ECOLOGICAL PROTECTION AND

ENVIRONMENTAL GOVERNANCE IN THE

ERA OF BIG DATA CORPORATE FINANCE

POLITICAL PERFORMANCE STUDIES

Xiaochuan Cao*

School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074,

China

cxiaoch2021@163.com

Yuhu Luo

School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074,

China

Reception: 21/03/2023 Acceptance: 06/05/2023 Publication: 28/06/2023

Suggested citation:

Cao, X. and Luo, Y. (2023). Ecological Protection and Environmental

Governance in the Era of Big Data Corporate Finance Political

Performance Studies. 3C Empresa. Investigación y pensamiento crítico,

12(2), 39-55. https://doi.org/10.17993/3cemp.2023.120252.39-55

https://doi.org/10.17993/3cemp.2023.120252.39-55

3C Empresa. Investigación y pensamiento crítico. ISSN: 2254-3376

Ed. 52 Iss.12 N.2 April - June, 2023

ABSTRACT

The theory of sustainable development based on ecological protection and

environmental governance places greater emphasis on the coordination between

ecological civilization and economic construction. In response to the contradiction

between economic development and ecological protection and environmental

governance. We combine big data processing and big data mining techniques to

conduct an in-depth study of ecological protection and environmental governance. In

addition, we focus on exploring the relationship between relevant corporate financial

performance and ecological protection and environmental governance. The results

show that our proposed ecological conservation and environmental governance

model has a maximum error of 2.37% and 1.27% in predicting ecological change and

environmental governance respectively. The improvement in ecological conservation

prediction is 63.72% and 65.93% respectively. In environmental governance, the

improvement is 11.6% and 14.47%. The corresponding corporate earnings can be

further increased by up to 37.81% and 41.36%. This shows that the adjustment of

corporate finance can effectively solve the fluctuation of earnings caused by

ecological protection and environmental management, and also promote the steady

growth of corporate earnings.

KEYWORDS

Ecological protection; environmental governance; economic construction; big data;

corporate finance

INDEX

ABSTRACT

KEYWORDS

1. INTRODUCTION

2. A FRAMEWORK FOR APPLYING BIG DATA FINANCIAL PERFORMANCE

ANALYSIS TO ECOLOGICAL PROTECTION AND ENVIRONMENTAL GOVERNANCE

ENTERPRISES

2.1. The general framework of the model

2.2. Ecological protection and environmental governance state network indicators

2.3. Accuracy of ecological conservation and environmental governance models

3. RESULTS AND DISCUSSION RELATED TO ECOLOGICAL PROTECTION AND

ENVIRONMENTAL GOVERNANCE

3.1. Impact of ecological protection and environmental governance indicators

3.2. Assessment and prediction of ecological conservation indicators

3.3. Assessment and prediction of environmental governance indicators

3.4. Corporate financial returns

4. CONCLUSION

REFERENCES

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1. INTRODUCTION

Nowadays, China's economic development has been remarkable and it has

become the second-largest economy in the world [1]. However, the rapid development

of China's economy [2, 3] has come at the expense of the environment [4], with

human activities, especially those of industrial enterprises, causing more damage to

the environment every year [5]. Therefore, it is urgent for environmental management

and ecological protection. Therefore, the task requirements should be to accelerate

green and low-carbon development, continuously improve the quality of the

environment, enhance the quality and stability of the ecosystem, and comprehensively

improve the efficiency of resource use. At present, the construction of ecological

civilization has gradually made positive progress [7, 8]. The rough and fast-growing

economy needs to be transformed into a green and low-carbon sustainable

development model [9, 10]. China is currently accelerating the process of

environmental pollution control [11], while more stringent regulation of heavily polluting

enterprises is being implemented. In the process of ecological protection and

environmental management, to enable healthy, stable, and sustainable economic

development [12], it is also necessary to take into account the environmental carrying

capacity when society conducts economic behavior. We also need to consider the

impact of environmental governance on business finances. We, therefore, need to

establish a virtuous ecosystem and take a good ecological path in economic

development, we must insist on putting the ecological environment before economic

benefits while considering the benefits to the enterprise and dealing with the

harmonious relationship between the ecology and the enterprise. We cannot let

environmental management and ecological protection lead to an increase in the risk

factor of enterprises and affect their development. What we should do now is to

change the initial concept of economic development and use ecology and economics

to combine the two concepts to explore methods and paths that can solve the

problems of environmental governance, ecological protection, and economic

development.

