The invention discloses a multi-unmanned aerial vehicle atmospheric pollution source positioning method based on an improved teaching and learning algorithm, a multi-unmanned aerial vehicle group is innovatively combined with the improved teaching and learning algorithm, and an individual ability value model is provided, three indexes of unmanned aerial vehicle electric quantity, unmanned aerial vehicle flight height stability and pollution source gas concentration value searched by the unmanned aerial vehicle are adopted, and an individual capability value is used for replacing a random learning step length in a standard teaching and learning algorithm, so that the individual difference of the unmanned aerial vehicle is increased, the teaching and learning optimization algorithm is ingeniously combined, and the selection of the random step size has higher basis. Besides, a student class-by-class learning rule is adopted in a learning stage of teaching and learning an algorithm, so that the students can quickly approach to the reinforced class group in a later stage of the algorithm, and more detailed search is carried out. The search efficiency of the algorithm is improved, and efficient positioning of the atmospheric pollution source is realized.
本发明公开了一种基于改进教与学算法的多无人机大气污染源定位方法,创新性的将多无人机群与改进教与学算法相结合,提出了一种个体能力值模型,采用了无人机电量、无人机飞行高度的稳定性、无人机搜索的污染源气体浓度值三个指标,用个体能力值替代了标准教与学算法中的随机学习步长,既增加了无人机个体的差异性,也巧妙的结合了教与学优化算法,使随机步长的选择更有依据性。并且在教与学算法的“学”阶段采用学员分班学习规则,使得在算法后期,学员能够迅速向强化班集体靠近,进行更加细致的搜索。提高了算法的搜索效率,实现了对大气污染源高效的定位。
Multi-unmanned aerial vehicle atmospheric pollution source positioning method based on improved teaching and learning algorithm
一种基于改进教与学算法的多无人机大气污染源定位方法
2021-11-12
Patent
Electronic Resource
Chinese
IPC: | G01N Untersuchen oder Analysieren von Stoffen durch Bestimmen ihrer chemischen oder physikalischen Eigenschaften , INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES / B64C AEROPLANES , Flugzeuge / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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