Download Application of Neural Networks for the Environmental Quality

Application of Neural Networks for the Environmental Quality
Assessment of Eco-Agriculture Tourism1
SHI Yunxia
School of Business Management, Shandong Institute of Business and Technology, P. R. China, 264005
[email protected]
Abstract: The eco-agriculture touring environmental was closely related to sustainable development of
eco-agriculture tourism. The key to realize the sustainable development of eco-agriculture tourism was
the matter of the touring environment quality. In this paper, the evaluation system of eco-agriculture
tourism is set up and Neural Networks Method is used for the environmental quality assessment of
eco-agriculture tourism. It shows that making use of the method BP nerve network to evaluate a
eco-agriculture touring environmental quality was a suitable and valid method.
Keywords: Eco-agriculture tourism, Tourism environment, Environmental quality, Evaluation, BP
nerve network
1.
Introduction
The tourism industry has become the rapid development of the economy in the world. According to
conservative estimates, tourism income has surpassed more than 6% of global GNP. About 1.3 billion
people join into the tourism industry, which covers more than 6% of the global human resource. Tourism
industry has become the industrial types which has larger global output and higher employment rate in a
short decade. Because of the success of tourism industry in the world which cover the destroy of the
natural environment the study of tourism environment is relatively lagged behind other branches. We
should clearly recognize that tourism is highly dependent on the environment one of the industries. A direct
result of the deterioration of ecological environment of resources and environmental quality decline
threatens the sustainable development of tourism. We have to "smoke-free industrial smoke," sounded the
alarm bell, carrying out environment impact assessment, environmental protection and ecological
construction. It can be said from the birth of modern tourism began in 1841 the last century 60's, the tourism
environment of almost zero. These thriving tourism industry and tourism researches in other disciplines do
not match the rapid development. 40 years since the 40s of 20th century, with accelerated industrialization
and urbanization around the world, continue to the massive industrial pollution incidents have happened in
many developed countries. At the same time, environmental assessment emerged. After 60s, tourism
geographers and environmental scientists began to focus on tourism development in the environmental
quality evaluation process, gradually changing from exposing the fact that the negative impact of tourism to
the assessment of the cost of such negative impact. Our research works are relatively late.
Ecological agriculture tourism is a type of combination of eco-agriculture and eco-tourism. The difference
between Eco-agriculture tourism and general eco-tourism is that the background of Eco-agriculture
tourism’s activities is mainly in the rural ecological environment, and its active content usually revolves
around various aspects of ecological agriculture production and rural culture to carry out a series of
sightseeing, tours, technology demonstrations, agricultural experience, leisure, entertainment, fitness,
shopping, education and other activities with a benign environment and the special atmosphere. Most
Eco-agriculture tourism relies on the local village and town. In order to maximize the profit rather than focus
on ecological and environmental protection, the local places often ignore the protection of ecological
environment, making the ecological environment with picturesque scenery and fresh air before worsened,
and the significance of the ecological agricultural tourism is loosing. So how to establish a complete set of
scientific Eco-agriculture tourism development evaluation index system which is the integration of
，
1
This research is sponsored by the funds of Scientific Development Program of Shandong Academic Institutes.
760
ecological agriculture and ecological tourism, and by which to measure the sustainability of the
development of ecological agriculture tourism in China.
The Sustainability of the tourism place, combining the ecological functions, agricultural and tourism
function of Eco-agriculture tourism together for further planning and development is China's current
important issue be solved. So far the academic evaluation on the ecological quality of agricultural tourism is
less specialized, the majority of which focused on the existing environmental impact of tourism such as
environmental capacity. This paper tries to provide a comprehensive and effective evaluation of tourism
environment by the establishment of ecological agriculture tourism environment quality evaluation system,
using the method of BP neural network to provide a reference for the environmental protection of ecological
agriculture tourism.
2.
