In this paper, a hybrid inverse distance weighted (IDW) and the imperialist competitive algorithm (ICA) was proposed for grade estimations in mining projects. Indeed, coefficients of IDW equation, power, influence were modified by applying ICA algorithm. For this, an example solved using IDW, ordinary kriging, IDW-ICA. After successfully validating IDW-ICA, iron grades estimated Baba Ali mine, ...

abstract: this paper presents dynamic modelling and control of a linear prismatic series of elastic actuator. the capability of generating large torques is why this actuator is increasingly used in human-assistive robotic systems. due to having human in the loop, the actuator requires precise control. a fractional pid controller known for its improved performance is used for the control, due to...

the spatial distribution of petrophysical properties within the reservoirs is one of the most importantfactors in reservoir characterization. flow units are the continuous body over a specific reservoirvolume within which the geological and petrophysical properties are the same. accordingly, anaccurate prediction of flow units is a major task to achieve a reliable petrophysical description of a...

this paper presents a novel indirect adaptive power system stabilizer (pss) via a developed synergetic control methodology and fuzzy systems. fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. the synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law...

We consider max coloring on hereditary graph classes. The problem is defined as follows. Given a graph G = (V, E) and positive node weights w : V → (0,∞), the goal is to find a proper node coloring of G whose color classes C1, C2, . . . , Ck minimize k ∑ i=1 maxv∈Ci w(v). We design a general framework which allows to convert approximation algorithms for standard node coloring into algorithms fo...

in this study, we considered some competitive learning methods which include hard competitive learning (hcl) and soft competitive learning (scl) with/ without fixed network dimensionality for reliability analysis in microarrays. in order to have a more extensive view, and keeping in mind that competitive learning methods aim at error minimization or entropy maximization (different kinds of func...

 Numerous problems in engineering and science can be converted into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been widely used in many areas. However, due to the stochastic characteristics of its solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness o...

This paper presents and discusses some competitive learning algorithms for data clustering. A new competitive learning algorithm, named the dynamically penalized rival competitive learning algorithm (DPRCL), is introduced and studied. It is a variant of the rival penalized competitive algorithm [1] and it performs appropriate clustering without knowing the clusters number, by automatically driv...

Template matching is a widely used technique in many of image processing and machine vision applications. In this paper we propose a new as well as a fast and reliable template matching algorithm which is invariant to Rotation, Scale, Translation and Brightness (RSTB) changes. For this purpose, we adopt the idea of ring projection transform (RPT) of image. In the proposed algorithm, two novel s...

We consider the problem of scheduling resource allocation where a change in allocation results in a changeover penalty of one time slot. We assume that we are sending packets over a wireless channel of uncertain and varying capacity. In each time slot, a bandwidth of at most the current capacity can be allocated, but changing the capacity has a cost, which is modeled as an empty time slot. Only...