Wave Parameters Research Articles

Short-Term Prediction Model of Wave Energy Converter Generation Power Based on CNN-BiLSTM-DELA Integration

Wave energy is a promising source of sustainable clean energy, yet its inherent intermittency and irregularity pose challenges for stable grid integration. Accurate forecasting of wave energy power is crucial for reliable grid management. This paper introduces a novel approach that utilizes a Bidirectional Gated Recurrent Unit (BiGRU) network to fit the power matrix, effectively modeling the relationship between wave characteristics and energy output. Leveraging this fitted power matrix, the wave energy converter (WEC) output power is predicted using a model that incorporates a Convolutional Neural Network (CNN), a Bidirectional Long Short-Term Memory (BiLSTM) network, and deformable efficient local attention (DELA), thereby improving the accuracy and robustness of wave energy power prediction. The proposed method employs BiGRU to transform wave parameters into power outputs for various devices, which are subsequently processed by the CNN-BiLSTM-DELA model to forecast future generation. The results indicate that the CNN-BiLSTM-DELA model outperforms BiLSTM, CNN, BP, LSTM, CNN-BiLSTM, and GRU models, achieving the lowest mean squared error (0.0396 W) and mean absolute percentage error (3.7361%), alongside the highest R2 (98.69%), underscoring its exceptional forecasting accuracy. By enhancing power forecasting, the method facilitates effective power generation dispatch, thereby mitigating the adverse effects of randomness on the power grid.

Using Machine Learning Techniques to Predict Significant Wave Height Compared with Parametric Methods

Prediction of Sea Wave parameters is an important issue as it is the main design factor for maritime structures. Previously, researchers have used many parametric and numerical approaches, which may be complex in application, take a long time in preparation and sometimes require a bathymetric survey. Recently, soft computing techniques such as Fuzzy Inference Systems, Genetic Algorithm, Machine Learning, etc. have been used to predict sea wave parameters in many marine areas around the world. The ease of application, high accuracy and low computational time of these techniques make them a very good choice in many engineering applications. This study focuses on prediction of significant wave height (Hs) by applying one of the most advanced Machine Learning techniques known as Support Vector Machine (SVM). SVM models are built on the basis of different Kernel functions (Linear, Sigmoid, Radial Basis Function, and Polynomial) which transform the input data into an n-dimensional space where a hyperplane can be generated to partition the data. The results of SVM models are analyzed, evaluated and then compared with the results of commonly used parametric models (P-M, SPM, and CEM). This study shows that the P-M model has reliable and satisfactory results among all parametric models, as its statistical errors are close to those of SVM models (RBF and Polynomial), while all of them are identical in their correlation factors (0.999). Moreover, the parametric models (SPM and CEM) are more accurate in their results than the SVM models (Linear and Sigmoid). Also, this study confirms that the SVM models (RBF and polynomial) are the most accurate models overall, as they have the best generalization error among all models. Finally, it can be concluded that SVM models (RBF and Polynomial) are a promising technique in the sea wave height prediction and can be used as an economic and accurate alternative solution to other prediction models.

Two-component nonlinear waves

The generalized equation for the study of two-component nonlinear waves in different fields of physics is considered. In special cases, this equation is reduced to a set of the various well-known equations describing nonlinear solitary waves in the different areas of physics. Using the generalized perturbation reduction method the explicit analytical expressions for the shape and parameters of two-component nonlinear wave is presented. This nonlinear wave solution coincides with the vector 0π pulse of the self-induced transparency.

