The swarm intelligence and evolutionary methods are commonly utilized by researchers in solving the difficult combinatorial and Non-Deterministic Polynomial (NP) problems. The N-Queen problem can be defined as a combinatorial problem that became intractable for the large ‘n’ values and, thereby, it is placed in the NP class of problems. In the present study, a solution is suggested for the N-Queen problem, on the basis of the Meerkat Clan Algorithm (MCA). The problem of n-Queen can be mainly defined as one of the generalized 8-Queen problem forms, for which the aim is placing 8 queens in a way that none of the queens has the ability of killing the others with the use of the standard moves of the chess queen. The Meerkat Clan environment is a directed graph, called the search space, produced for the efficient search of valid n-queens’ placement, in a way that they do not cause harm to one another. This paper also presents the development of an intelligent heuristic function which is helpful to find the solution with high speed and effectiveness. This study includes a detailed discussion of the problem background, problem complexity, Meerkat Clan Algorithm, and comparisons of the problem solution with the Practical Swarm Optimization (PSO) and Genetic Algorithm (GA. It is an entirely review-based work which implemented the suggested designs and architectures of the methods and a fair amount of experimental results.
This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that
Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks
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An automatic text summarization system mimics how humans summarize by picking the most significant sentences in a source text. However, the complexities of the Arabic language have become challenging to obtain information quickly and effectively. The main disadvantage of the traditional approaches is that they are strictly constrained (especially for the Arabic language) by the accuracy of sentence feature functions, weighting schemes, and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha
... Show MoreAmong the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the
... Show MoreThe researchers have tried to focus on how to determine the number of pipes that are present in one obtained hyperbola in radargram profile. Ground Penetration Radar (GPR) survey was performed to distinguish between two zero-spaced iron pipes in radargram. The field work was carried out by constructing artificial rectangular models with dimensions of length, width, and depth equal to 10.0, 1.0, 0.65 meter respectively that filled with dry clastic mixture deposit, three twin sets of air filled iron pipes of 15.24 cm (6 inch) diameter were buried horizontally and vertically inside the mixture at different distances together. Visual and Numerical interpretation were chosen to get the best results. In the visual interpretation, the amplitude
... Show MoreThe researchers have tried to focus on how to determine the number of pipes that are present in one obtained hyperbola in radargram profile. Ground Penetration Radar (GPR) survey was performed to distinguish between two zero-spaced iron pipes in radargram. The field work was carried out by constructing artificial rectangular models with dimensions of length, width, and depth equal to 10.0, 1.0, 0.65 meter respectively that filled with dry clastic mixture deposit, three twin sets of air filled iron pipes of 15.24 cm (6 inch) diameter were buried horizontally and vertically inside the mixture at different distances together. Visual and Numerical interpretation were chosen to get the best results. In the visual interpretation, the amplitude
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