Research on Landscape Ecological System of Highway Based on Neural Network

2012 ◽  
pp. 237-244
Keyword(s):  
Neural Network ◽  
Ecological System ◽  
Landscape Ecological

Landscape-ecological zoning of the Orenburg city based on geomorphometric, ecological and economic features of the territory

2020 ◽  
pp. 63-70
Author(s):  
S.A. Dubrovskaya ◽  
◽  
R.V. Ryakhov ◽  
Keyword(s):  
Neural Network ◽  
Urban Space ◽  
Landscape Planning ◽  
Digital Terrain Model ◽  
Ecological Framework ◽  
Natural Landscape ◽  
Territorial Planning ◽  
Object Of Study ◽  
Landscape Ecological ◽  
First Time

The article is a complex of detailed studies of the natural landscape structure and the ecological and functional purpose of the urbanized territory. The relevance of the study is determined by the fact that it is necessary to introduce territorial planning documents (master plan) and landscape planning projects, with the allocation of specific sections of the natural-ecological framework of cities. The study was conducted with the aim of studying the natural-technical geosystem to optimize the interaction of nature transformed by human activities and the socio-economic needs of society. To achieve this goal, a typification scheme for landscape structures of urban space was developed for the first time, based on a digital terrain model and using the method of automated typological zoning of relief using its morphometric data using artificial neural networks. As a result of automated training of the neural network model and verification of the data obtained, 15 classes were obtained (taxa tracts) and established the correspondence of each type of landscape in space with an indication of geomorphometric characteristics. Based on the digitized model of the functional zoning of Orenburg and types of landscapes, for the first time, an integrated map of the landscape-ecological zoning of urban space was developed and classifications of types and types of landscape zones were presented: primary and mixed. Cartographic models of the natural-landscape component of Orenburg, which is the natural-ecological framework of the object of study – recreational zones and a hydrographic network are separately presented. The results obtained are important for maintaining the landscape functions of the urbanized area, forecasting changes, and minimizing the effects of anthropogenic impact. Key words: urban planning, natural-ecological framework, functional types of land use, technological systems, type of landscape purpose, landscape, geomorphometric features, neural network algorithm.

scholarly journals Analysis of Landscape Ecological Planning Based on the High-Order Multiwavelet Neural Network Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
ChuanDong Yu ◽  
Nan Du
Keyword(s):  
Neural Network ◽  
Landscape Ecology ◽  
Wavelet Neural Network ◽  
High Order ◽  
Average Error ◽  
Ecological Planning ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Landscape Ecological Planning ◽  
Landscape Ecological

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.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural
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