Caltech scientists have found a fast and efficient way to add up large numbers of Feynman diagrams, the simple drawings ...

Currently, PET scanner validation phantoms, methods, and acceptance criteria for clinical trials are not standardized. This ...

To address the problems of low classification accuracy, redundancy of feature subsets, and performance susceptibility to parameters in wrapper-based feature selection in traditional Support Vector ...

Li, H. and Au, S. (2010) Design Optimization Using Subset Simulation Algorithm. Structural Safety, 32, 384-392.

An autoregressive integrated moving average (ARIMA) model is a statistical analysis model that leverages time series data to forecast future trends.

To address the problems of low classification accuracy, redundancy of feature subsets, and performance susceptibility to parameters in wrapper-based feature selection in traditional Support Vector ...

Metaheuristic optimization algorithms are strongly present in the literature on discrete optimization. They typically 1) use stochastic operators, making each run unique, and 2) often have algorithmic ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.