Establishing coverage of the target sensing field and extending the network’s lifetime, together known as Coverage-lifetime is the key issue in wireless sensor networks (WSNs). Recent studies realize the important role of nature-inspired algorithms in handling coverage-lifetime problem with different optimization aspects. One of the main formulations is to define coverage-lifetime problem as a disjoint set covers problem. In this paper, we propose an evolutionary algorithm for solving coverage-lifetime problem as a disjoint set covers function. The main interest in this paper is to reflect both models of sensing: Boolean and probabilistic. Moreover, a heuristic operator is proposed as a local refinement operator to improve the quality of the solutions provided by the evolutionary algorithm. Simulation results show the necessity to inject a heuristic operator within the mechanism of evolutionary algorithm to improve its performance. Additionally, the results show performance difference while adopting the two types of sensing models.
This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t
... Show MoreIn many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th
... Show MoreIn this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req
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We apply a semi classical partial-wave scattering method based on the induced density approach (IDA) model. For ion electron scattering, the transport cross section is used to calculate the energy loss. This method yields a non-perturbative exemplification of energy loss, bridging the difference among classical and quantal representations. The focus of this work is the interaction of hetero nuclear di-cluster (He-H) ions with a free gas. The results show three kinds of stopping power in (a.u) (cluster stopping power, self-stopping power and correlated stopping power) of hetero nuclear di-cluster ions (He-H) with velocity at different atomic di-cluster distances at different densities and temperatures. We find that Bragg’
... Show MoreIt is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological
... Show MoreHuman detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
... Show MoreThe aim of this work is to develop an axi-symmetric two dimensional model based on a coupled simplified computational fluid dynamics (CFD) and Lagrangian method to predict the air flow patterns and drying of particles. Then using this predictive tool to design more efficient spray dryers. The approach to this is to model what particles experience in the drying chamber with respect to air temperature and humidity. These histories can be obtained by combining the particles trajectories with the air temperature/humidity pattern in the spray dryer. Results are presented and discussed in terms of the air velocity, temperature, and humidity profiles within the chambers and compared for drying of a 42.5% solids solution in a spray chamber
... Show MoreIn this paper the wind data that is measured for 12 months (January to December 2011) at Al-Hay district of Wasit province, southern IRAQ country has been analyzed statistically. The wind speed at heights of 10 m above ground level was measured for every 10 minutes interval. The statistical analysis of wind data was performed using WAsP software which is based on Weibull distributions. The Weibull shape and scale parameters is obtained and used in this paper statistics. The achieved results demonstrated that the study area has Annual Mean Energy Production (AMEP) about 219.002 MWh. The computations have been performed on 70m hub‟s height of the turbine and on Earth surface roughness length (0.0, 0.03, 0.1, 0.4, 1.5) m respectively.
Simulation Study
Abstract :
Robust statistics Known as, Resistance to mistakes resulting of the deviation of Check hypotheses of statistical properties ( Adjacent Unbiased , The Efficiency of data taken from a wide range of probability distributions follow a normal distribution or a mixture of other distributions with different standard deviations.
power spectrum function lead to, President role in the analysis of Stationary random processes, organized according to time, may be discrete random variables or continuous. Measuring its total capacity as frequency function.
Estimation methods Share with
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