算法
现场可编程门阵列
进化算法
计算机科学
水准点(测量)
高级合成
算法设计
人口
计算机硬件
人工智能
大地测量学
社会学
人口学
地理
作者
Jeng‐Shyang Pan,Qingyong Yang,Jyh‐Horng Chou,Chia-Cheng Hu,Shu-Chuan Chu
标识
DOI:10.1016/j.knosys.2023.110774
摘要
The QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm, a new intelligence optimization algorithm, has been widely used in many optimization fields. In this paper, a hardware-based QUATRE algorithm is designed and implemented on a field-programmable gate array (FPGA). To facilitate the implementation of the QUATRE algorithm on hardware, this paper simplifies the co-evolutionary matrix generation process. Compared with the original QUATRE algorithm, the simplified QUATRE algorithm may reduce latency and resource occupation. The Vivado High-Level Synthesis (HLS) design tool is used to complete the IP core design of the QUATRE algorithm. Through the benchmark function test under different population sizes, compared with the QUATRE algorithm implemented by software, both the running speed and optimization performance of the QUATRE algorithm implemented by hardware are significantly better than the former. Compared with the GA, DE, and PSO algorithms implemented by hardware, the QUATRE algorithm also shows strong competitiveness.
科研通智能强力驱动
Strongly Powered by AbleSci AI