Exploration On Optimization Of Planting Density Of Vallisneria And Construction Of Multi-agent Model

In the field of water environmental management,bioremediation methods have always been a hot topic.In recent years,the urban artificial landscape water body has been increasing,but due to improper maintenance,the corresponding water pollution phenomenon has gradually intensified.At this time,the treatment and maintenance of water bodies is more urgent.In this paper,the effects of submerged plant bitter grass on the treatment of polluted water are studied.Through the indoor micro-artificial water culture experiment,the optimal applicability planting density of bitter grass in the treatment of polluted water is explored.For the real society water management provides certain technical support and assistance.Firstly,the chlorophyll a concentration and water quality factor content in water were monitored under the indoor experiment conditions.Correlation analysis,analysis of variance and principal factor identification analysis were used to determine the main controlling factor of algae growth in the bitter grass group is:DO?TP?TN and Tur.The RBF neural network is used to verify the four main control factors,and finally the four main control factors obtained have higher accuracy and credibility.Secondly,the water quality of the two experimental stages was evaluated by fuzzy neural network.On the one hand,it was found that the bitter grass had an excellent promotion effect on the water purification.On the other hand,the purification effect of bitter grass on water body is not enhanced with the increase of planting density.The evaluation results show that the difference in planting density of bitter grass affects the purification effect of water quality to some extent,and the best density exists in the planting of bitter grass.Then,using the analytic hierarchy model to analyze the experimental water bodies planted with different density of bitter grass,it is concluded that the scheme weight value of the 10 strains of bitter grass is the largest,and the 20 plants are the second.It is initially found that in the indoor eutrophic water culture experiment,the applicability and rationality of the bitter grass planting density with better purification effect range from 0 to 20 plants.Furthermore,the optimal planting density of bitter grass was further explored by nonlinear constrained optimization method.Finally,the optimal value of planting density of bitter grass in experimental water was 50/m2,which was reasonable and scientific to provide reference for improving the water pollution control.Finally,based on cellular automata and multi-agent modeling technology and NetLogo platform,a water system model of bitter grass and algae growth is constructed.Through the study of the behavior rules of the main body,the dynamic evolution of water body under different density of bitter grass planting was simulated,and the simulation results of water body simulation were analyzed.The validity and accuracy of the simulation model construction and the optimization of planting density of bitter grass were obtained.