Due to the promotion of ecological protection and environmental management,

various research scholars have contributed their ideas. It is hoped that ways can be

found for environmental and ecological development and economic development of

enterprises. New approaches to environmental governance can help to mitigate

adverse socio-economic and ecological impacts. Broadbent, E.N [13] develops CoP-L

on tools and strategies to improve infrastructure governance that can be used as a

mechanism. Their research promotes learning and action on factors related to

governance effectiveness. In addition, they used mixed methods [14, 15] to explore

textual analysis and regional multi-iterative discussions with stakeholders. Zuo, L [16]

argue that understanding the relationships between ecosystem services and exploring

their drivers is necessary for effective ecosystem management. They quantified four

factors: soil conservation, water production, net primary productivity, and habitat

quality [17, 18]. Ecological priority conservation areas and ecological priority

restoration areas are then identified, which facilitates targeted conservation. In terms

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of corporate ecological protection, micro-enterprises with profit-seeking characteristics

have not developed sufficient motivation for environmental governance. hu, J [19]

proposed that environmental protection departments carry out environmental

regulation and their strength in enforcing regulations has an important impact on

corporate environmental governance. wang, X [20] proposed an environmental

monitoring system based on a ZigBee wireless sensor network. The system consists

of a wireless monitoring network and a remote PC to achieve real-time remote

monitoring of environmental information such as temperature and humidity, light

intensity, rainfall, etc. Lu, S [21] looked at the legal system and established a

corresponding ecological civilization system by legal norms, which has a positive

effect on promoting environmental protection. They also focus on the current situation

of China's ecological environment [22, 23], analyze its problems, and propose

corresponding solutions in light of the problems. Guan, Y [24] combine the current

requirements of China's ecological environmental protection. They introduced the

macro background of the development of social organizations for environmental

protection in China in terms of policies and regulations, material support, and

propaganda guidance, and further analyzed the existing problems. Wu, M [25]

conducted an in-depth discussion on the relationship between the economy,

resources, and environment in the Greater Bay Area of China. The relationship

between the green economy and the carrying capacity of resources and the

environment in the Greater Bay Area is analyzed. By constructing a comprehensive

economic-resource-environment index system, the entropy weighting method is used

to calculate the index weights. They argue that the coordination of the economic-

resource-environment system in China's Greater Bay Area is currently increasing and

that economic development is moving towards high resource-carrying capacity and

high environmental carrying capacity. Mazzanti, M [26] Their research questions cover

everything from economic and financial performance to innovation adoption, to

circular economy implementation and environmental protection. In addition in applying

clustering techniques [27, 28] to better design and target policy tools for circular

economy, environmental protection, and eco-innovation in areas related to ecological/

sustainability transition. Nowadays, due to the spread of information technology,

computer network computing has developed [29, 30]. The processing of various

complex problems through big data has also received increased attention. Fu-sheng

[31] drew on the international BOT model to construct urban big data based on next-

generation information technology such as artificial intelligence, cloud computing, and

the Internet of Things to help the ecological construction of smart cities. Chen, F [32]

used big data as a research context to construct a rural agroecological system

ecological based on complex systems theory The study was based on the complex

system theory to build an ecological management system for rural agricultural

ecosystems. Among the many research scholars mentioned above on ecological

protection and environmental quality, they have studied various aspects from the

perspective of laws and regulations, ecological service system relationships, and

artificial intelligence. In addition to the purely ecological influences and related

governance methods, economic orientation has a great influence on ecological

protection and environmental governance. In particular, with the rapid development of

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information technology, it is essential to analyze the relationship between ecological

conservation, environmental governance, and related corporate finance based on big

data.

The theory of sustainable development based on ecological protection and

environmental governance places greater emphasis on the coordination between

ecological civilization and economic construction. This research plays a guiding role in

the construction and development of ecological protection and governance. The

results of the research are conducive to promoting the common progress of the

environment, economy, and society. Therefore, we combine big data processing and

big data mining technology to conduct in-depth research on ecological protection and

environmental governance. In addition, we focus on exploring the relationship

between relevant corporate financial performance and ecological protection and

environmental governance. It is a win-win situation for enterprises if they can maintain

a healthy and stable growth of their revenue in the process of ecological protection

and environmental management.

