Open AccessEnvironmental Assessment Model Based on the Back Propagation Neural Network
Author(s) -
Dengli Zhou
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/300/3/032105
Subject(s) - quality (philosophy) , balance of nature , environmental quality , environmental resource management , computer science , artificial neural network , environmental planning , balance (ability) , backpropagation , environmental science , environmental economics , business , ecology , economics , artificial intelligence , medicine , philosophy , epistemology , physical medicine and rehabilitation , biology
With the continuous development of economy and society, the problem of environmental pollution is becoming more and more serious. However, people’s demand for a better environment is increasing. Under this background, it becomes particularly important to effectively evaluate the quality of the environment. So we use the Back Propagation Neural Network(BPNN) to establish a weight model. The model mainly includes Driving force, Pressure, Status, Influences, Response indicators and has strong practicability. Subsequently, we examined the impact of land development projects on the environment and conducted an analysis of land development projects taking into account environmental costs. Finally, we use our model to evaluate the Three North Shelter Forest project. Through the evaluation, we can find that the project has greatly improved the local ecological environment, making it a great project. To sum up, the model we have established can effectively evaluate the quality of ecological balance and has certain practical guiding significance.