Y. Improving harris hawks optimization algorithm for hyperparameters estimation and feature selection in ν-support vector regression based on opposition-based learning. J. Chemom. 34(11), 3311. https://doi.org/10.1002/cem.3311 (2020). Article CAS MATH Google Scholar Ismael, O. M., Qasim,...
Second, roaming density criteria were put forward, by eliciting marginal density function, to model particles’ shrinking behavior, and then, if necessarily, refine particles’ weights and, accordingly, the estimation is updated. This in turn expects to contribute to A2. In particular, in the ...
The distribution can be estimated, e.g., using kernel density estimation methods. The testing can then be performed as explained above except that the significance values are computed/integrated relative to the estimated distribution. Note that the null distribution must be estimated for each time ...
This might be a crude estimation of the redundancies within the data. However, for the results we show here the standard errors of the mean are tiny compared to the effect size and our main results would be valid even if the correction factor was much bigger. Conclusion We proposed a new...
Much of contemporary landslide research is concerned with predicting and mapping susceptibility to slope failure. Many studies rely on generalised linear m
The modified fuzzy set filter was experimented by utilizing MATLAB (version 2017a) with 4 GB RAM, 3.0 GHz Intel i3 processor and 500 GB hard disc [29]. The modified fuzzy set filter’s performance was compared with a few existing filters in order to estimate the efficiency of proposed filt...
Training options of the bi-LSTM were set as optimizer \(=\)‘Adam’ (adaptive moment estimation), including \(L_2\) regularization factor, maximum number of epochs \(= 80\), minimum batch size \(= 150\), initial learning rate \(= 0.01\), and gradient threshold \(= 1\). For the...
To analyze the performance of the proposed adaptive particle filter, we compare it with the method proposed in [27] which presented a motion estimation based adaptive particle filter for face tracking. In [27], the authors are required to manually preset the scaling factor of motion model in ...
currently operates with four particle beams available at Heidelberg Ion Beam Therapy center, i.e., raster-scanning proton (1H), helium (4He), carbon (12C) and oxygen ions (16O). FRoG enables comparative analysis of different models for estimation of physical and biological effective dose in 3D...
It provides superior performance than algorithms using Gaussian-based kernel. Actually, not only have the kernel-based functions been used in the community of adaptive signal processing and communication, but also been extended to develop optimal state estimation rules to capture high order information ...