Abstract: In recent years, medical diagnostics has increasingly relied on machine learning techniques to improve accuracy and efficiency. Among these, the Random Forest algorithm has emerged as a ...

Accurate classification of wetland vegetation is essential for biodiversity conservation and carbon cycle monitoring. This study developed an adaptive ...

Abstract: The current econometric models have the disadvantages of low prediction accuracy and poor model fitting effect. To solve these problems, this study combines Markov chain Monte Carlo ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...

Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...