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Ultra-short-term photovoltaic power prediction based on modal reconstruction and BiLSTM-CNN-Attention model Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-19 Wei Liu, Qian Liu, Yulin Li
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RadonPotential: An interactive web application for radon potential prediction under different climates and soil textures Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-19 Juan Jose Galiana-Merino, Sara Gil-Oncina, Javier Valdes-Abellan, Juan Luis Soler-Llorens, David Benavente
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A lightweight building change detection network with coordinate attention and multiscale fusion Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-17 Weipeng Le, Liang Huang
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Determining future scenarios of urban areas with cellular automata/Markov Chain Model method; example of Ereğli District Konya-Türkiye (2030–2040) Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-16 Taha Kağan Aydın, S. Savaş Durduran
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Rainfall-runoff modeling using machine learning in the ungauged urban watershed of Quetta Valley, Balochistan (Pakistan) Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-15 Ghunwa Shah, Arjumand Zaidi, Abdul Latif Qureshi, Shahzad Hussain, Rizwan, Tarique Aziz
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Ontology-driven relational data mapping for constructing a knowledge graph of porphyry copper deposits Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-13 Chengbin Wang, Liangquan Tan, Yuanjun Li, Mingguo Wang, Xiaogang Ma, Jianguo Chen
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A novel machine learning approach for interpolating seismic velocity and electrical resistivity models for early-stage soil-rock assessment Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-12 Mbuotidem David Dick, Andy Anderson Bery, Nsidibe Ndarake Okonna, Kufre Richard Ekanem, Yasir Bashir, Adedibu Sunny Akingboye
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ENSO dataset & comparison of deep learning models for ENSO forecasting Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-10 Shabana Mir, Masood Ahmad Arbab, Sadaqat ur Rehman
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Groundwater level estimation using improved deep learning and soft computing methods Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-09 Amin Mirboluki, Mojtaba Mehraein, Ozgur Kisi, Alban Kuriqi, Reza Barati
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Physics-informed loss functions for vertical total electron content forecast Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-09 Eric Nana Asamoah, Massimo Cafaro, Italo Epicoco, Giorgiana De Franceschi, Claudio Cesaroni
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CEDG-GeoQA: Knowledge base question answering for the geoscience domain via Chinese entity description graph Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-09 Lai Wei, Qinghua Lu, Yilin Duan, Hong Yao, Xiaojun Kang
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Surface water extraction from high-resolution remote sensing images based on an improved U-net network model Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-08 Guoqing Wang, Guoxu Chen, Bin Sui, Li’ao Quan, Er’rui Ni, Jianxin Zhang
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Adaptive direct sampling-based approach to ore grade modeling Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-06 ZhangLin Li, ShuiHan Yi, Ning Wang, XiaLin Zhang, Qiyu Chen, Gang Liu
While gaining recognition, the Multiple-Point Geostatistics (MPS) method faces limitations in its application to mineral resource reserve estimation due to a lack of standardized parameter-setting practices. To address this challenge, this paper proposes an adaptive MPS parameter optimization framework based on optimization algorithms, which is implemented by a particle swarm algorithm (PSO) and direct
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An improved multi-filter fusion indoor localization algorithm based on INS and UWB Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-04
Abstract With the increasing demand for indoor services based on location information, the importance of achieving accurate indoor positioning has become increasingly prominent. However, wireless sensor networks (WSNs) are impacted by non-line-of-sight (NLOS) transmissions when transmitting signals, resulting in decreased positioning accuracy. In contrast, The Inertial Navigation System (INS) operates
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Quantification and mapping of the carbon sequestration potential of soils via a quantile regression forest model Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-04
Abstract Understanding the soil carbon sequestration potential is vital for decision-making related to crop and soil management and for prioritizing the area for carbon sequestration and climate change mitigation. In the present study, we mapped the soil carbon sequestration potential (CSP) along with its uncertainty over two depth ranges (0–30 cm and 0–100 cm) in parts of Western Ghats, Kerala, India