Progresses on Some Open Problems Related to Infinitely Many Symmetries

The quest to reveal the physical essence of the infinitely many symmetries and/or conservation laws that are intrinsic to integrable systems has historically posed a significant challenge at the confluence of physics and mathematics. This scholarly investigation delves into five open problems related to these boundless symmetries within integrable systems by scrutinizing their multi-wave solutions, employing a fresh analytical methodology. For a specified integrable system, there exist various categories of n-wave solutions, such as the n-soliton solutions, multiple breathers, complexitons, and the n-periodic wave solutions (the algebro-geometric solutions with genus n), wherein n denotes an arbitrary integer that can potentially approach infinity. Each subwave comprising the n-wave solution may possess free parameters, including center parameters ci, width parameters (wave number) ki, and periodic parameters (the Riemann parameters) mi. It is evident that these solutions are translation invariant with respect to all these free parameters. We postulate that the entirety of the recognized infinitely many symmetries merely constitute linear combinations of these finite wave parameter translation symmetries. This conjecture appears to hold true for all integrable systems with n-wave solutions. The conjecture intimates that the currently known infinitely many symmetries is not exhaustive, and an indeterminate number of symmetries remain to be discovered. This conjecture further indicates that by imposing an infinite array of symmetry constraints, it becomes feasible to derive exact multi-wave solutions. By considering the renowned Korteweg–de Vries (KdV) equation and the Burgers equation as simple examples, the conjecture is substantiated for the n-soliton solutions. It is unequivocal that any linear combination of the wave parameter translation symmetries retains its status as a symmetry associated with the particular solution. This observation suggests that by introducing a ren-variable and a ren-symmetric derivative, which serve as generalizations of the Grassmann variable and the super derivative, it may be feasible to unify classical integrable systems, supersymmetric integrable systems, and ren-symmetric integrable systems within a cohesive hierarchical framework. Notably, a ren-symmetric integrable Burgers hierarchy is explicitly derived. Both the supersymmetric and the classical integrable hierarchies are encompassed within the ren-symmetric integrable hierarchy. The results of this paper will make further progresses in nonlinear science: to find more infinitely many symmetries, to establish novel methods to solve nonlinear systems via symmetries, to find more novel exact solutions and new physics, and to open novel integrable theories such as the ren-symmetric integrable systems and the possible relations to fractional integrable systems.

Sustainable solution to the critical challenges of an oceanic wave farm for maximizing power generation

In this paper, a general wave farm design procedure has been presented. For example, the design procedure is applied to the Bay of Bengal, Bangladesh. Firstly, the most effective site is selected to construct a wave farm considering various techno-economic factors. A coordinated drawing for the proposed site selection procedure is presented, which includes a coastal area map and sea, grid map, wave height, and different assorted factors. Transmission line cost is analyzed for nearly equipotential locations. Then wave height, time period, wave power, and vertical speed are observed for the selected location. In the next step, a wave farm layout has been designed considering point absorber type device and the oceanic wave dataset with statistical analysis. Further, a linear electrical generator (LEG) is designed and analyzed for the wave farm. The generator is simulated in the ANSYS/Maxwell environment. Since the wave parameters vary from time to time, the LEG is simulated for several vertical speeds. To find the highest output power, the load profiles are analyzed for each speed separately. In the next step, the LEG is optimized. Simulation result shows that the flux distribution of optimized LEG is better than its initially designed counterpart. Efficiency of the optimized LEG is 7 % greater than its initial design. The proposed method of site selection, statistical analysis of the wave dataset, and the optimized LEG design are combined in this paper for maximum wave energy extraction.

Reaction zone structure of spontaneous reaction wave at steady subsonic and supersonic speeds

The reaction zone structure of spontaneous reaction wave at steady subsonic and supersonic speeds is discussed using numerical simulation and theoretical approaches. The main objective of this study is to develop the mathematical model of the spontaneous reaction wave propagating at a steady speed and to clarify the relationship between the reaction zone structure and non-dimensional parameters. A one-dimensional direct numerical simulation (DNS) of the spontaneous reaction wave propagation is performed, and the modeling assumptions are discussed based on the numerical results. The non-dimensional parameters, the Damköhler number and a parameter related to compressibility defined by the Mach number of the spontaneous reaction wave velocity, are introduced into the modeling. The mathematical model is developed using asymptotic techniques, and the solution of the reaction zone structure is analytically derived using Newton’s method. The relationship between reaction zone structure of spontaneous reaction wave and non-dimensional parameters is discussed based on the analytical solutions.

Nonlinear model predictive dynamic positioning of a remotely operated vehicle with wave disturbance preview

Exploiting preview information of disturbances within robot control is an effective method of handling state perturbations. For underwater vehicles operating in wave-dominated environments, disturbances significantly influence vehicle response and pose a threat to operational safety. In consideration of this, a complete end-to-end control architecture is developed in this work for disturbance rejection during station keeping tasks under wave perturbations, encompassing a nonlinear model predictive controller (NMPC) combined with a deterministic sea wave predictor (DSWP). The wave predictor exploits a continuous measurement of the wave elevation at a location upstream of the vehicle to form a forecast of the temporal evolution of the wave elevation at the vehicle location. The predicted wave parameters are then used to estimate the impending wave-induced hydrodynamic loading, enabling explicit consideration of accurate short-term disturbance forecasts within the controller, ensuring this preview is incorporated in the optimised control sequence. Experimental testing confirms the validity of the wave predictor, producing RMSE as low as 0.017 m. The proposed strategy is then simulated under various wave conditions, optimising control actions inclusive of the preview information. The NMPC outperforms a similar disturbance mitigating feed-forward controller, with average improvements of up to 52% and is found to perform best even with noisy, lower accuracy wave predictions, as well as with communication time delays, providing a high degree of robustness. This demonstrates the potential of the proposed control framework to effectively tackle disturbance mitigation of underwater vehicles subject to large magnitude wave disturbances, expanding the operational envelop of autonomous systems towards forbidding ocean environments.

