The Particle Swamp Fuzzy Analytical Hierarchical Process (PSFAHP) for Arthropoda in a control condition Artificial Intelligence for the better growth of Prawn, Shrimp, Lobster (PSL)

Abstract

The migration of hatched PSL towards the proper location of food in the shape of a group and the suitable environment for the PSL in which important chemicals and nutrients are required for their growth are the two key elements that affect the PSL's birth and mortality rate. The first phase of this study used particle swamp optimization, which is closely connected to particle (PSL) movement toward the objective or search space, which in this case is a sea, river, or control-conditioned pond. These PSLs move with a specific velocity from their original position to the appropriate position for a better quality of life. Cost, population, learning coefficients, and particle global are all connected elements that influence PSL movement decisions. Cost, population, learning coefficients, particle global position, particle current location, updated PSL location, and particle velocity are all connected aspects that influence PSL movement decisions. Once the particles have communicated and migrated to their ideal place, they learn the path, timing, and velocity. Once the PSLs have arrived at their ideal location, several factors such as salinity, dissolved oxygen, nutrient food, and so on are involved. These two algorithms will show the PSL's death and birth rates. They will work together to defend the environment in the future. The following are the details of the algorithm. This study is hindering grisly exacerbates by curbing the core irrefutable factors like undesirable chemicals, and degraded environment.