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...

The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version created by the researchers from the University of Tehran. The authors of the present paper have extended the exIWO algorithm introducing a set of both deterministic and nondeterministic strategies of individuals’ selection. The goal of the project was to evaluate the e...

ardekoul fault zone which is along nnw-sse is located in eastern iran and northern part of the sistan subzone. dextral strike-slip fault zone of ardekuol is made of six main segments including korizan (28 km), bohn abad (8.8 km), abiz (32 km), gazkoon (20 km), moein abad (30.4 km), ghal maran (12 km), and two minor segments including olang morgh (12.8 km) and seh pestan (9.6 km).  the studied r...

The Weighted Set Cover Problem (SCP) is a popular optimization problem that has been applied to different industrial applications, including scheduling, manufacturing, service planning and location problems. It consists in to find low cost solutions covering a set of requirements or needs. In this paper, we solve the SCP using a recent nature inspired algorithm: Invasive Weed Optimization (IWO)...

Invasive Weed Optimization is a recently proposed population based meta-heuristic that mimics the colonizing action of weeds. In this article, an improvement to the classical algorithm has been proposed by introducing a constriction factor in the seed dispersal stage. Temporal Difference Q-Learning has been employed to adapt this parameter for different population members through the successive...

Heuristic optimization provides a robust and efficient approach for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier. The convergence rate and suitable diversity of solutions are of great importance for multi-objective evolutionary algorithms. The focu...

Minimum cross-entropy is widely used in image segmentation for its effectiveness. However, when the algorithm applied to multi-threshold segmentation, there are some problems such as large amount of calculation, time-consuming and poor practicability due exhaustive search optimal threshold. Therefore, this paper, a hybrid whale optimization (IWOA) which incorporates (WOA) invasive weed (IWO) pr...

In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. The K-means model was used for clustering the maintenance stations. The optimal number of clusters was calculated through the Silhou...

How to select the suitable parameters and kernel model is a very important problem for Twin Support Vector Machines (TSVMs). In order to solve this problem, one solving algorithm called Invasive Weed Optimization Algorithm for Optimizating the Parameters of Mixed Kernel Twin Support Vector Machines (IWO-MKTSVMs) is proposed in this paper. Firstly, introducing the mixed kernel, the twin support ...