Harris Hawks Optimization Model For Large Scene Video Monitoring Network Coverage Of High Core Rockfill Dam

The construction of high core rockfill dam is complex,with many construction machinery and personnel,which has great potential safety hazards.As a monitoring means with low economic cost and wide sensing range,video monitoring is of great significance for controlling the construction progress,ensuring the project safety and improving the level of construction supervision.However,at present,the layout of dam surface video monitoring network mainly depends on manual experience.There is a lack of comprehensive consideration of construction cost in the existing relevant research,and the commonly used video monitoring network coverage optimization method has some shortcomings,such as slow convergence speed and easy to fall into local optimization.To solve the above problems,this paper proposes a harris hawks optimization model for large scene video monitoring network coverage of high core rockfill dam.The main research results are as follows:(1)Aiming at the uncertainty of video surveillance network based on human experience,a large scene video monitoring network coverage optimization model for high core rockfill dam is proposed.According to the imaging principle,the geometric relationship between the camera and the dam coordinates of the sampling point is determined,and the optimization mathematical model of video monitoring network is constructed based on the set coverage model;In the light of the geographical environment and construction characteristics of high core rockfill dam,considering the relationship between repeated coverage area and construction cost in video monitoring network,the index of resampling rate per camera is proposed;Based on this index and coverage index,the mathematical model of large scene video monitoring network coverage optimization of high core rockfill dam is constructed,and then the layout scheme of dam surface video monitoring network is optimized.(2)Aiming at the problems of slow convergence speed and easy to fall into local optimization in traditional video monitoring network coverage optimization methods,a chaotic harris hawks optimization algorithm based on nonlinear energy is proposed.In order to solve the optimization problem of video monitoring network involving high-dimensional variables,based on the traditional harris hawks optimization algorithm,tent chaotic mapping is used to optimize the initial population distribution of harris hawks,so as to enhance the search ability and optimization speed of the algorithm;A nonlinear energy updating strategy is proposed to balance the transformation process of global search and local search,and enhance the local search ability in the later stage of the algorithm,so as to improve the overall optimization ability of the algorithm.(3)Taking a high core rockfill dam in Southwest China as an example,the effectiveness and superiority of the proposed model are verified.The optimal layout of dam surface video monitoring network is carried out by using the proposed harris hawks optimization model for large scene video monitoring network coverage of high core rockfill dam.The effectiveness of the model is verified by comparing the optimization scheme with the empirical scheme.At the same time,the superiority of the model is verified by comparing the improved Harris Eagle algorithm with the traditional harris hawks algorithm,particle swarm optimization algorithm,whale optimization algorithm,grey wolf optimization algorithm and butterfly optimization algorithm.The coverage of the optimized scheme and the proportion of repeated sampling points obtained in this study are 99.98% and 60.3%respectively,which are 13.8% and 23.2% higher than the empirical scheme,and significantly optimize the video monitoring effect.