www.nature.com/scientificreports OPEN received: 20 April 2016 accepted: 03 October 2016 Published: 21 October 2016 The temporal frequency tuning of continuous flash suppression reveals peak suppression at very low frequencies Shui'er Han1, Claudia Lunghi2,3 & David Alais1 Continuous flash ...
RMSE and R-RMSE values obtained as a function of input pixel resolution showed errors in tree quantification below 15% when 30cmpixel1 resolution imagery was used to generate the DSMs. The study conducted in two orchards with this UAV system and the photo-reconstruction method highlighted that ...
The LSTM-TCN shows good performance compared to other methods with a value of MAE = 0.236, MAPE = 3.10%, RMSE = 0.342, and R2 = 0.94. Wind power prediction is also an area where the LSTM-TCN model is applied. In Ref. [33], LSTM-TCN combined with a self-attention mechanism is ...
Therefore, we find that the resonance diagram method is more suited for the detection of low-frequency wave resonance over reef flat environments. In addition, the peak transfer values, HAy(fp,transfer), of the resulting EVres,diagram ranged from 0.63 to 3.40, showing that transfer function ...
The low RMSE values of ≤0.03 at 2.2 m and 2.9 m b.g.l. in the range of measurement accuracy of the moisture sensors demonstrated the suitability of the quasi-one-dimensional model setup and the assigned material properties for the simulation of moisture contents, which, in this area, are...
The models achieve relatively low MAE, MSE, and RMSE, indicating small errors in the prediction of wind power. The random forest model exhibits the lowest MAE, MSE, and RMSE values on the training set, suggesting superior performance in capturing the training data patterns. However, the ...
low_f_mat = sp.mean(self.power_mat[1:4 * n_chan + 1,:,:], 0).real # Factorize it into preinciple components. e, v = linalg.eigh(low_f_mat) self.low_f_mode_values = e # Make sure the eigenvalues are sorted. if sp.any(sp.diff(e) < 0): raise RuntimeError("Eigenvalues...
mean(logpxz + KLD) rmse_val = rmse_score(x, reconstructed_x) # Compute all the gradients gradients = T.grad(logpx, self.params.values()) # Adam implemented as updates updates = self.get_adam_updates(gradients, epoch) batch = T.iscalar('batch') givens = { x: x_train[batch*self....
These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89 –0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046),...
RMSE means root mean square error of the predicted height value and the ground truth. δ refers to the threshold accuracy rate, which indicates the proportion of pixels whose maximum ratio between the predicted depth and the real depth is within a certain threshold range (1.253), asδ=maxh...