2. A FRAMEWORK FOR APPLYING BIG DATA

FINANCIAL PERFORMANCE ANALYSIS TO

ECOLOGICAL PROTECTION AND ENVIRONMENTAL

GOVERNANCE ENTERPRISES

In the context of the big data era, the establishment of a big data analysis platform

for ecological protection and environmental governance enterprises enables the

collection and acquisition of financial and performance information for ecological

protection and environmental governance enterprises in real time. Through the pre-set

ecological protection and environmental governance logic language of the financial

analysts, the report output performance end is fed back and the output data is

processed to derive the important information required by the various departments

and management of the ecological protection and environmental governance

enterprise in real-time.

This paper uses a proposed method based on the output of financial and

performance information from the ecological conservation and environmental

governance state network to predict the time series generated by different

environmental systems. The results conclude that the performance of the state

network with ecological protection and environmental governance is reliable.

2.1. THE GENERAL FRAMEWORK OF THE MODEL

Ecological conservation and environmental management state networks are

artificial recurrent neural networks that remain active even in the absence of relevant

environmental data. This is shown in Figure 1.

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Figure 1. Model diagram of the ecological protection and environmental governance state

network.

The ecological protection and environmental governance state network consists of

a front-end input layer, an intermediate reserve pool, and an output layer, whose

corresponding input vectors, state connection vectors, and output vectors can be

expressed as follows.

(1)

(2)

(3)

Among them, is a dimensional input vector; is a dimensional state

continuum vector; and is a dimensional output vector. At sampling time , the

state equation update and the financial and performance information output equation

of the ecological protection and environmental governance state network are shown

below.

(4)

(5)

Where the weight ratio within the reserve pool is a dimensional matrix, the

weight ratio at the input layer is a dimensional matrix, and the from

the financial and performance information output layer and then the feedback

connection is a dimensional matrix of warrant ratios. is the noise vector and

the hyperbolic tangent is used as the activation function in this paper. In equation (5),

which is the output equation of the single output network, the weight ratio of the

output financial and performance information is a dimensional matrix. is the

financial and performance information output of the ecological protection and

environmental governance state network. is composed of the hyperbolic tangent

activation function and the weight ratio of the output financial and performance

u(n)=(u1(n), u2(n), …, uk(n))T

x(n)=(x1(n), x2(n), …, xr(n))T

)=(

), …,

))T

u(n)

x(n)

y(n)

(n+ 1) = tanh

(

Winu(n+1)+Wx(n)+W

back

y(n)+v(n)

)

y(n+ 1) = Wout x(n+ 1)

r×r

Win

r×k

Wback

r×l

v(n)

Wout

l×r

y(n)

u(n)

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information after passing the training. The network is continuously activated even in

the absence of relevant environmental data.

The main component of the ecological conservation and environmental

management state network is the use of a large-scale stochastic sparse reserve pool

as the relevant environmental data processing medium. After processing the

environmental data input signals are mapped from a low-dimensional input space to a

high-dimensional state space. The network is eventually trained in the high-

dimensional state space using linear regression methods for partial connection weight

ratios.

2.2. ECOLOGICAL PROTECTION AND ENVIRONMENTAL

GOVERNANCE STATE NETWORK INDICATORS

This subsection first gives definitions of the relevant ecological conservation and

environmental management state network indicators, including definitions of

prediction steps, sparsity, energy loss (energy consumption), energy efficiency

(energy efficiency), and contribution.

1. The number of prediction steps is the minimum number of steps at a moment

in time. This is described as follows:

(6)

where are the values of the signal sequence at moment

and is the output value of the corresponding prediction sequence at

moment . reflects the predictive performance of the ecological conservation and

environmental management state network.

2. Sparsity is a connection probability between the neurons in the reserve pool

and the financial and political performance information output neurons. This is

described as follows.

(7)

where denotes the number of dormant synapses in the conservation and

environmental governance state network and denotes the number of all tunable

synapses in the ecological conservation and environmental governance state network.