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Machine learning regression algorithms for predicting the susceptibility of jointed rock slopes to planar failure Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-03
Abstract Stability assessment of road cut slopes is not only difficult, but also time-consuming due to the complexity in material properties, coupled with the presence of structural discontinuities. Conventional methods of assessment and simulation of rock slope failures come up with several challenges for geotechnical engineers. This study attempts to develop machine learning models using linear regression
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Satellite image classification using deep learning approach Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-03 Divakar Yadav, Kritarth Kapoor, Arun Kumar Yadav, Mohit Kumar, Arti Jain, Jorge Morato
Our planet Earth comprises distinguished topologies based on temperature, location, latitude, longitude, and altitude, which can be captured using Remote Sensing Satellites. In this paper, the classification of satellite images is performed based on their topologies and geographical features. Researchers have worked on several machine learning and deep learning methods like support vector machine,
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Innovative agricultural diagnosis: DQRR-AFH algorithm model for effective leaf disease prevention and monitoring Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-03 S. L. Bharathi, N. Deepa, J. Sathya Priya, K. Muthulakshmi
In recent decades agricultural decision-making system has played a vital role in the field monitoring process. For these emerging technologies like the Internet of Things (IoT), artificial intelligence (AI), and wireless sensors are utilized for precise data extraction and analysis. However numerous techniques are developed for increasing agricultural production and enhancing operational efficiency
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An improved edge detector for interpreting potential field data Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-02 Luan Thanh Pham
Mapping geologic features, such as faults and contacts, often involves extracting the edges of potential field sources, which is popularly done using a variety of different edge detectors. Nevertheless, these detectors have general drawbacks, such as low-resolution output or dependence on the source depth. To address these problems, an improved edge detector that employs the unit step function of the
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Random Forest and Multilayer Perceptron hybrid models integrated with the genetic algorithm for predicting pan evaporation of target site using a limited set of neighboring reference station data Earth Sci. Inform. (IF 2.8) Pub Date : 2024-04-01
Abstract This study explores the application of machine learning algorithms for the prediction of pan evaporation (Ep), which is a critical factor in water resource management for the assessment of water demand and usage. Specifically, this research evaluates the effectiveness of two base models: Random Forest (RF) and Multi-Layer Perceptron (MLP) and their optimized counterparts using a Genetic Algorithm
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Forecasting groundwater fluctuations caused by earthquakes using fuzzy logic and AHP Method: A case study from Iran Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-14 Hossein Rashidi Gooya, Homayoon Katibeh, Amjad Maleki
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Spatiotemporal analysis of land surface temperature trends in Nashik, India: A 30-year study from 1992 to 2022 Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-12 Kratika Sharma, Ritu Tiwari, Arun Kumar Wadhwani, Shobhit Chaturvedi
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MS-YOLO: integration-based multi-subnets neural network for object detection in aerial images Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-12 Xinyu Cao, Minglei Duan, Hongwei Ding, Zhijun Yang
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Assessment of groundwater level using satellite-based hydrological parameters in North-West India: A deep learning approach Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-12 Pranshu Pranjal, Dheeraj Kumar, Ashish Soni, R. S. Chatterjee
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A reliable and energy-aware end-to-end routing approach in sdn/fog-based iout Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-12 Reza Mohammadi
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Reliability of Monte Carlo simulation approach for estimating uniaxial compressive strength of intact rock Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-11 Adeyemi Emman Aladejare, Kayode Augustine Idowu, Toochukwu Ozoji
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Identifying pre-seismic ionospheric disturbances using space geodesy: A case study of the 2011 Lorca earthquake (Mw 5.1), Spain Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-11
Abstract This research work examines earthquake-induced ionospheric anomalies through an in-depth analysis of Total Electron Content (TEC) parameter. It involves modeling the ionospheric F2-layer by processing geodetic and geophysical data to generate regional TEC maps. Additionally, a geodetic approach is developed for short-term seismic hazard prediction, grounded in seismo-ionospheric interactions
