Study On Intelligent Flood Disaster Prediction And Evaluation Models In Flood Control Decision-Making

Currently,with the aggravation of global floods disaster,non-structural measures against floods have drawn more attention.Under this background,it has practical sense to develop a flood disaster evaluation system in flood control decision-making.With the analysis of demands of current disaster evaluation we designed a function framework for the evaluation system.Also, computer technology,artificial intelligent technology,visual simulation technology,mathematics, management,decision-making,and other technologies have been used to build a complete set of evaluation models.Our work has established foundation for achieving scientific,systematic,and rational disaster evaluation.The main contributions of the paper are:(1)We put forward the three-layer architecture of the decision support system(DSS)for flood control,including interface layer,application layer,and foundation layer,and make detailed design separately.Hereinto,the foundation layer provides information and technology support for the system,it includes database(storing space data and attribute data),model-base and knowledge-base;the interface layer implements friendly interaction between system and analysers;the application layer uses data and models to implement the analysis of information requirements in every part,it is the hard-core of the system.After that,each function sub-system is designed,respectively.(2)A genetic algorithm(GA)-based BP neural network model for flood peak prediction is built.Aiming at the shortage of BP network used in the flood prediction,a novel GA-BP network prediction model is proposed through combined GA computing steps with network optimization process.With the practical data,simulation prediction and result analysis are done through adopting BP and GA-BP network model,respectively.The results demonstrate the flood prediction with the GA-BP network can improves the prection efficiency and preciseness.(3)We put forward an algorithm and model for terrain and flood simulation in the flood prediction system.In order to complete the visual simulation of submerge course,we do three-dimension landform simulation based on grid model method.Then we advance an improved adaption algorithm based on butterfly-subdivision model,and compute a new insert value point through combining with the butterfly-shape algorithm and multi-steps curve insert value,subdivide selectly the trangle unit network to simulate three-dimension terrain.It can be as a foundation architecture for the real-time flood system.And,from the DEM,we use improved grid spread algorithm to simulate flood-inundated process and estimate flood-inundated area and water-deep distribution under certain condition of flood water levels or flood volumes.Finally, we use Web-based 3D visualization tool(Java 3D)to draw flood hazard maps,and demonstrate flood-inundated process dynamically under different conditions.(4)The flood disaster fast evaluation algorithms during the flood control decision-making are studied.According to the evaluation requirements of the different flood phases and the evaluation indexes of the flood situation,we build the fast evaluation models of flood simulation using grey-relating analysis,BP network and RBF network.Thereinto,RBP network is improved based on the basic RBF network,that is,replacing the primary linearity layer with competion layer to make the model complete mode judgement.Through the instance analysis,three models can acquire the good evalutation results.Especially,the gray-relating analysis and RBF network model has the fast evaluation speed and high stability.Thus,these two models can be used into the fast flood disaster evaluation system and the operation results can provide scientific guidelines for the flood control decision-making.(5)We put forward a flood disaster evaluation model based on immune genetic algorithm (IGA).Aiming at the shortage of the weak local search capability and immaturity,we advance an IGA-NN model to evaluate the flood disaster,and present the IGA-NN design method and optimization steps.We compare the IGA-NN with the SGA-based optimized network model to show the superiority of the IGA-NN.The results shows that IGA has better global and locally optimization capability and improve the immaturity convergence of the SGA.IGA-NN can inflect the correlativity between the multi-indexes and disaster levels,evaluate the flood disaster, and have faster responsion speed and higher evaluation precision.(6)We design and implement flood precision and evaluation system for the flood control DSS.Through the requirement analysis of flood prediction and evaluation system,we design the system.According to the different course of the flood disaster development,the flood evaluation system is divided into three main functional modules,that is,flood prediction,flood decision-making,and flood evaluation.We discuss its important function in the flood contrl DSS and confirm its function architecture.In addition,we design the interface between the sub-systems.At last we implement the three function modules among flood prediction and evaluation system.Finally,we conclude the thesis,and provide the direction for further studies.