Peak ground motions and spectral accelerations estimated from the prediction equations are highly significant in earthquake hazard studies. Recently, these predictive relationships developed for higher-order parameters obtained paramount importance as they describe different ground motion characteristics. The northeastern region of India experiences extreme seismicity due to the Indian plate subduction under the South Asian plate. However, only a few ground motion prediction equations (GMPEs) are available for such tectonic environments due to insufficient ground motion data. In this regard, it is noticed that the tectonic environment experienced by New Zealand is similar to that of northeast India. So, in this paper, two GMPE models for New Zealand are developed with the help of the artificial neural network (ANN) technique using the GeoNet database. Model-1 corresponds to various higher-order parameters, whereas model-2 developed for spectral accelerations (S_a) between 0.01 and 5s. Further, these models are compared against global and region-specific GMPEs. The developed models shows good agreement with other GMPEs and the data but slightly over predicts at distances greater than 300 km. Additional consideration of site-to-site variability in the current models reduced the total standard deviations of model-1 by 19–22 % and model-2 by 20%–23 %. Further, the estimates of these developed models are compared with some of the significant earthquakes in northeast India, and from these results, it is concluded that the current models can be adapted in such regions to estimate ground motion.

从预测方程估计的峰值地面运动和频谱加速度在地震灾害研究中非常重要。最近，这些为高阶参数开发的预测关系在描述不同的地面运动特征时变得极为重要。由于南亚板块下的印度板块俯冲，印度东北部地区经历了极端地震活动。然而，由于地震动数据不足，只有少数地震动预测方程 (GMPE) 可用于此类构造环境。在这方面，注意到新西兰经历的构造环境与印度东北部的构造环境相似。所以，在这篇论文中，在人工神经网络 (ANN) 技术的帮助下，使用 GeoNet 数据库开发了新西兰的两个 GMPE 模型。模型 1 对应于各种高阶参数，而模型 2 为谱加速度（S_a ) 在 0.01 到 5s 之间。此外，这些模型与全球和区域特定的 GMPE 进行了比较。开发的模型与其他 GMPE 和数据显示出良好的一致性，但在大于 300 公里的距离上略高于预测。当前模型中对站点间可变性的额外考虑将模型 1 的总标准偏差降低了 19–22%，将模型 2 的总标准偏差降低了 20%–23%。此外，将这些开发模型的估计值与印度东北部的一些重大地震进行了比较，从这些结果可以得出结论，当前模型可以在这些地区适用于估计地震动。