Intelligent Hunting Mode of Orca Behavior for Computational Model of Artificial Algorithm A.N. Afandi
Universitas Negeri Malang
Abstract
The orca is referred to as the killer whale where Orcas consume a variety of prey, often specializing in particular kinds of marine mammals like seals and other dolphin species. Orca hunting techniques are inventive and sophisticated and evolved physiologically in reaction to their prey. The hunting activity in this strategy is particularly intriguing since it may be used for instruction, social learning, or even teaching younger group members how to hunt effectively. By choosing prey based on strength and speed before catching everything, hunting can be seen as a significant aspect of orca society. In this work, a piece of artificial intelligence called the Orca Algorithm is built on a hunting method that considers these preferences. The Selection Stage, Speeding Stage, and Ambushing Stage are processes used in the development of the Orca Algorithm. Searching for a maneuver that will result in the desired outcome while speeding is an intelligent mechanism. The selection stage is used to choose the ideal target from all potential targets for catching the intended prey. In addition, the Orca number, Wave factor, Prey number, and Hunting cycle are characteristics of the Orca Algorithm. In this study, Orca Algorithm is applied to a dynamic problem associated with flexible loads. The simulation results show that the Orca Algorithm finds the best solution to the problem in the fewest iterations. The computations used to determine demand changes over all periods are fast and smooth, with strong convergence characteristics. In addition, the problem features various characteristics as well as changing usage to cover the whole length solution. Another activity related to service/shopping uses 35,350 EV while the vehicle drives for leisure time around 55,250 and 7,950 for another purpose. Moreover, the EVs have charged in a total power of 3,177.8 MW distributed for a pattern of 2,535.8 MW for two trips and 62.1 MW one way.