3. Energy loss is the total energy loss of the output synapses activated in the

ecological conservation and environmental management state network. This is

calculated as follows.

predict

(n)−y

original

(n)

yoriginal

⩽

Δ= 0.001,yoriginal(n)

ypredict(n)

(N−S)

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(8)

where is a matrix of weights between the

connecting financial and

performance information output neurons.

(4) Energy efficiency is the energy loss per unit corresponding to the predicted

number of steps in the ecological protection and environmental management state

network. This is calculated as follows.

(9)

2.3. ACCURACY OF ECOLOGICAL CONSERVATION AND

ENVIRONMENTAL GOVERNANCE MODELS

This section discusses the comparison of the outputs derived from the ecological

conservation and environmental management state network predictions with the

experimental results. In Figure 2 the horizontal coordinates indicate the number of

prediction steps and the vertical coordinates indicate the accuracy of the predicted

values. In this paper, the number of prediction steps is set to 20, 40, 60, 80, and 100

for comparison. It can be seen that as the number of prediction steps increases, the

prediction accuracy of the network model increases. When the number of prediction

steps is 40, the model prediction accuracy can reach 95.61%. When the number of

prediction steps reaches 100, the model prediction accuracy is 97.45%, which is only

a 1.84% increase in prediction accuracy. At the same time, the network will increase

the computational cost as the number of prediction steps increases. Therefore, 40 is

chosen as the number of prediction steps for the network iteration in this paper.

∑

i=1

(Wout

Wout

steps

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Figure 2. Plot of the number of ecological protection and environmental management state

network prediction steps versus prediction accuracy.

3. RESULTS AND DISCUSSION RELATED TO

ECOLOGICAL PROTECTION AND ENVIRONMENTAL

GOVERNANCE

Currently, some large and medium-sized energy companies in the Chinese energy

industry are facing trade-off decisions and constraints between the dilemma of

ecological protection and environmental treatment and energy production. The needs

in terms of energy production, ecological protection, and environmental treatment all

need to be assessed through the indicators of an ecological and environmental

protection enterprise. However, there are enormous tests in the area of environmental

management and ecological protection, and it is, therefore, necessary to make a

targeted analysis of the financial situation of ecological protection and environmental

management companies and the corresponding performance results. The problems

faced by companies in the field of ecological protection and environmental

management are (1) a lack of awareness of ecological protection among the

population and (2) insufficient investment in the ecological economy and research and

development by the companies themselves. Research on environmental

management, pollution treatment, and sustainable development has been relatively

in-depth or at the application R&D stage in previous years and needs to be further

assessed from the application environment; (3) In recent years, with the domestic

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economy, especially in some of the faster-growing regions, the development of

research, development and application environment in ecological protection and

environmental management has been full of vitality and vigor. However, in the rapid

economic development, pollution problems in various industries have become more

and more prominent. The current market environment for ecological protection and

environmental management enterprises in the new era is undergoing the pressure of

social opinion, means of publicity, innovation in business methods, and the combined

impact of energy efficiency and environmental conditions. At the same time, the

development and innovation of various big data technologies are gradually influencing

the methods of financial analysis, analyzing and predicting the future development

from the financial situation of the business community. The purpose of this is to serve

the wider ecological and environmental management business community. In turn, it

provides further policy and economic guidance to enterprises. It also guides the future

of ecological protection and environmental management in China.

3.1. IMPACT OF ECOLOGICAL PROTECTION AND

ENVIRONMENTAL GOVERNANCE INDICATORS

For this purpose, we collected information related to the financial performance of

companies regarding ecological protection and environmental management from

2016-2020 and used an artificial recurrent neural network (ANN) to make non-linear

predictions of the categorical data. One of the data sources was collected using a city

in Guangdong Province, China as the base database. The input parameters include

forest conservation indicators, water conservation indicators, air quality indicators, and

pollutant and waste treatment indicators. For the output parameters, we used

comprehensive evaluation indicators, which were set up as ecological protection

indicators and environmental management indicators. In Table 1, we summarise the

annual average forest protection indicators, water resource protection indicators, air

quality indicators, and pollutant and waste treatment indicators for a municipality for

the five years 2016-2020. It is observed that there is a huge crisis in ecological

protection indicators as well as environmental governance in a city in Guangdong

Province during the period 2016-2017. The figures for the area covered by forests, the