The Construction of Eco-agriculture Tourism Environmental Quality
Evaluation System
2.1 The definition of the concept of tourism environment and the definition in this paper.
The current academic Definition of the concept of tourism environment in Chinese has not fully unified.
Zhou Yanting thinks that tourism environment refers to the physical environment formatted by natural and
human factors in all areas with tourism value. Liu Zhenli believes that the so-called tourism environment, in
terms of its content, includes both natural and social factors related with tourism activities and, more
importantly, includes the situation of tourism resources. Chen Anze believes that the tourist environment
refers to the sum of external conditions on which tourism activities exists and be carried out, including the
social and political environment, natural environment, tourism environment and climate itself and tourism
resources. Even though there are many divergent views of definition of the concept of the tourism
environment, the tourism landscape, ecological and social conditions of service constitute the main factors
of the tourism environment. By taking the natural environment as example, the corresponding
eco-environmental quality evaluation system of agriculture and tourism is built in this paper.
2.2 Tourism Environmental Quality Evaluation System
2.2.1 The principle of the Construction
Indicators are the basic standards and metrics of assessment. Indicators system is the fundamental conditions
and theoretical basis of ecological assessment. Whether it will be built successfully or nor will decide the
authenticity and feasibility of the evaluation results. There are many factors that constraint the quality of
tourism environment. When we select the evaluation factors, we should be guided by the following
principles: First, scientific principles, evaluation of selection should be based on accurate scientific basis, to
be selected to reflect the comments of Tourism and the essential characteristics of eco-environmental quality
change in status indicators. Adopt the scientific theory and methods to construct the index system which can
reflect the developing actual state and development direction of the ecological agriculture tourism
objectively, which have the scientific guidance. Second, dominant principle, tourism ecological quality is
affected by geology, physiognomy, soil, vegetation climate and other factors, in many factors, the role of
various factors and mode of action of the process are different, therefore, should choose a representative
which can directly reflect the environmental quality of regional tourism the main features of the dominant
indicators. Third, the operational principle, the selected indicators should be the main factors that can affect
the development of ecological agriculture and tourism.
2.2.2 The method of the Construction
Index system is not only the carrier of the content of the tourism environmental quality, but also the external
expression of it. In accordance with the systematic thinking, the part of the tourism environment was
decomposed. These components or elements are ordered into one kind of class and each integral part was
evaluated individually. Then the whole environmental quality system was evaluated. For scientific,
comprehensive, objective and clear demonstration of the tourism environment in the form of quality
evaluation system, we divided them into two levels: the first level indicator is to show the basic elements of
761
composition; second indicator is to show the characteristics of the tourism environment directly and
concretely, based on the further refinement of basic elements.
2.2.3 The construction of evaluation index system
The ecological tourism environment of the study area is a complex systemic one, and its basic features
include integration, space and its time stability. The factors that affect the quality of Eco- agricultural
tourism environment are manifold. The construction of evaluation index system is to get scientific,
systematic implementation of the comprehensive analysis of aimed object. So the indicators should be given
full consideration of scientific and regional particularities. Based on the above principles and references to
other documents and relevant experts, taking into account the feasibility of actual supporting data, the author
establish Eco—environmental quality evaluation system of the Eco—agricultural tourism (Table 1).
Tab.1 Eco—environmental quality evaluation system of the Eco—agricultural tourism
Eco—environmental quality evaluation system of the Eco—agricultural tourism(U)
Air Quality U1
SO2n The average concentration (U11)
NO2n The average concentration (U12)
TSP The average concentration (U13)
Water Environment U2
BOD(U21) COD(U22)
Dissolved nitrogen (U23) TN(U24)
Climate and weather U3
The average annual temperature (u31)
Average annual precipitation (u32)
The average relative humidity (u33)
humidity (u34)
Vegetation coverage U4
NDVI (U41)
Soil erosion U5
Ratio of slope (U51)
Clear concentration of surface U6
Surface Cleanliness Index (u61)
（ ）
（ ）
（ ）
（ ）
3.
