Earthquake-prone Regions Research Articles

Performance Evaluation of a Community-Engaged Low-Cost Earthquake Early Warning System for Aotearoa New Zealand

Abstract Can an effective earthquake early warning (EEW) system be implemented at a low cost in earthquake-prone regions? This study addresses this question by evaluating the feasibility of a low-cost, community-engaged EEW system in the Greater Wellington region of New Zealand. The system utilizes decentralized processing to run two algorithms: (1) NZ-PLUM, an adaptation of the propagation of local undamped motion approach tailored to New Zealand’s seismic context, and (2) NZ-PLUM-P, an enhanced version that incorporates P-wave detection for faster alerts. NZ-PLUM triggers alerts based on horizontal acceleration thresholds that are more sensitive to S waves, whereas NZ-PLUM-P offers a longer warning window by detecting the initial P waves. The system’s effectiveness is evaluated through an analysis of ambient noise in the community-hosted network, where 24 out of 27 stations exhibit low-to-medium noise levels. A false alert analysis confirms zero false alerts with both algorithms at an alerting threshold of Modified Mercalli intensity 5.0. The performance is further assessed using data from three recent local earthquakes: an M 3.9 event on 23 May, an M 4.1 event on 3 June, and an M 4.0 event on 6 July 2024. The results show that NZ-PLUM-P significantly improves warning times compared to NZ-PLUM, with average gains of 2.6, 1.25, and 6.4 s across five target points. These findings demonstrate the feasibility of implementing a low-cost, community-driven network capable of delivering effective EEWs. This approach presents a promising, cost-effective alternative for developing or enhancing EEW systems in earthquake-prone regions. Future research should focus on expanding the algorithms across the entire network, incorporating site amplification factors to refine intensity predictions, and increasing community engagement to further reduce noise and enhance system reliability.

Seismic Analysis of Multistorey RC Building by Using Staad.Pro V8i

Abstract - The rapid increase in urban population has led to the vertical expansion of cities, resulting in the construction of high-rise buildings. As the height of buildings increases, their vulnerability to seismic forces also increases. In earthquake-prone regions, the structural stability of multistorey reinforced concrete (RC) buildings becomes a critical aspect of design. Seismic analysis, therefore, plays a pivotal role in ensuring that structures can withstand dynamic loads caused by earthquakes. This study focuses on the seismic analysis of a G+14 storey RC framed building using STAAD Pro V8i, a widely used software tool for structural analysis and design in the field of civil engineering. The primary objective of this research is to analyze and understand the seismic behavior of a 15-storey (G+14) RC building, taking into consideration the dynamic effects of earthquake loading. The structure is assumed to be located in Seismic Zone IV (moderately to highly earthquake-prone), and the analysis is performed according to the seismic design provisions of the Indian Standard IS 1893 (Part 1): 2016 and IS 456:2000 for RC design. The modeling includes dead load, live load, and seismic load cases, with combinations formulated as per IS 875 (Part 1 & 2) and IS 1893 standards. The Response Spectrum Method is employed for the dynamic analysis as it provides more accurate results for taller buildings compared to the equivalent static method. In this study, the building is modeled as a regular frame structure using M30 grade concrete and Fe500 steel. The seismic zone factor, response reduction factor, importance factor, and soil type are all input into the STAAD Pro V8i software to generate and apply dynamic seismic loads. Key response parameters analyzed include storey displacement, storey drift, base shear, and natural time period. The software enables visualization of deformation shapes, bending moments, and shear forces, which are essential for evaluating the structural performance during an earthquake. This research concludes that STAAD Pro V8i is an effective tool for seismic analysis and offers valuable insights into the behavior of high-rise RC buildings under dynamic loading conditions. The analytical results assist engineers in designing structures that are both safe and compliant with current codes. Moreover, the findings emphasize the need for incorporating seismic considerations from the early stages of design, especially in regions with high earthquake risk. Keywords: Seismic analysis, STAAD Pro V8i, G+14 building, multistorey RC frame, response spectrum method, base shear, storey drift, lateral displacement, IS 1893:2016, earthquake loading, reinforced concrete design, structural dynamics, dynamic analysis, Indian seismic code, high-rise buildings.

