A Multi-Objective Antenna Placement Genetic Algorithm for Matched Array Synthesis on Complex Platforms

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

Genetic algorithm based indicator sequence method for exon prediction

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

A Faster 2D Technique for the design of Combinational Digital Circuits Using Genetic Algorithm

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

An Improved Design of Combinational Digital Circuits with Multiplexers using Genetic Algorithm

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

On tuning the orientation of grains of spray pyrolysed ZnO thin films

Effect of varying spray rate on the structure and optoelectronic properties of spray pyrolysed ZnO film is analysed. ZnO films were characterised using different techniques such as X-ray diffraction (XRD), photoluminescence, electrical resistivity measurement, and optical absorption. The XRD analysis proved that, with the increase in spray rate, orientation of the grains changed from (1 0 1) plane to (0 0 2) plane. The films exhibited luminescence in two regions—one was the ‘near band-edge’ (NBE) (∼380 nm) emission and the other one was the ‘blue-green emission’ (∼503 nm). Intensity of the blue-green emission decreased after orientation of grains shifted to (0 0 2) plane. Scanning electron microscope (SEM) analysis of the films asserts that spray rate has major role in improving the crystallographic properties of the films. Moreover resistivity of the films could be lowered to 2.4×10−2 cm without any doping or post-deposition annealing