because of high cost of drilling and analysis of samples, it needs to predict gold and silvers based on pathfinder such as as, sb, cd, pb and zn and decrease the cost and time exploration project implementation. in this paper, the model based on a multilayer perceptron artificial neural network (mlp-ann) optimized by invasive weed optimization algorithm (iwo) to predict of gold and silver in za...

Aiming at the insufficiency of credit scoring models, this paper puts out a new approach by using combining forecast model for personal credit scoring. Based on linear regression and logistic regression models, this paper constructed a combining model and used particle swarm optimization (PSO) to search each single model’s weight. In order to control the type II error rate,the particle’s fitnes...

Land resource management requires extensive land mapping. Conventional soil mapping takes a long time and is expensive; therefore, geographic information system data as predictor in texture modeling can be used an alternative solution to shorten reduce costs. Through digital elevation model data, topographic variability obtained independent variable predicting texture. Geographically weighted r...

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit’s centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automat...