletin of Engineering Geology and the Environment 80 (1), 385-397 , 2021 2021 Citations: 31
Analyzing the performance of univariate and multivariate machine learning models in soil movement prediction: A comparative study P Kumar, P Priyanka, J Dhanya, KV Uday, V Dutt IEEE Access 11, 62368-62381 , 2023 2023 Citations: 27
Seismic recurrence parameters for India and adjoined regions J Dhanya, KP Sreejaya, STG Raghukanth Journal of Seismology 26 (5), 1051-1075 , 2022 2022 Citations: 24
Hybrid broadband ground motion simulations in the Indo-Gangetic basin for great Himalayan earthquake scenarios S Jayalakshmi, J Dhanya, STG Raghukanth, PM Mai Bulletin of Earthquake Engineering 19 (9), 3319-3348 , 2021 2021 Citations: 21
New generalized ANN-based hybrid broadband response spectra generator using physics-based simulations V Sharma, J Dhanya, M Gade, J Sivasubramonian Natural Hazards 116 (2), 1879-1901 , 2023 2023 Citations: 16
A non-Gaussian random field model for earthquake slip J Dhanya, STG Raghukanth Journal of Seismology 23 (4), 889-912 , 2019 2019 Citations: 13
Probabilistic fling hazard map of India and adjoined regions J Dhanya, STG Raghukanth Journal of Earthquake Engineering 26 (9), 4712-4736 , 2022 2022 Citations: 9
3D crustal velocity model for ground motion simulations in North-East India S Sangeetha, J Dhanya, STG Raghukanth Journal of Earthquake Engineering 25 (3), 475-511 , 2021 2021 Citations: 8
Ground motion simulation for earthquakes in Sumatran region J Dhanya, STG Raghukanth Current Science, 1709-1720 , 2018 2018 Citations: 8
An ensemble random forest model for seismic energy forecast SS Shukla, J Dhanya, P Kumar, Priyanka, V Dutt Natural Hazards and Earth System Sciences Discussions 2024, 1-40 , 2024 2024 Citations: 5
Non-linear principal component analysis of response spectra STG RAGHUKANTH Journal of Earthquake Engineering 26 (4), 2148-2167 , 2022 2022 Citations: 5
A non-stationary random field model for earthquake slip J Dhanya, STG Raghukanth Journal of Seismology 24 (2), 423-441 , 2020 2020 Citations: 5
Effect of topography on earthquake ground motions A Dhabu, J Dhanya, STG Raghukanth Recent Advances in Structural Engineering, Volume 2: Select Proceedings of … , 2018 2018 Citations: 5
Predictive models for ground motion parameters using artificial neural network J Dhanya, D Sagar, STG Raghukanth Recent Advances in Structural Engineering, Volume 2: Select Proceedings of … , 2018 2018 Citations: 4
Forecasting of global earthquake energy time series STG Raghukanth, B Kavitha, J Dhanya Advances in Data Science and Adaptive Analysis 9 (04), 1750008 , 2017 2017 Citations: 4