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Design and implementation of an Automatic Deep Stacked Sparsely Connected Convolutional Autoencoder (ADSSCCA) neural network for remote sensing lithological mapping using calculated dropout Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-09 Charlie Gael Atangana Otele, Mathias Akong Onabid, Patrick Stephane Assembe
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An eXtreme Gradient Boosting prediction of uplift capacity factors for 3D rectangular anchors in natural clays Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-09 Duy Tan Tran, Tinnapat Onjaipurn, Divesh Ranjan Kumar, Weeraya Chim-Oye, Suraparb Keawsawasvong, Pitthaya Jamsawang
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Efficiency analysis of ITN loss function for deep semantic building segmentation Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-09 Mohammad Erfan Omati, Fatemeh Tabib Mahmoudi
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Post-stack seismic inversion through probabilistic neural networks and deep forward neural networks Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-08 Víctor Sotelo, Ovidio Almanza, Luis Montes
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How does extreme point sampling affect non-extreme simulation in geographical random forest? Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-08 Hui Wang, Meixu Chen, Zhe Wang, Li Huang, Christopher C. Caudill, Shijin Qu, Xiang Que
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KG-Unet: a knowledge-guided deep learning approach for seismic facies segmentation Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-08 Xiang-Ye Zhang, Wan-Li Wang, Guang-Min Hu, Xing-Miao Yao
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Comparison of tree-based ensemble learning algorithms for landslide susceptibility mapping in Murgul (Artvin), Turkey Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-04
Abstract Turkey’s Artvin province is prone to landslides due to its geological structure, rugged topography, and climatic characteristics with intense rainfall. In this study, landslide susceptibility maps (LSMs) of Murgul district in Artvin province were produced. The study employed tree-based ensemble learning algorithms, namely Random Forest (RF), Light Gradient Boosting Machine (LightGBM), Categorical
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Clustering the temporal distribution pattern of sub-daily precipitations over Iran Earth Sci. Inform. (IF 2.8) Pub Date : 2024-03-04 Kousha Hoghoughinia, Bahram Saghafian, Saleh Aminyavari
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Correction to: Deep learning-based 1-D magnetotelluric inversion: performance comparison of architectures Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-24 Mehdi Rahmani Jevinani, Banafsheh Habibian Dehkordi, Ian J. Ferguson, Mohammad Hossein Rohban
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A systematic review of Earthquake Early Warning (EEW) systems based on Artificial Intelligence Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-24 Pirhossein Kolivand, Peyman Saberian, Mozhgan Tanhapour, Fereshteh Karimi, Sharareh Rostam Niakan Kalhori, Zohreh Javanmard, Soroush Heydari, Seyed Saeid Hoseini Talari, Seyed Mohsen Laal Mousavi, Maryam Alidadi, Mahnaz Ahmadi, Seyed Mohammad Ayyoubzadeh
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A multiscale road matching method based on hierarchical road meshes Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-22 Yuzhu Wang, Haowen Yan, Pengbo Li, Xiaomin Lu
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Incremental learning-random forest model-based landslide susceptibility analysis: A case of Ganzhou City, China Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-21 Xu Wang, Wen Nie, Wei Xie, Yang Zhang
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Application of geophysical and multispectral imagery data for predictive mapping of a complex geo-tectonic unit: a case study of the East Vardar Ophiolite Zone, North-Macedonia Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-20 Filip Arnaut, Dragana Đurić, Uroš Đurić, Mileva Samardžić-Petrović, Igor Peshevski
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OpenEOcubes: an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-19 Brian Pondi, Marius Appel, Edzer Pebesma
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Constraint information extraction for 3D geological modelling using a span-based joint entity and relation extraction model Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-16 Can Zhuang, Chunhua Liu, Henghua Zhu, Yuhong Ma, Guoping Shi, Zhizheng Liu, Bohan Liu
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AI-driven reinforced optimal cloud resource allocation (ROCRA) for high-speed satellite imagery data processing Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-15 Uma Maheswara Rao Inkollu, J. K. R. Sastry
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K-Means Featurizer: A booster for intricate datasets Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-15 Kouao Laurent Kouadio, Jianxin Liu, Rong Liu, Yongfei Wang, Wenxiang Liu