Earthquake Resilience in Low-Rise Concrete Buildings: A Study on the Effectiveness of Base Isolators

Earthquakes pose significant challenges worldwide, causing severe structural damage, loss of life, and socioeconomic disruptions. To mitigate seismic effects, base isolators have emerged as an effective design strategy for reducing structural damage by decoupling buildings from ground motion. This study investigates the seismic performance of a low-rise concrete building equipped with base isolators, focusing on the influence of isolator mass, stiffness, and damping ratio on key structural responses, including the base shear, natural period, and inelastic storey drift. A symmetric three-storey building was analysed using linear time-history analysis. The ground motions were scaled according to the Indonesian Seismic Code (SNI 1726:2019) to reflect local seismic hazards. Base isolators were modelled as joint springs, and variations in mass (15, 30, and 45 kN), stiffness (1500, 3000, and 4500 kN/m), and damping ratios (20%, 30%, and 40%) were systematically evaluated. The results reveal that increasing the stiffness of the base isolators significantly increases the base shear and inelastic storey drift, whereas higher damping ratios effectively reduce both parameters. Variations in the isolator mass have a minimal impact on the structural response. Additionally, the natural period of the building remained constant across different damping ratios, highlighting the dominant role of the mass and stiffness in the period determination. These findings emphasise the importance of optimising isolator properties to balance seismic performance and structural safety. This study provides critical insights into the design of base-isolated buildings and offers a valuable reference for enhancing the resilience and safety of structures in earthquake-prone regions.

Comparative review of intelligent structural safety in building seismic risk mitigation utilizing an integrated artificial intelligence controller

Seismic events provide significant hazards to the safety and structural integrity of building structures, requiring efficient mitigation techniques. Conventional approaches to mitigating earthquake risks may lack the capacity for prompt adaptation and response. The integration of artificial intelligence (AI) controllers offers an attractive way to improve building safety in earthquake-prone regions. The fundamental unpredictability and complexity of seismic forces can undermine conventional safety measures, resulting in deficiencies in effectiveness and responses. A solution that can dynamically respond and proactively mitigate hazards must be developed to solve these concerns. This review attempts to analyze the possible impact of AI controllers in substantially mitigating seismic risks for structures. This study investigates the efficacy of intelligence structural security systems in enhancing resilience and reducing damage during seismic events through the analysis of AI-driven techniques, methodology, applications, and performance metrics. A systematic analysis of the literature is performed to identify and evaluate prior research on AI controllers employed to reduce seismic risk in structures. The research highlights the influence of integrated AI controllers on control systems, examining several AI controllers, including machine learning algorithms, neural networks, and evolutionary algorithms concerning structural safety. A case study is carried out on a conventional controller, specifically the sliding mode controller (SMC), fuzzy logic controller (FLC), and radial basis function neural network nonsingular terminal sliding mode controller (RBFNN-NTSMC). The findings reveal that the RBFNN-NTSMC effectively reduces building vibrations by up to 63% compared to an uncontrolled structure, significantly outperforming the FLC and SMC, which achieved reductions of 13% and 12%, respectively. This case study illustrates how AI-driven techniques enhance structural resilience and reduce seismic vulnerability. The integration of AI controllers has the potential to enhance the safety and durability of structures by employing advanced computational methods to limit hazards, facilitate real-time response, and optimize structural performance during earthquakes.

ST-elevation myocardial infarction incidence in a high-risk seismic zone.

ST-elevation myocardial infarction incidence in a high-risk seismic zone.

Improving Seismic Performance of RC Structures with Innovative TnT BRBs: A Shake Table and Finite Element Investigation

Addressing the critical seismic vulnerabilities of reinforced concrete (RC) beam-column joints remains an imperative research priority in earthquake engineering. This study presents an experimental and analytical investigation into the seismic performance enhancement of non-ductile RC frames using an innovative all-steel Tube-in-Tube Buckling-Restrained Brace (TnT BRB) system. Shake table tests were performed on one-third scale RC frame specimens, including a baseline structure representing conventional substandard design and a counterpart retrofitted with the proposed TnT BRBs. Experimental results revealed that the unretrofitted specimen experienced pronounced brittle shear failures, excessive lateral deformations, and significant degradation of beam-column joints under cyclic seismic loading. In contrast, the TnT BRB-retrofitted specimen exhibited substantially improved seismic behavior, characterized by enhanced energy dissipation, controlled inter-story drifts, and preserved joint integrity. Advanced fiber-based finite element modeling complemented the experimental efforts, accurately capturing critical nonlinear phenomena such as hysteretic energy dissipation, stiffness degradation, and localized damage evolution within the structural components. Despite inherent modeling limitations regarding bond-slip effects and micro-level cracking, strong correlation between numerical and experimental results affirmed the efficacy of the TnT BRB retrofit solution. This integrated experimental-analytical approach offers a robust, cost-effective pathway for upgrading seismically deficient RC structures in earthquake-prone regions.