（ ）
（ ）
Applications of Neural Networks for the Environmental Quality Assessment of
Eco-Agriculture Tourism
3.1 Assessment Method
The characteristics of adaptability, learning ability and large-scale parallel computing power of Neural
network expert system is more suitable to solve the issues of incomplete information, more analysis
indicators, some non-linear related indicators issues that encountered in the environmental quality
assessment of Eco-Agriculture tourism. Many of the indicators can not be numerically defined, that is
there is no clear boundary, only the evaluation of the extent of the high and low, so a BP neural network
expert system provides an effective way for Eco-agriculture tourism environmental quality evaluation.
3.2 The basic principles of BP neural network
BP artificial neural network is a common classification of data mining. It is suitable for applying to the
network, using the form of the instructors’ training .It provides of input vector while providing output
vector. By adjusting the network's connection weight, the network output in the minimum mean square
sense is made closed to the desired output. The process of learning is composed by the positive direction
of propagation and back propagation. In the forward propagation process, the input neurons were
transported to the output layer after the processing by hidden neuron layer .If the output layer can not
get the expected output; it can enter the back propagation process. the error between expected output
and actual output can return along the original connection path, by modifying the neuron layers and the
connection weights, so that the error decreases, and then it can be transferred to a positive
communication process. The cycle repeated until the error is less than the given value. A typical 3-layer
BP artificial neural network model is shown in Figure I.
762
3.3 BP artificial neural network assessment model
Input and output: all the secondary analysis indicators were treated as input vector in this paper.
X=(H11 H12 H13 ⋯ H42 H43) To the environmental evaluation of travel as the output value of
Y. Input vector contains the quantitative indicators and qualitative indicators, as for the qualitative
indicators which can take the experts grade and other way to quantify. On the quantization of tourism
environmental quality level, the text takes an extent method, that is make the extent which contents the
travel environmental quality and the output value Y divided according to the table 2, in which 3A is the
highest level of quality tourism environment, c is the minimum level of quality tourism environment.
， ， ，， ， ，
Input layer
Hidden layer
Output layer
Figure.1 3-layer BP artificial neural network model
C
(0,0.1)
2B
(0.4,0.5)
Table 2 Ecological Agriculture grade range of quality tourism environment
2C
3C
B
(0.1,0.2)
(0.2,0.3)
(0.3,0.4)
3B
A
2A
3A
(0.5,0.6)
(0.6,0.7)
(0.7,0.8)
(0.8,0.9)
Network structure: the number of input layer neurons take in 14, corresponding to the input vector; the
output layer has a neuron; the determination of the hidden layer neuron number has no particularly good
way currently, the text takes the experience methods, taking the number of hidden layer was 38, so the
basic structure of the network is 14-38-1 3-layer BP neural network expert system. Neuronal function,
error function and learning algorithm: the input layer neurons functions f (x) = X, the input layer
neurons transmitted the input value which is not addressed to the hidden layer directly through the
weighted hidden layer neuron. The hidden layer and output layer neurons node function is Sig-moid
type functions: f (X) = 1 / (1 + exp (-x)), characterized by the function domain of real numbers, range
from (O, 1), and infinitely differentiable. Threshold of all neurons are taken to be 0, so that the weights
wk = (wijk) ni -1 ×ni. In the formula nk means the number of the k layer, wij is the weights between the
k-1 layer neuron i and the k-layer. Then the receiver value of the k-layer neuron j: netjk=Σi=1nk-1 ,j=1
2 ⋯, nk; to the k +1 level of output value), yi=f (netjk)j=1.2⋯.
