In most situations, the system is required to take decisions based on multiple inputs, but the search space is usually very huge so that it will be very hard to use the traditional algorithms to take a decision; at this point, the metaheuristic algorithms can be used as an alternative tool to find near-optimal solutions.
When using the traditional genetic algorithms, one can encounter problems with the immense effort required in coding ones own finite element code (or for integration with other commercial finite element software) when using the traditional genetic algorithms.
In addition, current research has ignored the use of ensemble learning techniques, such Bagging or Boosting, to obtain better predictive performance than using the traditional learning algorithms.
Xampling uses modulated wideband converter [6] (MWC) to sample, whose results are infinite measurement vectors (IMV), and it cannot directly reconstruct signal using the traditional reconstruction algorithms.
The ANN was trained using the traditional backpropagation algorithm, which is designed to minimise the average error on a training set of generated data.
We next analyzed the differential distribution of the methylation results using the traditional GoMiner algorithm which treats each probe as an independent assessment.
Individual HMMs for the four TFs were trained using the traditional Baum-Welch algorithm.
Then using the PCC as the column 'match' score, the method aligns the two PWMs using the traditional Smith-Waterman algorithm for sequence alignment.
The calibration of models was performed using the nonlinear least squares optimization methods, by programming in Mathematica and by applying the genetic Algorithm, and using the traditional linear least squares method.
For comparison, the modified structures (with various portions deleted) were then superpositioned using the EM algorithm and using the traditional method which omits columns with gaps.
