In this paper, a novel PSO–SVR model that hybridized the constrict particle swarm optimization (PSO) and support vector regression (SVR) is proposed for ...
Jun 6, 2010 · This hybrid PSO–SVR model searches for SVR's optimal parameters using constrict particle swarm optimization algorithms, and then adopts the ...
Apr 17, 2023 · The IDWW method offers significant theoretical advantages and addresses the adverse effects of uneven sample lengths on the estimates. The IDWW ...
In this paper, we propose a grade estimation technique that combines multilayer feed-forward neural network (NN) and k-nearest neighbour (kNN) models to ...
Jul 26, 2023 · This involves automatically identifying and combining data variables that are most relevant to the prediction task. For example, in estimating ...
The model is a self-adaptive parameters optimizing one through using PSO algorithm to search the global optimum values of number of historical points and ...
Apr 30, 2023 · Estimation theory is a sub-section of the wide-ranging field of statistics and signal processing. Estimation methods attempt to predict, filter, ...
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Feb 26, 2019 · Accurately predicting students' grades in future courses has attracted much attention as it can help identify at-risk students early so that ...
Random forests begins with the p columns of x as predictors, but then coins a host of new predictors via the splitting process (e.g., “cpap less than or greater ...