total water reserves, and the overall air quality index decreased by 23.25%, 15.70%,

and 26.87% respectively. This shows that the regulation of ecological protection is in

great danger. The combination of massive illegal or unsustainable tree felling, water

wastage, soil erosion, and pollution with the emission of harmful or greenhouse gases

such as CO2

has led to a simultaneous decline in the forest environment, water

environment, and air quality. In addition, it was observed that the number of pollutant

and waste treatment plants, which should be treated as pollutant emissions, did not

increase significantly; the number of pollutant and waste treatment plants only

increased by 5.8% between 2016 and 2017, which is far from enough to address a

large number of ecological protection and environmental management issues and

gaps during the period. As a result, there were huge ecological problems during this

period. In the period 2017-2020, however, the significant development and promotion

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of ecological protection and environmental management enterprises and the related

technological advances and developments have led to a significant improvement in all

indicator parameters. The area covered by forests will increase by 5.62%, 10.88%,

and 16.43% in the period 2018-2020 compared to the figures for 2017. Total water

reserves have increased by 4.48%, 8.47%, and 12.26% year-on-year. The combined

air quality index increased by 6.12%, 14.29% as well as 18.37% year-on-year. The

number of pollutants and waste treatment plants increased by 28.125%, 55.80%, and

63.39% year-on-year.

Table 1. Annual average indicator data for a city in Guangdong Province for 2016-2020

3.2. ASSESSMENT AND PREDICTION OF ECOLOGICAL

CONSERVATION INDICATORS

In the process of ecological protection, the number of ecological protection

indicators can clearly show how effective it is for ecological protection. Therefore, we

have collected the ecological protection index between 2016 and 2020 and analyzed

the index for these years using our proposed ecological protection and environmental

governance model. As shown in Figure 3, in the actual ecological protection index, the

figures for 2016 to 2022 are 0.557,0.313,0.361,0.397 and 0.431 respectively. the

predicted figures in our proposed ecological protection and environmental governance

model are 0.562,0.317,0.359,0.394 and 0.421 respectively. the maximum fluctuation

values are below 0.01, and the maximum error is within 2.37%, which indicates that

our proposed model has good accuracy. In addition, we have used the Ecological

Conservation and Environmental Management model to predict the Ecological

Conservation Index for subsequent years. According to our predictions, in 2024 and

2025, the relevant indices reach 0.519 and 0.526, an increase of 63.72% and 65.93%

compared to 0.317 in 2017. This indicates that after 2017, China's commitment to

ecological protection has become more and more powerful. China is not pursuing

pure economic growth, they are building their economy while paying more and more

attention to the ecological protection of the country. Strengthening ecological

protection is conducive to strengthening China's green and low-carbon science and

technology innovation, and sustaining the growth of green and low-carbon industries.

This will be conducive to the formation of new green economic dynamics and

sustainable growth poles. It will significantly improve the quality and efficiency of

Year 2016 2017 2018 2019 2020

Forest cover (in million hectares) 56.14 43.09 45.51 47.78 50.17

Total water reserves (in billions of cubic metres) 37.83 31.89 33.32 34.59 35.80

Air Quality Composite Index (0-1) 0.67 0.49 0.52 0.56 0.58

Pollutants and waste treatment plants 211 224 287 349 366

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economic and social development, and provide a strong impetus for China to build a

strong socialist modern state comprehensively.

Figure 3. Assessment and prediction maps for ecological conservation indicators

3.3. ASSESSMENT AND PREDICTION OF

ENVIRONMENTAL GOVERNANCE INDICATORS

China's fight against environmental pollution is of great theoretical and practical

significance in achieving sustainable economic development, building a moderately

prosperous society, and ultimately realizing the overall harmony of human society. It is

conducive to the sustainable development of China's economy. When building an

economy, there is a need to establish a way of development that meets the

development needs of the present without compromising the ability of future

generations to meet their needs. China is a developing country and the biggest

problem it faces is developing its economy, which depends on the environment and

resources to support it. The state of environmental governance is conducive to

building a moderately prosperous society in all aspects. In the previous decades,

China's rapid economic development had caused serious environmental pollution.

