Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
Browse
2 results
Search Results
Article A Machine-Learning-Based Multi-Hazard GIS-AHP Framework for Wind Turbine Siting under Earthquake–Landslide Coupling(IOP Publishing Ltd, 2026) Dinçer, Ali Ersin; Demir, Abdullah; Öztürk, Şevki; Kalpakcı, Volkan; Dilmen, ÖmerThis study presents a machine-learning-based multi-hazard geographical information system (GIS)-analytical hierarchy process (AHP) framework for wind turbine siting that explicitly accounts for the coupled effects of earthquake and landslide hazards. The primary innovation lies in the development of a conditional weighting algorithm that integrates machine-learning-derived hazard assessments with structural engineering logic. Landslide susceptibility is first modeled using a random forest classifier trained on a comprehensive inventory of historical landslide data and 12 geo-environmental conditioning factors, producing a high-resolution susceptibility map with excellent predictive performance (AUC = 0.86). Feature importance analysis indicates that slope, hydrological indices, and geological conditions are the dominant controls on landslide occurrence. This data-driven map is then integrated with earthquake hazard zones and additional environmental and technical constraints within a GIS-AHP framework to generate a comprehensive wind turbine suitability assessment. Results show that explicitly accounting for earthquake-landslide coupling leads to a nearly 20% reduction in high and very high suitability areas, accompanied by an expansion of low and moderate suitability zones, highlighting the limitations of single-hazard planning approaches. The main contribution of this study lies in advancing renewable energy planning through the explicit integration of interdependent natural hazards, demonstrating how earthquake-resistant foundation strategies can simultaneously mitigate landslide risks.Article Citation - WoS: 1Citation - Scopus: 1A Sustainable Decision-Making Framework to Evaluate Land and Seaside Disposal Options for Tunnel Spoil: A Case Study of Trabzon(Science Press, 2025-05) Dincer, Ali Ersin; Demir, Abdullah; Ozturk, Sevki; Yilmaz, KutaySustainable urbanization is essential for developing cities. To ensure the success of planned construction projects, designers must prioritize sustainability by lowering emissions and reducing costs. Tunnel projects are common worldwide, but disposing of the excavated material presents a significant challenge due to unsuitable geographic conditions. While coastal cities with mountainous terrains have historically used spoil for sea filling, this study offers alternative landside options to promote sustainability. By using a conventional analytical hierarchy process (AHP) method for multi-criteria decision-making (MCDM), the study evaluates land use, sustainability, slope, and drainage lines as constraints for the AHP method. The transportation-related greenhouse gas (GHG) emissions are also considered to reduce environmental damage. Particle swarm optimization is used to determine the minimum transportation distance from the excavation zone to the dumpsite. As a sub-criteria of land use, the seaside is also considered a dumpsite compared with other options on the land side. The spatial analysis results of the case study show that suitable landside sites are available for the Trabzon tunneling project. Although coastal areas in Trabzon have been used for spoil dumping for filling purposes in the past, landside deposition is a viable alternative. The suitability ranks of land and coastal filling options are relatively similar, and selecting the seaside as the dumpsite for the Trabzon tunneling project reduces CO2 emissions. By adopting sustainable practices, we can realize a better future for our cities and the environment.