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Exploring effect of scale dependency in LST downscaling – using convolution neural network-extreme learning machine (CNN-ELM) Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-14 Jidnyasa Patil, Sandeep Maithani, Surendra Kumar Sharma
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Multidimensional displacement analysis of Semeru Volcano, Indonesia following December 2021 eruption from multitrack InSAR observation Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-14 Argo Galih Suhadha, Harintaka Harintaka
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Deep learning-driven regional drought assessment: an optimized perspective Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-13 Chandrakant M. Kadam, Udhav V. Bhosle, Raghunath S. Holambe
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Urban building function classification based on multisource geospatial data: a two-stage method combining unsupervised and supervised algorithms Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-13 Shouhang Du, Meiyun Zheng, Liyuan Guo, Yuhui Wu, Zijuan Li, Peiyi Liu
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Extraction of Surface Water Bodies using Optical Remote Sensing Images: A Review Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-12 R Nagaraj, Lakshmi Sutha Kumar
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A SMOTified extreme learning machine for identifying mineralization anomalies from geochemical exploration data: a case study from the Yeniugou area, Xinjiang, China Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-12 Alina Shayilan, Yongliang Chen
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Reservoir porosity assessment and anomaly identification from seismic attributes using Gaussian process machine learning Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-08 Maulana Hutama Rahma Putra, Maman Hermana, Ida Bagus Suananda Yogi, Touhid Mohammad Hossain, Muhammad Faris Abdurrachman, Said Jadid A. Kadir
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Impacts of DEM type and resolution on deep learning-based flood inundation mapping Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-07
Abstract The increasing availability of hydrological and physiographic spatiotemporal data has boosted machine learning’s role in rapid flood mapping. Yet, data scarcity, especially high-resolution DEMs, challenges regions with limited access. This paper examines how DEM type and resolution affect flood prediction accuracy, utilizing a cutting-edge deep learning (DL) method called 1D convolutional
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Rainfall variability over multiple cities of India: analysis and forecasting using deep learning models Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-06 Jagabandhu Panda, Nistha Nagar, Asmita Mukherjee, Saugat Bhattacharyya, Sanjeev Singh
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Computing changes in regular square grids: towards integration of pixel and edge level analyses Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-05 Mihai-Sorin Stupariu
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Deep learning-based 1-D magnetotelluric inversion: performance comparison of architectures Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-03 Mehdi Rahmani Jevinani, Banafsheh Habibian Dehkordi, Ian J. Ferguson, Mohammad Hossein Rohban
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Exploitation of the ensemble-based machine learning strategies to elevate the precision of CORDEX regional simulations in precipitation projection Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-03 Alireza Ghaemi, Seyed Arman Hashemi Monfared, Abdolhamid Bahrpeyma, Peyman Mahmoudi, Mohammad Zounemat-Kermani
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Positioning and detection of rigid pavement cracks using GNSS data and image processing Earth Sci. Inform. (IF 2.8) Pub Date : 2024-02-02 Ahmed A. Nasrallah, Mohamed A. Abdelfatah, Mohamed I. E. Attia, Gamal S. El-Fiky
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Multi-objective optimal allocation of water resources based on improved marine predator algorithm and entropy weighting method Earth Sci. Inform. (IF 2.8) Pub Date : 2024-01-31 Zhaocai Wang, Haifeng Zhao, Xiaoguang Bao, Tunhua Wu
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Quantitative study on color characteristics of urban park landscapes based on K-means clustering and SD. method Earth Sci. Inform. (IF 2.8) Pub Date : 2024-01-27 Jingyang Feng, Kai Zhang, Zhihong Xu, Chenfan Du, Xiaohong Tang, Lingqing Zhang
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Thermodynamic state shift observed prior to the 2011 Mw 9 East Japan earthquake through data mining using cellular automaton Earth Sci. Inform. (IF 2.8) Pub Date : 2024-01-26
Abstract In this study, we employed our previously developed data mining method to show that a thermodynamic state shift occurred preceding the 2011 Mw 9 East Japan Earthquake (GEJE), coinciding with the onset of crustal stress manifestations. Our discussion starts with the insights obtained from our prior research, which revealed that small ground vibration fluctuations (GVF) detected near the epicenter