Environmental pollution has become a major public hazard today. The Chinese

government's efforts to manage the environment, properly manage the relationship

between the economy and the environment, and manage the environment and protect

the environment will provide an important foundation and prerequisite for China to

build a moderately prosperous society and is a strong guarantee for China to achieve

moderately prosperous for all people at an early date. Therefore, we have conducted

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an in-depth discussion on China's environmental governance, reflecting the extent of

China's environmental governance through the environmental governance indicator

factor. In Figure 4, we present the environmental governance factors for China

between 2016 and 2020 and compare them with the results predicted by our

proposed ecological conservation and environmental governance model. We can see

that the actual environmental governance factors are 0.513,0.519,0.532,0.537 and

0.558 respectively, with environmental governance showing a steady and slow

increase. The model predicts governance factors of 0.512, 0.518, 0.529, 0.534, and

0.551 for the period 2016 to 2020, with a maximum fluctuation of 0.007 or 1.27%

compared to the actual values. This is mainly due to several factors in the

environmental management process, including relevant laws and regulations, the

enforcement efforts of law enforcement officers, and some local environmental

influences. By forecasting the environmental governance in 2024 and 2025, the

relevant factors are large 0.586 and 0.593. Compared with 2017, the steady increase

of 11.6% and 14.47% indicates that environmental governance is steadily

progressing.

Figure 4. Assessment and prediction of environmental governance indicators

3.4. CORPORATE FINANCIAL RETURNS

Corporate finance needs to help decision-makers make the right judgment on the

market based on the data provided by the finance department so that the company

can grasp the right business direction in the market, develop steadily and stay in the

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invincible position. The focus of finance in an enterprise varies with the stage of

development of the enterprise. To verify the impact of ecological protection and

environmental management on corporate earnings, we track the earnings of a

particular enterprise. As can be seen in Figure 5, between 2016 and 2020, the actual

annual earnings growth of the enterprise is at 3.58%, 3.66%, 3.98%, 4.07%, and

4.14%. In our proposed model, the corresponding economic growth is 3.6%, 3.65%,

3.95%, 4.1%, and 4.12%. In addition, we forecast economic returns for the coming

years, which are expected to grow by 5.03% and 5.16% in the years 2024 and 2025.

This indicates that there will be no impact on the company's finances when it comes

to ecological and environmental management. The corresponding increase in revenue

could be as high as 37.81% and 41.36%. This shows that the adjustment of corporate

finance can effectively solve the fluctuation of earnings caused by ecological

protection and environmental management, and can also promote the steady growth

of corporate earnings.

Figure 5. Graph of growth in corporate financial returns

4. CONCLUSION

Ecological protection and environmental management have a very significant and

positive role to play in promoting sustainable development in China. In the process of

ecological protection and environmental management, maintaining the economic

growth of the enterprise according to specific circumstances is also a necessary

environment for the development process. In business, finance permeates every

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aspect of business management, and all business management activities are

ultimately reflected in financial data. These data can expose the loopholes and

weaknesses in business management and provide early warning for the prevention of

business risks. In the article, we combine big data technology for financial analysis to

analyze and predict the future direction of development from the financial and fiscal

status of the enterprise group. This is intended to provide further policy as well as

economic guidance to the larger ecological conservation and environmental

management business group. The findings of the study are as follows.

We used an artificial recurrent neural network (ANN) to make non-linear

predictions of categorical data and summarised the data for a city's average

annual forest conservation indicators, water conservation indicators, air quality

indicators, and pollutant and waste treatment indicators for the five years

2016-2020. The results show a 23.25%, 15.70%, and 26.87% reduction in the

total water reserves and air quality composite index respectively.

In the assessment and prediction of ecological protection and environmental

management indicators, our proposed ecological protection and environmental

management model has a maximum error of 2.37% and 1.27% in the

prediction of ecological change and environmental management. This indicates

that our model has good accuracy. It also improves 63.72% and 65.93% in

ecological conservation prediction and 11.6% and 14.47% in environmental

governance, respectively. It shows that our ecological protection and

environmental governance are steadily progressing.

3. In carrying out ecological protection and environmental management, it is vital

to ensure that companies earnings. In our forecasts, the corresponding

corporate earnings can be further increased by 37.81% and 41.36%. This

shows that the adjustment of corporate finance can effectively solve the

fluctuation of earnings caused by ecological protection and environmental

management, and also promote the steady growth of corporate earnings.

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