首页|Researcher from University of Technology-Iraq Describes Findings in Intelligent Systems (Improved rapidly exploring random tree using salp swarm algorithm)
Researcher from University of Technology-Iraq Describes Findings in Intelligent Systems (Improved rapidly exploring random tree using salp swarm algorithm)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Data detailed on intelligent systems have been pr esented. According to news reporting from Baghdad, Iraq, by NewsRx journalists, research stated, "Due to the limitations of the initial rapidly exploring random tree (RRT) algorithm, robotics faces challenges in path planning." The news journalists obtained a quote from the research from University of Techn ology-Iraq: "This study proposes the integration of the metaheuristic salp swarm algorithm (SSA) to enhance the RRT algorithm, resulting in a new algorithm term ed IRRT-SSA. The IRRT-SSA addresses issues inherent in the original RRT, enhanci ng efficiency and path-finding capabilities. A detailed explanation of IRRT-SSA is provided, emphasizing its distinctions from the core RRT. Comprehensive insig hts into parameterization and algorithmic processes contribute to a thorough und erstanding of its implementation. Comparative analysis demonstrates the superior performance of IRRT-SSA over the basic RRT, showing improvements of approximate ly 49, 54, and 54% in average path length, number of nodes, and nu mber of iterations, respectively."
University of Technology-IraqBaghdadIraqAsiaAlgorithmsIntelligent SystemsMachine Learning
NETL
NSTL
