optimization of the exploitation operation is one of the most important issues facing the mining engineers. since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. the aim of this optimization is to maximize the net present value (npv). since the objective function of this problem is non-linear, three methods can b...

Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present value (NPV). Since the objective function of this problem is non-linear, three methods can b...

Markov modeling provides an effective approach for modeling ion channel kinetics. There are several search algorithms for global fitting of macroscopic or single-channel currents across different experimental conditions. Here we present a particle swarm optimization(PSO)-based approach which, when used in combination with golden section search (GSS), can fit macroscopic voltage responses with a...

A novel rotational motion compensation algorithm for high-resolution inverse synthetic aperture radar (ISAR) imaging based on golden section search (GSS) method is presented. This paper focuses on the migration through cross-range resolution cells (MTCRRC) compensation, which requires rotation angle and center as priori information. The method performs in a nonparametric way and uses entropy cr...

The Double Exponential Smoothing (DES) and Triple (TES) are forecasting methods that require two three smoothing parameters, respectively. parameters often determined through a trial error process is not really efficient since many experiments need to be done. Therefore, in this study, parameter estimation algorithm conducted the form of modified Golden Section Search (GSS) obtain optimal from ...

Artificial Bee Colony (ABC) algorithm is a Nature Inspired Algorithm (NIA) which based on intelligent food foraging behaviour of honey bee swarm. This paper introduces a local search strategy that enhances exploration competence of ABC and avoids the problem of stagnation. The proposed strategy introduces two new local search phases in original ABC. One just after onlooker bee phase and one aft...

In unmanned aerial vehicle (UAV) applications, the UAV's limited energy supply and storage have triggered development of intelligent energy-conserving scheduling solutions. this paper, we investigate minimization for UAV-aided communication networks by jointly optimizing data-transmission UAV hovering time. The formulated problem is combinatorial non-convex with bilinear constraints. To tackle ...

This paper proposes a novel optimization algorithm Varying Population based Bacterial Foraging Algorithm (VPBFA), to solve optimal bidding strategy in a pool based electricity market. In a power market, Generating Companies (suppliers) participate in the bidding process in order to maximize their profits. Each supplier bid strategically for choosing the bidding coefficients to counter the compe...

Based on the existing study of online comment on the short text paradigm and the golden section method as introduced, an improved method that calculates the short text distance based on the Golden section method is hereby proposed. The new method considers the text distance as the combination between the semantic distance and the form distance on the basis of the importance weight and the prefe...