A LabVIEW-Based Target Optimization Genetic Algorithm for Biological Predators
Authors: Ryann Alimuin, Elmer Dadios, and Argel Bandala
Abstract
Initial projection of a continuously repositioning target is a setback in genetic algorithm; a GA program needs constant input sampling to predict and declare a targets status. Another difficulty is the incorporation of GA to hardware and software which considered as the most important tool in sensor integration. Familiarity in programming is essential in utilizing the NI LabVIEW and NI myDAQ environment. The aim of this research paper is to provide a solution for determining the locus (gene position) of a target through distinctly employed multiple sensors which employs low-frequency (LF) ground-wave oscillations as its signal sources. The targets’ position as well as the speed is continuously monitored through virtual instrument (VI) software; the user will be able to visually analyze the constant system mutation plots and the number of completed generations. Upon completion on the number of generations, the plot points can be imported to a spreadsheet for further analysis. The multiplatform software will be able to plot the response under real-time circumstances.