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 to check the performance of each algorithm, and the other test for 30 trials to measure the statistical results of the performance of the proposed algorithm against the others. Results confirm that the proposed FTMA global optimization algorithm has a competing performance in comparison with its counterparts in terms of speed and evading the local minima.
In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as the Bayes method. The comparison was made using the mean error squares (MSE), where the best estimator is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).
Abstract
Although the rapid development in reverse engineering techniques, 3D laser scanners can be considered the modern technology used to digitize the 3D objects, but some troubles may be associate this process due to the environmental noises and limitation of the used scanners. So, in the present paper a data pre-processing algorithm has been proposed to obtain the necessary geometric features and mathematical representation of scanned object from its point cloud which obtained using 3D laser scanner (Matter and Form) through isolating the noised points. The proposed algorithm based on continuous calculations of chord angle between each adjacent pair of points in point cloud. A MATLAB program has been built t
... Show MoreIntended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted
... Show MoreIn this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad. One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.
The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a
... Show MoreRA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
... Show More<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T
... Show MoreThis research aims to test the causal relationship long-and short-run between the price of gold the global crude oil price and the exchange rate of the dollar and how you can take advantage of the nature of this relationship, particularly in the Arab oil states that achieve huge surpluses, including Iraq and how to keep on the purchasing power of these surpluses or reduce the levels of risk.
The problem is that the Arab oil countries, adversely affected, as a result of that relationship, due to the fact that its role confined to the sale of crude oil only. They do not have control in the dollar, then they are not able to take advantage of its impact on the price of gold the fact that gold is effective pr
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