，
，
3.4 The specific steps in environmental quality assessment
Step 1: initialize the neural network weights w and learning accuracy. Step 2: Determine the learning
samples x, Y. For each study sample, the input vector x is made up by the14 second class indicator of
Tourism Environmental Quality at a fixed composition. Qualitative indicators of these indicators should
be given a quantitative value score by experts. The desired output Y is given in Table 2, which can be
the middle value in the range. Step 3: Using learning samples in turn train the neural network until the
network becomes stable. Step 4: According to the environmental quality of tourism index system to
quantify the all secondary indicators of the city, according to a fixed order, constitutes the input vector x,
and the qualitative index is still quantized by the expert ratings. Step 5: To the trained neural network
763
input vector x, getting the network output Y. Step 6: According to Table 2, determine the range of the
output value Y. In accordance with the order to complete the six steps, you can come to a conclusion
that the environment quality of the eco-tourism belongs to which level in the range. So you can evaluate
and compare the different tourism environment.
4.
Conclusion
This paper develops a ecological agriculture tourism environment quality evaluation system, which
contains quality of atmospheric environment, water environment, climate and weather, vegetation cover,
soil erosion and the clean surface concentration, using BP neural network approach to evaluation,
implement the review quantitative criteria, in order to provide uniform objective indicators, overcome
subjective of decision-making, to further improve the Scientifics, justice and rationality of the city
environmental quality evaluation. It is worth noting that tourism environmental assessment including
assessment of the ecological environment, the social environment and economic environment evaluation.
The tourism has to rely on the local social environment, and therefore evaluation of the social
environment is also important. In the future the impact of the social environment on the ecological of
agricultural tourism should also be fully considered, make a comprehensive evaluation on the ecological
agriculture and tourism environment. By time and manpower implications, this study is not enough
intensive and perfected in many ways, more work needs to be done. In doing this evaluation, just
collected some of the major factors data, in the future should increase the acquisition of related factors
for more research, and increase other environmental factors on the monitoring and research, making
research results more complete and more convincing.
References
[1]. GIS and RS based on eco-environmental quality evaluation of agricultural tourism. Yunnan
Geographic Environment Research. 2008.09. P7-11.
[2]. Zhang Zijie, Zhou Fan. Biology and kinetics of activated sludge [M]. Beijing: China
Environmental Science Press, 1989.(in chinese)
[3]. Zhang group, Exposing first. Activated sludge models and processes of software development [J].
Environmental pollution control technology and equipment. 2001,2 (6): 384l
[4]. Pei-Li Lu, Dai-Jun, et al. Kinetic Model of Activated Sludge progress and prospects [J]. Chongqing
University. 2002,25 (3): 109 1 l14. (in chinese)
[5]. Ya-Lei Zhang, Yong-Mei Li, translation. Activated sludge model [M]. Shanghai: Tongji University
Press, 2002. (in chinese)
[6]. Henze M. Activated Sludge Model No. 1[A]. Scientific and Technieal Repo~No. 1[C]. London:
IAWPRC, 1987.
[7]. Henze M, et a1. Waste'water and biomass characterization for theActivated Sludge Model No 2:
biological phosphoms removal [J]. Wat. Sei. Tech.1995.31(2): l3-23.
[8]. Henze M, et a1. Activated Sludge Model No. 2d[J]. Wat. Sci. Tech, 1999. 39(1): 165—182.
[9]. Gujer W, et a1. Activated Sludge Model No. 3[J]. Wat. Sci. Tech, 1999, 39(1): 183—193.
[10]. Barker, P S, Dold, P L. COD and nitrogen mass balances in acti—vated sludge systems [J]. Wat.
Res, 1995, 29(2): 633-643.
[11]. Murnleitner E, Kuba T, Van Loosdrecht MCM, Heijnen JJ. An in—tegrated metabolic model for
the aerobic and denitrifying biologi—cal phosphorus removal process [J]. Biotech Bioeng. 1997.
54(5): 434-450.
[12]. Jian-E Zuo, Ling Xuefeng, Gu Xia sound. Anaerobic Digestion Model No. l (ADM1) Introduction
[J]. Environmental Science, 2003,16 (1) :57-61. (in Chinese)
．
764