A GPR-PSO incremental regression framework on GPS/INS integration for vehicle localization under urban environment

Exploring the Optimal Alloy for Nitrogen Activation by Combining Bayesian Optimization with Density Functional Theory Calculations

“…Hence, the surface energy and the reaction heat of NN bond cleavage do not have a simple linear correlation. To efficiently search for alloys that will allow NN bond cleavage at a low reaction heat, it is necessary to use BO based on Gaussian process regression, which can be extended to a nonlinear regression model by kernel tricks …”

“…To efficiently search for alloys that will allow N�N bond cleavage at a low reaction heat, it is necessary to use BO based on Gaussian process regression, which can be extended to a nonlinear regression model by kernel tricks. 62 3.3. Comparison of BO Using Each Acquisition Function and Random Search.…”

Indoor navigation systems based on data mining techniques in internet of things: a survey

“…Reduce the accumulated error, improve the generation ability and minimize the use of infrastructure with fuzzy decision tree (FDT) [95] KNN Improve accuracy, adaptation and provide continuous position information based on k-nearest neighbor algorithm (KNN) [100] SVM Increase the accuracy and decrease the costs, robust against noisy and large data set with a hybrid of the k-nearest neighbors algorithm and the Multi-Class Support Vector Machines (KNN-SVM) model [99] Coarse-grained turn estimation can be performed with very high accuracy [101] Clustering Offers a formalism for identifying with use of hierarchical effective reactive algorithms for navigating through the combinatorial space in concert with geometric realizations for a particular choice of the hierarchical clustering method [96] k-means K-Means clustering is proposed to automatically identify and discard transient high amplitude interferences and make noise covariances estimation [102] Classification A realistic indoor multi path environment classification based on practical RF measurements that is a compromise between accuracy and resources/complexity [97] Regression Improve robustness and accuracy, localization error and the computation complexity based on regression tree Improvement in the positional accuracy base on Artificial Neural Network (ANN) [98] Support Vector Machine Regression (SVR) and Partial Least Squares Regression (PLSR) [103] Bayesian networks…”

Selecting Hyper-Parameters of Gaussian Process Regression Based on Non-Inertial Particle Swarm Optimization in Internet of Things

“…Zhu et al [24] utilized PSO and GA to optimize hyperparameters of GPR in the displacement prediction of geotechnical engineering, and the deformation prediction results of landslide displacement indicate that the coupling model of PSO-GPR evidently improved the prediction precision when compared to that of GA-GPR. Xiao et al [25] designed a PSO based algorithm to optimize GPR hyper-parameters, which were tuned with high time efficiency for vehicular position prediction. Peng et al [26] optimized hyper-parameters of GPR that combined the chaos control mechanism based on the traditional PSO algorithm in 2017.…”