Evaluation of Retrofit Interventions in Terms of Seismic Resistance

Abstract: Historical buildings are being abandoned in many parts of the world in order to meet modern requirements, and these neglected structures negatively affect the urban texture, economy, and social structure of urban area. There is a growing trend towards repurposing historical buildings, which play a crucial role in transferring cultural heritage to future generations. These interventions sometimes involve minor enhancements such as strengthening the structure. However, they sometimes include extensive measures such as adding modern equipment or changing the function of the building. These different scaled interventions influence the building's resistance and can sometimes reduce the earthquake resistance of the building in earthquake prone regions. However, the standards which are used to determine the earthquake resistance of buildings are often based on modern construction techniques. Therefore, it is usually difficult to evaluate the earthquake resistance of historical buildings constructed by using traditional methods. These interventions sometimes negatively affect the historical character of the building as well. In order to preserve the historical and urban texture of cities it is crucial to prevent excessive interventions and to carry out these interventions in a controlled manner. This study evaluates the preservation and improvement interventions which are carried out in earthquake-prone regions. Key words: historical buildings, traditional construction techniques, heritage protection, intervention, seismic resistance

Seismic Behavior Analysis of RC Structures with Variable Shear Wall Orientations and Filler Slabs: A Comparative Study of Structural Classes

Reinforced concrete (RC) structures, popular designs in construction, boast strength and durability. Consideration of their seismic performance becomes critical in earthquake-prone regions. This article discusses the seismic behavior of these structures, with a focus on shear wall configurations and filler slabs. The intention is to deeply understand their roles, benefits, and possible improvements that enhance seismic resilience. Shear walls provide significant increases in stiffness through lifter strength and produce lower levels of lateral displacements. In this regard, they dissipate the seismic energy through inelastic deformations. Filler slabs reduce the weight of the overall structures, thus less seismic forces acting on them, and induce an improved energy dissipation. Several advances have occurred in relating advanced materials like ultra-high-performance concrete (UHPC) and fiber-reinforced polymers (FRPs) in increasing performance through improvements in the design of these elements. Some of these improved quality controls and reduction of several construction cycles are prefabricated modular construction. The most important aspects of evidence are that the two factors, shear walls, and filler slabs, work best for optimum performance against earthquakes. Research findings provide further direction into newer avenues for research, including smart materials and sensor technologies; performance-based design adoption; and sustainability in seismic design. These improvements are paramount in creating safe and resilient RC structures against damage due to seismic events.

A Review: Economic Evaluation of Seismic Retrofitting

Seismic retrofitting is a critical strategy for enhancing the resilience and safety of structures, particularly in earthquake-prone regions. Various retrofitting techniques, including fiber-reinforced polymer (FRP) applications, energy dissipation devices, shear walls, and steel bracing, have been explored for their effectiveness in improving structural performance. This study reviews the existing literature on seismic retrofitting, highlighting the role of financial incentives, market strategies, and regulatory frameworks in promoting retrofitting practices. The effectiveness of FRP materials in retrofitting reinforced concrete (RC) and masonry structures is particularly emphasized due to their ease of application, costeffectiveness, and superior strength-to-weight ratio. Standardized evaluation methods and seismic resistance guidelines remain crucial for ensuring reliable and efficient retrofitting practices. While retrofitting offers a viable alternative to demolition and reconstruction, further research is needed to refine cost-effective solutions and develop comprehensive seismic evaluation frameworks. The increasing adoption of innovative retrofitting technologies suggests a promising future for enhancing seismic resilience in modern construction practices.

