Thus, compared to uniform grid experiments the number of grid points is reduced significantly.
By solving the experimental design problem, the time to start the experiments, the number of experiments and the experimental operating conditions are determined.
With the full factorial designs commonly used for simulation experiments, the number of runs grows exponentially with the number of factors involved, while the run length remains constant.
In frequency domain experiments, the number of runs is independent of the number of factors, while the required run lengths increase relatively slowly.
In our experiments, the number of dimension in each NN was divided evenly.
To reduce the number of experiments, the number of data was kept at minimum.
Through trials and experiments, the number of neurons in the first and second hidden layers was 15 and 8 respectively.
In these experiments, the number of sensor nodes was 1000, and the location of event area changed every 1000 s.
In different sensor node density experiments, the number of sensor nodes deployed is, respectively, 100, 120, 150, 180, and 200.
In the experiments, the number of nodes is fixed at 1000, the radius is set 100 m, and the speed of nodes is set 0 m/s.
In order to investigate the performance of classification for the five methods considered in the experiments, the number of training images per subject λ tr is also varied.
