文档介绍：predict model based on the improved artificial bee colony algorithm, a new model of
subsidence prediction was optimized obtained. Then, the optimized model was
applied to engineering examples. The final results shows that the error range of the
predicted subsidence and the actual subsidence amount is (0, ), which fully
demonstrates the feasibility and effectiveness of the improved artificial bee colony
algorithm in the prediction of surface subsidence, which is of great theoretical
significance for guiding on-site construction.
Finally, summarized the research content, pointed out the need for further
research on improved algorithm, and put forward the development directions of the
artificial bee colony algorithm.
Key words: Artificial Bee Colony algorithm; Tabu Search; Tabu list; Subsidence
Prediction; Probability Integral method.
Thesis: Fundamental research
目录
目录
1 绪论 ........................................................................................................................................ 1
论文研究的背景、目的和意义 .................................................................................. 1
论文研究的背景 ................................................................................................ 1
研究意义 ............................................................................................................ 2
人工蜂群算法的研究现状及发展趋势 ...................................................................... 2
人工蜂群算法介绍 ............................................................................................ 2
人工蜂群算法的研究现状 ................................................................................ 4
发展趋势 ............................................................................................................ 5
本文研究内容及研究方案 ...........................