Link distance-support vector regression (LD-SVR) based device free localization technique in indoor environment

Machine-Learning Approaches for the Discovery of Electrolyte Materials for Solid-State Lithium Batteries

“…To solve this problem, a trial-and-error method on standard functions and cross-validation may be needed, which is time-consuming [66]. Overall, it is an effective technique due to its versatility in function selections and strength in predictive power, with a relatively small number of samples required [67,68].…”

A Systematic Review of Localization in WSN: Machine Learning and Optimization‐Based approaches

“…Specific symbols and notations used in Equation ( 65) are described in the paper. 80 Link distance-support vector machine model proposed by Anusha et al 81 frames link distance-based device-free localization in a 3D room environment of single and multiple targets. The reason behind the selection of SVM is its pliable feature.…”

“…Specific symbols used in Equation ( 66) are described in the paper. 81 An enhanced least-square algorithm for moving target localization and tracking in WSN has been proposed by Wang et al, 82 which ensembles the features of an improved Bayesian algorithm. For slumbering nodes, the range joint probability matrix keeps on updating periodically; this range joint probability matrix is created by the improved Bayesian algorithm.…”

“…Layering and filtering of longer links play a vital role in improved results. The position of the node is as follows: Specific symbols used in Equation () are described in the paper 81 …”

Parameters Adjustment Optimization for Prepreg of Copper Clad Laminate Based on Virtual Metrology

“…SVR was proposed by Vapnik [23]. Different from general regression, of which the goal is to find a function that can minimize the sum of square error, SVR allows the error to be smaller than ε [24]. Figure 2 shows the difference between general regression and SVR.…”