EFFECTIVENESS OF MACHINE LEARNING METHODS IN DETERMINING EARTHQUAKE PROBABLE AREAS: EXAMPLE OF KAZAKHSTAN

This study investigates the effectiveness of machine learning methods in identifying earthquake-prone areas in Kazakhstan and its neighboring regions. By leveraging a comprehensive dataset encompassing significant earthquake data from 1900 to 2023, various machine learning algorithms were employed, including RandomForest, GradientBoosting, Logistic Regression, Support Vector Classification (SVC), K-Nearest Neighbors (KNeighbors), Decision Tree, XGBoost, LightGBM, AdaBoost, and MLPClassifier. The primary objective was to analyze and compare the performance of these models in predicting earthquake magnitudes and frequencies. The results reveal that certain algorithms significantly outperformed others in terms of accuracy, underscoring the potential of machine learning techniques to enhance earthquake prediction capabilities. Notably, XGBoost and RandomForest demonstrated the highest predictive accuracy, suggesting their suitability for application in seismic risk assessment. These findings offer valuable insights for governmental agencies engaged in disaster management and prevention planning, highlighting the practical implications of integrating advanced analytical techniques in their strategies. In addition to model performance analysis, a visual heatmap was generated to illustrate the geographical distribution of earthquake occurrences across the studied regions. This visual representation effectively identifies high-risk areas, serving as a crucial tool for local authorities and researchers in making informed decisions regarding safety measures and emergency preparedness. This research contributes to the expanding body of knowledge on earthquake prediction utilizing machine learning, emphasizing the necessity for continuous improvement in predictive models by incorporating additional environmental and geological factors. The implications of these findings extend beyond academic discourse, holding significant potential for enhancing public safety in regions vulnerable to seismic activity. As such, this study advocates for the integration of machine learning methodologies in disaster management frameworks to mitigate risks and enhance preparedness in earthquake-prone regions.

Soil improvement in Qom City under the influence of montmorillonite nanoclay

Improving problematic soils using economical and appropriate methods is a major focus in geotechnical research. Recently, nanoparticles such as nanoclay have gained attention as a cost-effective and eco-friendly solution for enhancing soil quality. Nanoclay’s high specific surface area and ion exchange capacity make it economically viable, while its environmental friendliness comes from its derivation from bentonite minerals. This case study aims to improve a local sandy soil with low shear strength in an earthquake-prone region south of Qom City, Iran. The study uses nanoclay stabilization and compares its effectiveness on improving the local soil under both static and dynamic loading conditions, providing a novel approach. Thus, a series of direct shear and simple shear tests were performed to accomplish this specified task. After adding nanoclay to the soil, the sandy soil pores were filled with a cohesive mixture, increasing its agglomeration, which ultimately led to the following results. The results showed that incorporating nanoclay significantly increased the cohesion (c) value by an average of 12 times and raised the internal friction angle (Φ) by 15% compared to the untreated soil. Furthermore, the shear modulus (G) increased 1.4 times on average, while the damping ratio (D) decreased by 25% relative to the original soil. Overall, the use of montmorillonite nanoclay proved to be highly effective in enhancing the strength of non-cohesive sandy soils, especially under static loading. Additionally, the method of stabilizing soil with nanoclay was found to be economical for improving its strength in both static and dynamic conditions.

Forecasting Earthquake-induced Ground Movement under Seismic Activity Using Response Surface

This study employs Response Surface Methodology (RSM) to model and optimize earthquake-induced ground movements in gravelly geohazard-prone environments. RSM efficiently evaluates the interactions of seismic parameters, including soil type, fault distance, and peak ground acceleration (PGA), reducing computational and experimental efforts. A dataset of 234 entries encompassing 11 seismic and soil stress variables was curated and analyzed, yielding a high-precision predictive model with an R² of 0.9997. The resulting closed-form equation facilitates accurate risk assessment, structural safety optimization, and seismic resilience planning. By identifying critical thresholds and nonlinear relationships, RSM supports cost-effective mitigation strategies, infrastructure design, and retrofitting in earthquake-prone regions.

Redesigning Residential Building For Improved Seismic Performance

The seismic performance of existing buildings is crucial for ensuring structural safetyin earthquake-prone regions. This study focuses on the seismic redesign of an existing buildinglocated in Pudukad, Thrissur district, Kerala. The structural elements, including columns, beams,and foundations, were analysed using ANSYS software to evaluate their response to seismic forces.Based on the analysis, necessary modifications were incorporated to enhance the seismic resistanceof the structure. The redesigned model was then subjected to further analysis to assess theimprovements in performance. The study also provides recommendations for implementingseismic-resistant features to improve the overall resilience of buildings in similar seismic-proneareas. The findings contribute to the development of safer construction practices and retrofittingstrategies for existing structures, ensuring improved earthquake resistance and structuralintegrity.

