random forests

The construction industry significantly contributes to global carbon emissions, necessitating urgent mitigation measures.  This study addresses the challenge of predicting carbon emissions during construction projects using advanced artificial intelligence (AI) techniques.  The performance of two AI models, Random Forests (RF) and Support Vector Machines (SVM), is compared to determine their effectiveness in forecasting emissions based on construction materials, techniques and project scale.  Predictive models were developed using a dataset derived from previous research and real-world cons

Growing crops in modern conditions is a complex task and practically combines the practices of experience and the latest methods, including information technology, which has become part of the concept of "smart farming". An important factor in the stable predicted yield is the level of soil moisture, which is the result of changes in climatic factors such as air temperature, soil temperature, intensity of solar radiation, rainfall, wind speed, etc.