ASRIC Journal of Engineering Sciences 2025 v5-i2
ISSN: 2795-3548
EISSN: 2795-3548
ASRIC Journal of Engineering Sciences 2025 v5-i2
ASRIC Journal of Engineering Sciences 2025 v5-i2
Published: 2025-12-31
Articles
Effective On-Site Supervision- A Yardstick to Minimizing Building Construction Failure In Southwest Nigeria
Adeyemi, F. O*, Olaniyi O. A, Esuruoso, O.T
The building construction industry plays an essential role in the development of any developing nation. Despite various regulations and professional guidelines in the building construction sector, Nigeria continues to experience frequent building failure. This research therefore aims at assessing the effectiveness of on-site supervision as a yardstick to minimizing building construction failure in
Ensemble, Kernel-based, and Deep Learning approaches for flood susceptibility mapping: A case study at Lake-Watersheds
Sintayehu Adefires Abebe*, Mulu Sewinet Kerebih, Bewketu Assefa Mulu, Bekalu Weretaw Asres
Lake Tana and its surrounding regions experience frequent flooding, necessitating improved susceptibility mapping to mitigate risks and enhance resilience. This study applies data-driven machine learning techniques to assess flood susceptibility utilizing data sets commonly used in large-scale river basin studies. A comprehensive flood inventory of approximately 2,080 flooded locations was compile
Urban Flood Susceptibility Study: An AHP-Based Geospatial Multi-Criteria Evaluation in Kigali City, with a Focus on the Mpazi Catchment
Pierre Damien Iraguha, Tresor Hirwa
water floods are the most common and costly natural calamities that affect all countries globally. Flooding in Mpazi catchment (MC) in the city of Kigali (CoK) has raised an issue to sustainable city development. The major aim of this study was to assess flood hazard, vulnerability, and risk in the part of Mpazi catchment (MC) by utilizing GIS-based Multi-Criteria Decision Analysis (MCDA). Mapping
Issues