A Modular Smart Ocean Observatory for Development of Sensors, Underwater Communication and Surveillance of Environmental Parameters

The rapid growth of marine industries has emphasized the focus on environmental impacts for all industries, as well as the influence of key environmental parameters on, for instance, offshore wind or aquaculture performance, animal welfare and structural integrity of different constructions. Development of automatized sensors together with efficient communication and information systems will enhance surveillance and monitoring of environmental processes and impact. We have developed a modular Smart Ocean observatory, in this case connected to a large-scale marine aquaculture research facility. The first sensor rigs have been operational since May 2022, transmitting environmental data in near real-time. Key components are Acoustic Doppler Current Profilers (ADCPs) for measuring directional wave and current parameters, and CTDs for redundant measurement of depth, temperature, conductivity and oxygen. Communication is through 4G network or cable. However, a key purpose of the observatory is also to facilitate experiments with acoustic wireless underwater communication, which are ongoing. The aim is to expand the system(s) with demersal independent sensor nodes communicating through an “Internet of Underwater Things (IoUT)”, covering larger areas in the coastal zone, as well as open waters, of benefit to all ocean industries. The observatory also hosts experiments for sensor development, biofouling control and strategies for sensor self-validation and diagnostics. The close interactions between the experiments and the infrastructure development allow a holistic approach towards environmental monitoring across sectors and industries, plus to reduce the carbon footprint of ocean observation. This work is intended to lay a basis for sophisticated use of smart sensors with communication systems in long-term autonomous operation in remote as well as nearshore locations.

Characteristics of measured typhoon waves on the central coast of Zhejiang province

The risk of typhoon disasters is high in the Zhejiang coastal areas; however, it has been difficult to characterize waves generated by these typhoons, particularly in shallow waters. In this study, the characteristics of nearshore typhoon waves were analyzed using data from 14 typhoon processes from a wave station on the central coast of Zhejiang Province for three consecutive years from 2016 to 2018. According to their paths, these typhoons were divided into landing and non-landing steering types. Wave parameters were evaluated using statistical analyses and linear regression. Variations in wave parameters and spectra are discussed. We obtained several key results: (1) The dominant wave direction was E-SE and the strong wave direction was SE. (2) There were strong correlations between characteristic wave heights and between characteristic periods. (3) Single-peak spectra were dominant, with a frequency of 92.33%. The minimum peak frequency was 0.06–0.1 Hz and the maximum peak period was 17.7 s. The typhoon waves were mainly composed of swells with a frequency of 94.54%. (4) Affected by Typhoon Maria (No. 201808), a maximum wave height of 8.20 m was observed at 04:00 on July 11, 2018. This study provides an important reference for the design of offshore structures and disaster prevention and mitigation.

Study of age-related retinal hemodynamic changes by laser speckle flowgraphy

Background: Diagnostics of hemodynamic changes is important both for clarifying the features of the course of pathological process of many ophthalmic diseases and for optimizing treatment tactics. Laser speckle flowgraphy (LSFG) is a new non-invasive method for quantitative assessment of retinal blood flow. Aim: To study age-related changes of pulse waves both in large blood vessels and microvasculature in the optic nerve head and macula by laser speckle flowgraphy. Materials and methods: Age-related changes in blood flow were studied in 60 healthy volunteers using LSFG-RetFlow. We analyzed MBR — main parameter of pulse wave assessed by the laser speckle flowgraphy and also another 8 pulse wave parameters for large vessels and microvasculature in the areas of optic nerve head and macula. Results: The study revealed statistically significant (p ≤ 0.05) age-related changes in pulse waves for most parameters under study. In the large vessels of the optic disc blood flow dropped after 60 years, while in the microvasculature it decreased progradiently in the groups older than 40 and 60 years. In the macular region, blood flow in large vessels and microvasculature decreased mainly in the group aged over 61. Age-related changes in pulse wave parameters were unidirectional for both large vessels and microvasculature; trends were similar in both areas under investigation. Conclusions: The study demonstrated statistically significant (age-related changes in most laser speckle flowgraphy pulse wave parameters. The MBR, MV (MBR of Vascular area), MT (MBR of Tissue area) indicators are most informative in the ophthalmic hemodinamic screening. The study of another pulse wave parameters seems sufficient for the general MBR.

