Design And Implementation Of Forecasting Technical Indicators Of Transmission Line Engineering

In the consulting stage of the transmission line project and the preliminary design stage of the project,its engineering estimates or estimates are of great significance to the project decision or project preparation.Among them,the accurate estimation of the engineering quantity index is the key point in the preparation of the estimates or estimates.For the line engineering,the terrain,geological and meteorological conditions,crossing and other factors of the area where the line is located are very different.It is very difficult to accurately estimate the amount of line engineering in the early stage or preparation stage,of which the estimation of the tower index is still difficult and critical..In order to help engineering designers and experts accurately and conveniently predict and analyze various technical indicators of transmission line engineering quantities,this thesis designs and develops transmission line engineering technical index prediction software.Through the establishment of a database,machine learning algorithms are used to make use of the high-speed computing power of the computer for predictive analysis.The software is mainly divided into four sub-modules,namely user front-end interface(GUI)sub-module,back-end database sub-module,predictive analysis sub-module and result analysis sub-module.Among them,the back-end database module includes a typical tower database,engineering technology index database,user information database;inference decision analysis module includes SVR support vector inference machine,BP neural network inference machine and multiple linear regression inference machine,the prediction result analysis module is for prediction The resulting data is analyzed and the rules are displayed to the user.The software accesses the database remotely by logging in locally,searches and queries relevant data to form a sample set,and then passes it to the predictive analysis submodule for data prediction and analysis.Finally,the result is returned to the user interaction system submodule,and the result is visually displayed to the user.This thesis mainly relies on two methods to predict the technical indicators of transmission line engineering,namely the tower re-emphasis algorithm and the technical index prediction method.Among them,the Tieda database serves the tower relaunch algorithm,and the engineering technology index database serves the technical index prediction method.Finally,the prediction method is verified through five practical cases.Because of the lack of sufficient data,the tower reintroduction algorithm cannot be effectively verified.For the technical index prediction method,the three algorithms of support vector regression,BP neural network and multiple linear regression have obtained satisfactory results.