20 resultados para parallel admission algorithm


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A Multi-Objective Antenna Placement Genetic Algorithm (MO-APGA) has been proposed for the synthesis of matched antenna arrays on complex platforms. The total number of antennas required, their position on the platform, location of loads, loading circuit parameters, decoupling and matching network topology, matching network parameters and feed network parameters are optimized simultaneously. The optimization goal was to provide a given minimum gain, specific gain discrimination between the main and back lobes and broadband performance. This algorithm is developed based on the non-dominated sorting genetic algorithm (NSGA-II) and Minimum Spanning Tree (MST) technique for producing diverse solutions when the number of objectives is increased beyond two. The proposed method is validated through the design of a wideband airborne SAR

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Considerable research effort has been devoted in predicting the exon regions of genes. The binary indicator (BI), Electron ion interaction pseudo potential (EIIP), Filter method are some of the methods. All these methods make use of the period three behavior of the exon region. Even though the method suggested in this paper is similar to above mentioned methods , it introduces a set of sequences for mapping the nucleotides selected by applying genetic algorithm and found to be more promising

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Combinational digital circuits can be evolved automatically using Genetic Algorithms (GA). Until recently this technique used linear chromosomes and and one dimensional crossover and mutation operators. In this paper, a new method for representing combinational digital circuits as 2 Dimensional (2D) chromosomes and suitable 2D crossover and mutation techniques has been proposed. By using this method, the convergence speed of GA can be increased significantly compared to the conventional methods. Moreover, the 2D representation and crossover operation provides the designer with better visualization of the evolved circuits. In addition to this, a technique to display automatically the evolved circuits has been developed with the help of MATLAB

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This paper presents a new approach to the design of combinational digital circuits with multiplexers using Evolutionary techniques. Genetic Algorithm (GA) is used as the optimization tool. Several circuits are synthesized with this method and compared with two design techniques such as standard implementation of logic functions using multiplexers and implementation using Shannon’s decomposition technique using GA. With the proposed method complexity of the circuit and the associated delay can be reduced significantly

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The major problem of the engineering entrance examination is the exclusion of certain sections of the society in social, economic, regional and gender dimensions. This has seldom been taken for analysis towards policy correction. To lessen this problem a minor policy shift was prepared in the year 2011 with a 50–50 proportion in academic marks and entrance marks. The impact of this change is yet to be scrutinized. The data for the study is obtained from the Nodal Centre of Kerala functioning at Cochin University of Science and Technology under the National Technical Manpower Information System and also estimated from the Centralized Allotment Process. The article focuses on two aspects of exclusion based on engineering entrance examination; gender centred as well as caste-linked. Rank order spectral density and Lorenz ratio are used to cognize the exclusion and inequality in community and gender levels in various performance scales. The article unfolds the fact that social status in society coupled with economic affordability to quality education seems to have significant influence in the performance of students in the Kerala engineering entrance examinations. But it also shows that there is wide gender disparity with respect to performance in the high ranking levels irrespective of social groups