Application of New Modified Genetic Algorithm in Inverse Calculation of Strong Source Location

Abstract

With the rapid development of intelligent systems, the application of genetic algorithms to quickly and accurately determine the location of hazardous gas leaks is of great practical significance. To further improve the convergence efficiency and stability of the inverse calculation, a new improved genetic algorithm (NMGA) is designed on the basis of the improved genetic algorithm (MGA). The adaptive crossover rate and mutation rate change with the evolution algebra to guide the development trend of good gene genetics and change the genetic crossover ratio of parents and children in the culler’s gene pool to avoid damaging the good group genes by introducing bad genes. This study modified the adaptive crossover rate and mutation rate that change with the evolutionary generations to guide the development of good gene inheritance. Meanwhile, this study changed the genetic crossover ratio of parent and offspring in the elimination gene pool to avoid the introduction of unfavorable genes and the destruction of excellent group genes. Through the calculation simulation of the new improved genetic algorithm (NMGA) in Matlab and the quantitative and qualitative comparative analysis with the MGA statistical results, it is shown that NMGA can improve the slow convergence speed of MGA by reducing the number of iterations on the premise of ensuring the stability of MGA and the accuracy of the inverse calculation. The results indicated that the convergence rate and stability of NMGA greatly improved its convergence efficiency, inverse calculation accuracy, and stability, thereby providing powerful decision-making data for rapid emergency rescue work for sudden light gas leakage accidents.

Keywords

• new modified genetic algorithm (NMGA)
• strong source inverse calculation
• Matlab
• slow convergence
• stability