High-frequency vibration analysis of laminated composite plates using energy flow and shear deformation theories

Energy Flow Analysis (EFA) is an efficient approach for characterizing high-frequency vibrations through time-averaged energy density distributions. This study employs EFA to investigate vibroacoustic behavior in laminated composite plates subjected to high-frequency excitation. Governing equations of motion are derived using Classical Plate Theory (CPT), First Order Shear Deformation Theory (FSDT), and Higher Order Shear Deformation Theories (HSDT). Wave propagation parameters like wave number and group velocity are obtained from each theory and compared to assess accuracy. Energy density and intensity formulations are then developed based on classical solutions of the governing equations. EFA analysis indicates that HSDT provides more accurate predictions of wave parameters, especially at very high frequencies where it accounts better for shear deformation effects. Validation against classical energy density solutions shows acceptable accuracy with less than 0.5dB difference in the far-field. Comparisons further demonstrate the superiority of HSDT over FSDT for thicker plates in both classical and EFA analyses. This research establishes the effectiveness of EFA for high-frequency vibration analysis of composite laminates. The main novelty of this research lies in the integration of HSDT into the application of EFA for composite laminates, providing a more precise consideration of shear deformation effects at high frequencies. Specifically, HSDT enhances modeling of critical shear deformation effects at elevated frequencies. EFA delivers computationally efficient solutions while maintaining acceptable accuracy, improving characterization and design of composite structures under high-frequency loading.

Theory for plunger-type wavemakers to generate second-order Stokes waves and Smoothed Particle Hydrodynamics verification

Plunger-type wavemakers are used in ocean engineering laboratories globally. However, the wave-making theories remain incomplete due to the complex geometries of the plungers. This work derives the motion equations for an arbitrary-geometry plunger to generate second-order Stokes waves, along with the generic constraints on wave parameters. Taking wedge-shaped and cylinder-shaped plungers as examples, the motion equations and constraints are detailed. Subsequently, a smoothed particle hydrodynamics (SPH) model for the plunger-induced waves is established and validated by accurately reproducing published experimental results. Finally, the SPH model is applied to simulate the wave generation by the two plungers. The computed wave profiles, water pressures, and flow velocities are compared with their analytical solutions in terms of spatial distribution and time history. Additionally, the wave field stability and the wave generation process are evaluated. The results demonstrate that second-order Stokes waves with target waveforms can be precisely generated using an arbitrary-geometry plunger-type wavemaker within a short transition distance and time, thereby verifying the reliability of the proposed wavemaker theory.

In-situ calibration for real-time infrasound station monitoring and improved wave parameter determination

Infrasound signals can be detected using a time-delay of arrival approach to derive the back azimuth and trace velocity of the coherent wave. For these calculations, it is necessary to have a calibrated measure of the pressure. Although the calibration of microbarometers can be performed in a laboratory setting and in the field with specific metrological means such as those developed by the CEA, it is much more difficult to determine the transfer function of the wind noise reduction systems (WNRS), designed to reduce the wind associated noise. In-situ calibration of these WNRS's can be performed using a co-located, calibrated reference sensor. System defects, such as flooded pipes or blocked inlets, have significant impacts on the response, which in turn would influence the calculated infrasonic wave parameters. These defects can be characterized using in-situ calibration measurements. Experiments were undertaken at the infrasound station IS26 as part of the EMPIR Infra-AUV project, using a temporary detector that was used to simulate defects on the WNRS. This allowed for the effects on real infrasound detections to be quantified and corrected using in-situ calibrations. Additionally, case studies at IMS stations were performed demonstrating the utility of these methods on operational infrasound stations.

Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT

Abstract. In the past, satellite climatologies of gravity waves (GWs) have initiated progress in their representation in global models. However, these could not provide the phase speed and direction distributions needed for a better understanding of the interaction between GWs and the large-scale winds directly. The ESA Earth Explorer 11 candidate CAIRT could provide such observations. CAIRT would use a limb-imaging Michelson interferometer resolving a wide spectral range, allowing temperature and trace gas mixing ratio measurements. With the proposed instrument design, a vertical resolution of 1 km, along-track sampling of 50 km, and across-track sampling of 25 km in a 400 km wide swath will be achieved. In particular, this allows for the observation of three-dimensional (3D), GW-resolving temperature fields throughout the middle atmosphere. In this work, we present the methodology for the GW analysis of CAIRT observations using a limited-volume 3D sinusoidal fit (S3D) wave analysis technique. We assess the capability of CAIRT to provide high-quality GW fields by the generation of synthetic satellite observations from high-resolution model data and comparison of the synthetic observations to the original model fields. For the assessment, wavelength spectra, phase speed spectra, horizontal distributions, and zonal means of GW momentum flux (GWMF) are considered. The atmospheric events we use to exemplify the capabilities of CAIRT are the 2006 sudden stratospheric warming (SSW) event, the quasi-biennial oscillation (QBO) in the tropics, and the mesospheric preconditioning phase of the 2019 SSW event. Our findings indicate that CAIRT would provide highly reliable observations not only of global-scale GW distributions and drag patterns but also of specific wave events and their associated wave parameters. Even under worse-than-expected noise levels of the instrument, the resulting GW measurements are highly consistent with the original model data. Furthermore, we demonstrate that the estimated GW parameters can be used for ray tracing, which physically extends the horizontal coverage of the observations beyond the orbit tracks.

Early wave reflection of carotid artery is associated with 18F-FDG PET hypometabolism in Alzheimer's brain areas of cognitively normal adults.

Arterial stiffening likely plays a role in Alzheimer disease (AD) pathogenesis. The current study investigated whether inter-individual variations in arterial stiffness and pressure wave parameters were associated with 18F-FDG positron emission tomography (PET) metabolism in AD-associated brain areas throughout adulthood, independently of age and before the onset of any neuropsychological disorders. A prospective, large age-range population of 67 patients (17 young, 16 middle-aged, and 34 older adults; 37 women) underwent a: brain 18F-FDG PET, blood pressure recording, and carotid/femoral pulse wave-based measurements, including the time-to-peak of the reflected backward carotid pulse wave (bT), on the same day. Multivariable and quantitative voxel-to-voxel analyses (P-voxel < 0.005, corrected for cluster volumes) were conducted to assess associations between vascular parameters and 18F-FDG PET metabolism in AD-associated brain areas. In the multivariable analysis, only increased age and decreased bT were independently associated with the decline of metabolic activity in AD-associated brain areas (P < 0.001). In the voxel-to-voxel analysis with age as a covariate, bT was strongly associated with the metabolic activity of 40 clusters in AD-associated brain areas (clusters cumulative volume: 63 cm3; T score max: 5.7). In a large age-range population of adult patients, who are still unaffected by neuropsychological disorders, an early reflected arterial pressure wave, as evidenced by a decreased bT value, is strongly associated with hypometabolic activity of AD-associated brain areas, independently of age.

Investigation of hydrodynamic characteristics of an oyster reef under regular waves

Oyster reef living shorelines are popular solutions to mitigate coastal hazards while providing ecosystem services, and their hydrodynamic characteristics deserve further examination. This paper reports an experimental and numerical study of the hydrodynamic behavior of a bagged oyster shell (BOS) reef under regular waves. The dependence of the pore pressure within the reef and the hydrodynamic coefficients on the reef height, length, porosity, and wave parameters are investigated. The results show that the normalized maximum pore pressure ps_m∗ decreases from the seaside of the BOS reef to its leeside and decreases with increasing dimensionless reef length. With increasing wave steepness, ps_m∗ fluctuates with an overall increasing trend. With increasing BOS reef porosity, ps_m∗ decreases at seaside locations and increases at leeside locations; simultaneously, the wave reflection coefficient Kr and the wave dissipation coefficient Kd decrease, and the wave transmission coefficient Kt increases. With increasing wave steepness for a given wave period, Kr and Kt tend to increase, but Kd exhibits the opposite trend. As the dimensionless reef height and length increase, Kt decreases and Kd increases. Multivariate nonlinear regression and genetic programming-based symbolic regression methods are individually used to derive two formulas for predicting the wave transmission coefficient, with the formula from the latter method being found to give a higher prediction accuracy.