The Role of Disaster Preparedness Training in Shaping Students’ Attitudes Toward Earthquake Response

Disaster preparedness is a critical component of effective disaster risk reduction, particularly in earthquake-prone regions where timely response can save lives and mitigate damage. Schools, being central institutions in shaping societal knowledge and behavior, play a crucial role in imparting disaster preparedness training to students. As young learners constitute a vulnerable group during seismic events, equipping them with the necessary knowledge, skills, and attitudes to respond effectively to earthquakes is paramount. The study aimed at “The Role of Disaster Preparedness Training in Shaping Students’ Attitudes Toward Earthquake Response”. The objectives of the study were, 1) to investigate the current status of disaster management training during earthquake at school level. 2) To measure the attitude of students towards the need of disaster management training during earthquake at school level. The population for this research comprised employees working in higher secondary schools in the Rawalpindi/Islamabad area who are involved in disaster management, including both trained and untrained personnel, for the academic year 2023–2025. In the study, the sample size was expanded to increase the robustness and generalizability of the findings. The total population remained the same, comprising 1,480 students and 300 teachers. The sample included 148 students and 30 teachers, with a total sample size of 178 participants. Similar to the pilot study, the final study also achieved a 100% response rate. The findings indicate that most students do not feel adequately prepared for earthquakes, as 78% do not understand what to do, 92% believe drills are not conducted frequently enough, and 63% are unaware of safe zones. However, 100% trust their teachers' preparedness, 90% find drill instructions clear, and 70% acknowledge parental awareness of school safety plans. Hence, it is recommended that earthquake preparedness training should be intensified through more frequent drills and hands-on simulation exercises. Schools should integrate structured awareness programs that emphasize safe zone identification and emergency response measures. Additionally, parental involvement should be enhanced through regular communication and participation in school safety initiatives.

Post-Earthquake Fire Resistance in Structures: A Review of Current Research and Future Directions

Post-earthquake fires (PEFs) pose a significant secondary hazard in earthquake-prone regions, compounding the destruction caused by seismic events and threatening structural safety. This review explores the interplay between seismic damage and fire resistance, focusing on ignition sources such as damaged utility systems and overturned appliances, and their cascading effects on structural integrity. Advanced performance-based design approaches are evaluated, emphasizing the integration of probabilistic risk assessments, sequential analysis, and hybrid fire simulations to address multi-hazard scenarios. Key findings of current studies reveal that seismic damage, including spalling, cracking, and loss of fireproofing, substantially reduces the fire resistance of materials like steel and reinforced concrete, exacerbating structural vulnerabilities. Despite advancements, critical gaps persist in experimental data, probabilistic modeling, and comprehensive performance-based design guidelines for PEF scenarios. Addressing these deficiencies requires enhanced data collection, improved modeling techniques, and the integration of PEF considerations into building codes. This study provides a comprehensive review of PEF damage assessment and underscores the need for a holistic, multi-hazard design paradigm to enhance structural resilience and ensure safety in regions subject to seismic and fire risks. These insights provide a foundation for future research and practical applications aimed at mitigating the compounded effects of earthquakes and fires.

Nonlinear Static Analysis-an Advanced Analytical Approach to Mitigate Seismic Risks of Overhead Circular Water Tank

Overhead water tanks are vital components of water distribution systems, subject to varying loads and environmental conditions that can impact their structural integrity. Traditional linear static analysis methods often provide limited insights into the true behavior of these tanks under extreme loading scenarios. Nonlinear static pushover analysis offers a comprehensive approach to the assessment of the structural response of overhead water tanks under large deformations and nonlinear material behavior. This paper delves into a detailed investigation of the application of nonlinear static pushover analysis techniques for evaluating the seismic performance of overhead circular water tanks. Key aspects of the methodology include the development of pushover curves to assess the tank's capacity and ductility, as well as the identification of potential failure mechanisms and critical regions prone to damage. The structural response is evaluated for the 200Cu.m. capacity tank through the force-displacement curve, hinge formation pattern, and period of the tank for variable staging heights of tanks 18m, 14m and 10m. The value of the base shear for the 14m staging height tank is around three times the 10m staging height tank and for the 18m staging tank, it is around eight times. From the pushover curve for 18m, 14m and 10m it can be observed that sufficient ductility is achieved. For all heights of the tank, it can be seen that there is no significant failure of the structural members of the tank. The variation of base shear values in pushover analysis for tanks with staging heights of 18m, 14m, and 10m shows that taller tanks generally experience higher base shears due to increased mass and dynamic effects associated with their height. The period of the tank reduces with a reduction in the height of the tank. From the formation of the hinges pattern, it can be seen that hinges are within immediate occupancy: IO to life safety: LS performance level and life safety to collapse prevention: CP level. The findings emphasize the importance of adopting a nonlinear static analysis advanced analytical approach to mitigate risks associated with seismic events and ensure the structural reliability of overhead water tanks in earthquake-prone regions.

