Resilience Adaptation Approach for Reducing the Negative Impact of Climate Change on Coastal Heritage Sites through Machine Learning

The continuous cumulative worsening impact of climate change on heritage sites represents a new challenge for most the nonrenewable resources and buildings in general; this is especially true with respect to coastal sites, which are facing more dangerous situation as becomes extreme areas sea levels rise, putting at risk. A strict adaptation plan, usually made reducing change, may not be solution, different site locations, materials, hazard types need tailored plans. Therefore, research paper, resilience approach was introduced help adapt problematic impacts i.e., sites. To fulfill objective achieving resilient way that can easily developed relation mixed methods were used. First, literature reviewed using Connected Papers tool. Then, machine learning used process analyze input data plan an Egyptian case study, Alexandria. Next, arranged analyzed, highlighting main classifying algorithms responsible identifying range, software packages Infra Nodus WEKA, according differences final outcome adapted rescue plans via learning.