Artificial intelligence in construction: Topic-based technology mapping based on patent data

Automation in Construction, Journal Year: 2025, Volume and Issue: 172, P. 106073 - 106073

Published: Feb. 18, 2025

Language: Английский

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Optimal Site Selection for Wind and Solar Parks in Karpathos Island Using a GIS-MCDM Model

ISPRS International Journal of Geo-Information, Journal Year: 2025, Volume and Issue: 14(3), P. 125 - 125

Published: March 10, 2025

This research paper examines how to assess potential locations for wind turbines and photovoltaic modules by combining Geographic Information Systems (GIS) with multi-criteria decision-making (MCDM). These depend on the current legislation, where many areas are buffer zones due limitations. The study area is Karpathos, which faces energy water scarcity. need increase penetration rate of renewable sources (RES) 2030 can help this island fulfill both its needs through RES. To apply weighted linear combination technique, approach considers all eligibility criteria according legislation. After classifying them into four zones, MCDM results in a suitability map that displays spatial distribution final score, ranging from sites not appropriate highly suitable. In module scenario, zone corresponds 61% island, while turbine number increases 85%, highlighting difficulty finding suitable sites. A sensitivity analysis performed determine impact site scenarios.

Language: Английский

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Neural Networks for Analyzing Soil Organic Carbon Storage

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 455 - 480

Published: April 11, 2025

Soil organic carbon (SOC) is an essential element of the global cycle, serving a central role in climate change mitigation, soil fertility, and ecosystem sustainability. Conventional SOC estimation techniques are time-consuming, labor-intensive, geographically confined, thus confining their efficiency for large-scale monitoring. This chapter discusses how artificial neural networks, such as CNNs, RNNs, deep learning models, improve forecasting accuracy scalability. With integration remote sensing, geospatial data, environmental factors, AI-based models facilitate effective processing mapping distribution. Deep machine methodologies enhance predictive power, automate analysis, mitigate uncertainties estimation. Critical methodologies, issues, emerging trends exploiting networks storage discussed, prioritizing sequestration monitoring optimization, sustainable land management, resilience planning.

Language: Английский

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Evaluation of Explainable Ai Models in Analysis of Transferable Features of Geothermal Indicators

Published: Jan. 1, 2024

Language: Английский

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