首页|Islamic Azad University Researcher Has Provided New Data on Machine Learning (Qu antitative forecasting of bed sediment load in river engineering: an investigati on into machine learning methodologies for complex phenomena)

Islamic Azad University Researcher Has Provided New Data on Machine Learning (Qu antitative forecasting of bed sediment load in river engineering: an investigati on into machine learning methodologies for complex phenomena)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting from Islamic Azad University by Ne wsRx journalists, research stated, "The intricate calculation of bed sediment lo ad (BSL), which is influenced by hydraulic, hydrological, and sedimentary factor s, is vital for informed decision-making in water resource management." The news editors obtained a quote from the research from Islamic Azad University : "Machine learning models, which are gaining popularity due to their accessibil ity and ability to reveal complex relationships, play a significant role in tack ling these challenges. The efficacy of gene expression programming (GEP) models, support vector machines (SVMs), multi-layer perceptron (MLP), and multivariate adaptive regression splines (MARS) has been assessed through measured data of nu mber 540 obtained from six rivers, namely Oak Creek, Nahal Yatir, Sagehen Creek, Elbow River, Jacoby River, and Goodwin Creek from 1954 to 1992. The assessment of model performance has been conducted utilizing root mean square error (RMSE), R2, Nash-Sutcliffe coefficient (NSE), and developed discrepancy ratio (DDR) as indices. Following data normalization within the range of 0-1, the data models u nderwent training and testing processes with a partition ratio of 80% for training and 20% for testing."

Islamic Azad UniversityCyborgsEmergi ng TechnologiesEngineeringMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.8)