To improve the accuracy of deformation prediction in concrete buildings and large-scale infrastructures such as dams, this study proposes an Attention-BiLSTM model integrated with a parameter-optimized Variational Mode Decomposition (VMD). Specifically, the Pelican Optimization Algorithm (POA) is employed to optimize VMD parameters, enhancing signal decomposition efficiency for structural deformation time series. The optimized VMD is then coupled with a BiLSTM network embedded with an attention mechanism, forming a hybrid prediction framework that captures both temporal dependencies and key feature weights in monitoring data. Using three sets of engineering-measured deformation datasets, the proposed model is validated through comparative analyses with conventional single models (e.g., standalone BiLSTM and VMD-BiLSTM without attention). Results demonstrate that the developed model achieves superior accuracy and stability, significantly outperforming all comparative methods, with the highest R² reaching 0.996, while reducing MAE and RMSE by over 60% and 30%, respectively. Quantitative evaluation indicators (e.g., RMSE, MAE, and R²) confirm that the approach effectively captures both short-term fluctuations and long-term trends of structural deformation. These findings verify its reliability and applicability for intelligent safety monitoring of concrete buildings and infrastructures.

Extreme conditions are associated with water security as one of the vital issues that cannot be deduced, where natural disasters and extreme weather disturb the whole supply of water. Reservoir-based water sources have a crucial role to make the water supply resilient; nevertheless, they belong to the group of water sources that tend to encounter interruptions when triggered by typhoons and earthquakes. The foundations of these structures rest on strong policy frameworks and efficient management, which alleviate the damage from weather related phenomena. This research presents a comprehensive investigation into the endurance and weaknesses of reservoir-based water sources and aptly highlights the pertinence of those strategies to adaptively protect the supply of water under rapidly changing conditions. When investigating the water management policies of the People's Republic of China and Japan, it can be noted that they both possess valuable lessons about overcoming the difficulties stemming from natural catastrophes and harsh weather. The Chinese policy set not only reflects the growing trend of comprehensively managing water resources but is also faced with obstacles in implementation due to mismatches of regional conditions and incessant industrialization. Japan, as a country traditionally exposed to the earthquake and typhoons, has developed valuable methods for increasing the resilience of water systems, relying on a long history of disaster management and technological innovation. The study aims to synthesize the strategies brought by the approaches and put forward those measures and areas for cross-learning so that the vulnerability of water sources could be decreased, and resilience could be enhanced. The comparison does not only contribute to evaluating the water security policies of the states but also to the formulation of recommendations for the tougher environmental and human factors.