A 45-Year Updating Wind and Wave Hindcast Over the Oman Sea and the Arabian Sea

This study focuses on developing a comprehensive and reliable wind and wave hindcast for the Oman Sea and Arabian Sea, spanning a significant 45-year period (1979-2024). The objective is to capture the intricate wind and wave climate of the region, characterized by distinct monsoon cycles and occasional tropical cyclones. The availability of extensive wave data over four decades would be an irreplaceable tool for researchers and engineers, enabling improved accuracy in extreme value analysis, sediment transport studies, and wave-induced current simulations. Despite limited field observations, all available measured data within the region were collected, analyzed for configuration of the models and utilized for model calibration and validation. The hindcast data was generated using the Weather Research and Forecasting (WRF) model for winds and WAVEWATCH III (WW3) model for waves, and evaluated against observational and measured wind and wave parameters. A comprehensive statistical analysis of the hindcast model's performance reveals adequate agreement with measured data, as evidenced by root mean square errors (RMSEs) of 1.23m/s for wind speeds and 0.37m for significant wave heights in average. These results underscore the model's reliability for research and engineering applications, particularly in the Arabian Sea, with a focus on the northern coastlines of the Oman Sea. The specific model configuration employed in this study holds significant potential for future investigations in the northern Indian Ocean, offering a valuable tool for understanding and predicting climatical conditions in this region.

Evaluating the Application of the SIR Model to a Localized Population

Objective Using data collected from the Johns Hopkins COVID-19 Repository, I investigated the reliability of the SIR (Susceptible-Infected-Removed) model. Summary of Background Data Modern pandemic responses have evolved into effective defenses when implemented correctly but present issues in epidemiological modeling efforts. Intervention strategies such as quarantining and masking limit population size (N), which affects the accuracy of modeling population-based rate systems especially in highly transmissible diseases. Methods I begin by reviewing the SIR model retroactively to the initial SARS-CoV-2 Wuhan strain. I compared the parameters available in the published literature (N = 2,717,000, β = 2, γ = 1/14) to the best-fitting SIR-yielded values by minimizing the root mean squared error function. Subsequently, I evaluated its predictive capabilities on the Delta variant using early surge data, which was later compared against a retroactive analysis. Results Using a least-squares error best-fit analysis allowed me to retroactively define remarkably accurate model parameters for the Wuhan waves. Parameters including N = 730, β = 0.46, γ = 0.043 in the first wave and N = 11,200, β = 0.198, γ = 0.07 in the second reflected effective intervention strategies. I show it is an effective predictive tool regarding the Delta variant, yielding parameters N = 50,900, β = 0.87, γ = 1/3.7 that proved accurate when compared with parameters from a full retroactive analysis (N = 60,000, β = 0.94, γ = 1/3.6). Conclusion The similarity of the yielded parameters in my results supports the SIR model’s utility in epidemiological monitoring of high-transmissibility, low-mortality outbreaks vis-à-vis various containment measures.

Effect of the Magnetic Field, Electric Field, and Light Intensity on the Parameters of Recombination Waves in Silicon

Effect of the Magnetic Field, Electric Field, and Light Intensity on the Parameters of Recombination Waves in Silicon

An end-to-end multi-task network for early prediction of the instrumental intensity and magnitude in the north–south seismic belt of China

The seismic activity in the north–south seismic belt of China is among the highest in the world. Predicting instrumental intensity and magnitude after an earthquake mitigates regional seismic disasters. The standard workflow for prediction involves building empirical formulas using characteristic parameters of the initial arrival seismic wave, but this method has limitations in accuracy. Recent data-driven models have shown promise in predicting instrument intensity and magnitude. Still, this is currently done mainly on a single-task basis and does not consider whether a multi-task model can utilize complementary information from different tasks to improve overall performance. This study proposes a data-driven multi-task model called SeismNet, which can simultaneously predict instrument intensity and magnitude. We tested the effectiveness of SeismNet using ground motion records of the north–south seismic belt of China. The model can predict instrument intensity and magnitude more rapidly and accurately than the baseline and single-task models, with increasing accuracy as the input seismic wave duration increases. We also tested the method on three destructive earthquake events (Ms > 6.5) that occurred in China and found that at 3 s after the P-wave arrival, the prediction is almost consistent with the observation. Overall, this study offers a new method for improving earthquake prediction accuracy in the North-South seismic belt of China.