Abstract
Landscape architecture has both natural and social properties, which is the embodiment of people protecting the natural environment. Since the industrial revolution, the modern industry has developed rapidly. It has increased the living standard of people and consumed a lot of natural resources such as forest and energy. The ecological environment has been greatly damaged, and the landscape of gardens has been affected. Therefore, it is of great significance to find a method to evaluate the landscape ecology and plan the landscape ecology. This paper proposes a new high-order wavelet neural network algorithm combining wavelet analysis and artificial neural network. A model of ecological evaluation of landscape based on high-order wavelet neural network algorithm is proposed to evaluate the landscape ecology and provide reference data for the ecological planning of the landscape. The results show that the training times of the wavelet neural network to achieve the target accuracy are 3600 times less than those of the BP neural network. The MSE and MAE of the WNN are 0.0639 and 0.1501, respectively. The average error of the model to the comprehensive evaluation index of the landscape ecology is 0.005. The accuracy of the model to evaluate the sustainability of landscape land resources is 98.67%. The above results show that the model based on the wavelet neural network can effectively and accurately complete the evaluation of landscape ecology and then provide a decision-making basis for landscape ecological planning, which is of high practicability.
Highlights
Landscape architecture has both natural and social properties, which is the embodiment of people protecting the natural environment
Landscape has both natural and social attributes, which is a special landscape dominated by human activities [3]. e ecological planning of landscape refers to the planning measures taken to ensure the ecological balance of landscape based on the principles of ecology and the laws of society and nature. erefore, the ecological planning of landscape can improve the status of the ecological environment, ensure the good development of the ecological environment, and make people feel the importance of environmental protection [4]
Dhibi and Ben Amar [6] proposed a new method based on the multimother wavelet neural network (MMWNN) structure optimized by genetic algorithm to deal with Laplacian boundary deformation, and compared with the method based on LM algorithm, the results show that the processing speed and accuracy of the new method are better than those based on LM algorithm
Summary
Renewable resources should be used as much as possible in planning, and resources should be used efficiently and circularly [16]; practical principle: in the planning, the landscape needs to be in line with the reality and formulate the reasonable planning content [17]; economic principle: when carrying out ecological planning, we should try to control the cost and spend the least money to plan the most satisfactory effect. The evaluation index system has a great impact on the accuracy of the WNN model in the evaluation of the ecological status of landscape. Erefore, in the investigation and research of landscape, it is necessary to obtain as many parameters as possible that can reflect the ecological status of landscape and process them to ensure the accuracy of the data [18] The evaluation index system has a great impact on the accuracy of the WNN model in the evaluation of the ecological status of landscape. erefore, in the investigation and research of landscape, it is necessary to obtain as many parameters as possible that can reflect the ecological status of landscape and process them to ensure the accuracy of the data [18]
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