Seismic Performance of a Full-Scale Moment-Frame Housing System Constructed with Recycled Tetra Pak (Thermo-Stiffened Polymeric Aluminum Composite)

To address the growing need for sustainable and resilient building materials, the seismic performance of a full-scale moment-frame housing system constructed entirely from recycled Tetra Pak panels (thermo-stiffened polymeric aluminum or TSPA) was evaluated. The study presents an innovative approach to utilizing waste materials for structural applications, emphasizing the lightweight and modular nature of the system. The methodology included material characterization, finite element modeling (FEM), gravitational loading tests, and biaxial shake table tests. Seismic tests applied ground motions corresponding to 31-, 225-, 475-, and 2500-year return periods. Drift profiles and acceleration responses confirmed the elastic behavior of the system, with no residual deformation or structural damage observed, even under simultaneous peak ground accelerations of 0.37 g (x-direction) and 0.52 g (y-direction). Notably, the structure accelerations were amplified to 1.10 g in the y-direction (at the top of the structure), exceeding the design spectrum acceleration of 0.7 g without compromising stiffness or resistance. These results underscore the robust seismic performance of the system. The finite element model of the housing module was validated with the experimental results which predicted the structural response, including natural periods, accelerations, and drift profiles (up to 89% accuracy). The novelty of this research is that it is one of the first to perform shaking table seismic testing on a full-scale housing module made of recycled materials (Tetra Pak), specifically under biaxial motions, providing a unique evaluation of its performance under multidirectional seismic demands. This research also highlights the potential of recycled Tetra Pak materials for sustainable construction, providing an adaptable solution for earthquake-prone regions. The modular design allows for rapid assembly and disassembly, supporting scalability and the circular economy principle.

Seismic upgrading of RC frames using new hybrid dampers with recentering capability applying the second-generation of eurocode 8

This paper investigates the seismic upgrading of existing RC frames whose design was governed by the gravity loads in earthquake-prone regions, using new hybrid energy dissipation devices with recentering capability and applying the analytical methods of the second-generation of Eurocode 8. The energy dissipation devices combine in parallel three components (viscoelastic, elastoplastic and superelastic) that control the response under frequent (viscoelastic) and severe (elastoplastic) earthquakes, and minimize the permanent deformations (superelastic). Frames representative of residential buildings having short, medium and long fundamental periods are considered. Beams, columns and joints with brittle shear failure or insufficient ductility are first upgraded, applying local measures to attain a lateral deformation capacity of 2% of story height that ensures cost-effective strengthening with the hybrid energy dissipation devices. It is shown that the RC frames seismically upgraded with the proposed approach can endure the maximum earthquake foreseen in a high seismicity region with moderate (economically feasible to repair) damage and negligible permanent deformations. It is also shown that the energy-balance-based analysis implemented in the second-generation of Eurocode 8 for displacement-dependent dampers, with elastoplastic restoring force characteristics, can be applied with some limitations to design and verify structures featuring energy dissipation devices that include a superelastic component.

Earthquake epicenter prediction from the Java-Bali radon gas telemonitoring station using machine learning

Predicting the location of earthquake epicenters is a critical aspect of earthquake forecasting, as it complements efforts to determine the time and magnitude of seismic events. This research addresses the challenge posed by the uncertainty in epicenter locations, particularly along the extensive plate faults of Indo-Australia and Eurasia. In these regions, effective earthquake prediction is compromised without accurate epicenter information, impeding mitigation strategies and complicating disaster impact estimation. The primary objective of this study is to devise an algorithm for forecasting earthquake epicenter locations by harnessing variations in radon gas concentrations on southern Java Island, Indonesia, as a predictive precursor. Using a supervised machine learning approach, this study integrates radon gas concentration data to predict the distance between a radon gas telemonitoring station and the impending earthquake epicenter. Three distinct machine learning algorithms were evaluated using data from six Java-Bali radon gas telemonitoring stations within an early warning system. The random forest algorithm emerged as the most effective, yielding an average root mean square error of 453.10 kilometers. The findings of this research significantly contribute to earthquake risk mitigation efforts. This work enhances our capability to anticipate seismic events, and more effective disaster preparedness and response strategies in earthquake-prone regions.

Adjacent-NET: Deep learning classification of adjacent buildings for assessing pounding effects using building facade images in earthquake-prone regions

Adjacent-NET: Deep learning classification of adjacent buildings for assessing pounding effects using building facade images in earthquake-prone regions