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Forest fires have exhibited an escalating trend in both frequency and intensity globally, with major and catastrophic events causing significant damage to forest resources, human lives, and property. Timely and accurate ...

Abstract This paper proposes a novel hybrid ensemble machine learning framework integrated with Explainable AI (XAI) to overcome the fundamental trade-off between non-detection zones (NDZ) and false positives in conventi...

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

The global aviation industry plays a critical role in economic development and international connectivity. However, it also contributes significantly to environmental challenges, particularly through fuel consumption and...

Prediction of building occupancy is a very important element of structural health monitoring (SHM), smart building systems, and energy management. In this study, a number of visualization tools are used to analyze the pe...

Using historical data from blasting operations of open-pit mines to predict the average rock fragment size is crucial for optimizing blasting parameters. However, existing methods face 3 major challenges: interference fr...

Abstract Since the mid of 1990th, Mosul city over all Iraq cities, is used widely the local power diesel generators. The generators exhaust emits a large amounts of hydrocarbon gases, including, of course, carbon dioxide...