# Structure Optimization of e-Commerce Platform Based on Artificial Intelligence and Blockchain Technology

Authors: Shengqi Li
Journal: Wireless Communications and Mobile Computing
 (2020)

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## Abstract

The current e-commerce operation model has network defects such as network chaos and uneven network distribution, which affect economic development and progress. In response to the above problems, this article introduces the artificial intelligence system, optimizes and analyzes the structure of e-commerce websites, and combines the Internet economy with online website theory through independent screening and analysis of the artificial intelligence system. The concept of blockchain technology is introduced, and the characteristics of blockchain are analyzed through theory and data using quantitative analysis methods, and the problem of cross-border electronic payment is solved based on blockchain. Based on the analysis of artificial intelligence, an optimized online website innovation plan was obtained. Finally, the online website resource allocation variables are simulated, and the simulation method is used to test the scheme. The simulation test simulates the process of resource allocation, optimizes the use of innovative models, and hires professional financial personnel to observe records. The test verifies the effectiveness of the structure optimization of the e-commerce platform realized in this paper.


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## Body

## 1. Introduction

In the past century, using Internet economic theory to analyze e-commerce websites is an important channel analysis approach [1]. On the basis of the Internet economy, the analysis of various programs can extend the benefit of the selected scheme to the best state [2]. However, the theory is fixed, and it cannot be in the special circumstances of human judgment, make decisions sometimes with the reality of deviation, and need to be supplemented by the artificial intelligence system [3]. Through the auxiliary judgment of the artificial intelligence system, strengthening the integration of the optimization scheme of e-commerce structure can make greater progress on the original foundation [4]. The rational operation is one of the common concepts of the internet economy and artificial intelligence system, which integrates probability, efficiency, and inference to consolidate the rigor of decision in the process of artificial intelligence [5]. Nowadays, in the labor market, the implementation of online Web site is not as satisfactory, and the reason is that people cannot be doped to the decision-making stage and cannot achieve the “human-oriented” approach to development. In order to make up for the defects of this aspect, the system model of the artificial intelligence system and electronic commerce is born, and both of them reach the innovative optimization plan, which has a very reliable practical basis [6].The research contributions made in this paper mainly include the following aspects:(1)
The paper proposes an e-commerce website structure of an artificial intelligence system(2)
It is proposed to combine the Internet economy with online website theory through independent screening and analysis of the artificial intelligence system(3)
The method of quantitative analysis is used to analyze the characteristics of the blockchain through theory and data, and the problem of cross-border electronic payment is solved based on the blockchainThe rest of this paper is organized as follows. Section2 discusses related work, followed by the method which is discussed in Section 3. Result analysis and discussion is discussed in Section 4. Section 5 concludes the paper with summary and future research directions.


## 2. Related Work

Blockchain technology has laid a new foundation and direction for supply chain governance. An efficient and reliable global information transmission system will inevitably require a matching efficient and reliable value transmission system, which is the foundation of the prosperity of the blockchain. Blockchain uses cryptography to realize mutual distrust of distributed systems to reach consensus based on agreements without manual intervention. As one of the major technological breakthroughs in the last ten years, the blockchain is essentially a distributed consensus mechanism that realizes the value consensus between devices without manual intervention. This is the blockchain 1.0 technology represented by the Bitcoin network. Later, the Turing virtual machine was further implemented on this basis, and the blockchain 2.0 technology that supports smart contracts represented by Ethereum appeared. Currently, the blockchain technology 3.0 that supports large-scale enterprise-level applications is also under development.The e-commerce website structure determines the development direction of the internet economy to a certain extent and needs to construct a set of feasible structure optimization driving strategy for it [7]. Offline Web site theory to express the position lies in the social hard demand, cannot stand in the public perspective of decision-making, and need to fully expose the participants to demand and supply and demand information, on the basis of online Web site allocation which cannot get the real demands of participants [8]. The goal of optimizing the structure is to have a “people-oriented” policy, reasonable according to the demands of participants to collect, and achievement of a sustainable development of a strategic approach.Optimizing Innovation Mexico’s Basic Law adopts the policy of “people-oriented”, and the reliability of the analysis process can be ensured by using the optimization innovation model. At the same time, this paper also takes the optimization of the innovation system for business structure detection, for the test process encountered in the scope of the improvement of the general forecast, in the analysis of problems before the issue of the overall control [9]. In order to achieve complete accuracy, it is necessary to design and deal with the hidden layer, analyze and divide it by computer technology, and then input the required content data into it to ensure the smooth operation of the whole optimization innovation system [10].


## 3. Method

### 3.1. Optimize the Innovation Model to Build

In the beginning of the optimization innovation model, it will be advantageous for the next step to carry out the theory analysis procedure for the integration of a series of lifting space in the field of online Web resource allocation [11]. Through the current online site, a series of operational problems, distribution conflicts, and other information input into the computer system, and the use of systematic screening compressed into the data packet into the artificial intelligence, screening, and lifting operations [12]. In which the integrated retrieval link to carry out the implementation of online Web site allocation strategy, the intelligent model is computed using the computer algorithm, the information data is input into the theory analysis system according to the indication standard of each algorithm, and the model receives the data to digest processing and finally completes the construction of the whole collection model [13].In this process, using the auxiliary function of the computer system, first through the operation of artificial intelligence, get the theory analysis scheme; use the computer-specific code to classify the theory analysis scheme data, in order to provide the precondition for the next work development [14, 15]. Then, based on the theoretical analysis of the scheme coding, online Web site resource allocation optimization strategy, we will be as p theoretical analysis of the branch of the project coefficient, α for e-commerce Web site innovation optimization coefficient, bme represents the feasibility of innovative solutions, and δ as an optimization coefficient, through the following equation of the computations. The integration coefficient of the data of the e-commerce optimization scheme is obtained [16, 17]:
(1)pi=bmebδ2α1bpo=α1−bmebδ0.5bmebα1.In this formula, taking into account the reliability of the classification integration coefficient, we will continue to optimize the innovation model of the various aspects of error retrieval, to ensure the accuracy of resource allocation model, in this process using the set algorithm to organize, the independent number into the algorithm, the use of computer systems automatically integrated, and output results. The accuracy is represented by 1 and 0, respectively, of which 1 is accurate, and 0 is the error [18]. In the operation process, we use ψ to represent the number of the checked algorithm in the system. With these algorithms entered into the overall frame structure, the computer system automatically numbered every computation process [19]. In addition, M and I on behalf of its theoretical analysis of the performance of the node and the feasibility of the coefficient, y represents the e-commerce optimization coefficient and inserts the above model that is to ensure the optimization of the operating efficiency of the innovation model, but also to the formula to run the process of protection, which the inspection process as shown [20, 21]:
(2)My1=I1y1I1/y1+I2/y2×My.After guaranteeing the accuracy, finally, to determine the final solution, using the optimal screening algorithm, where the nextF is the optimal node coefficient, b represents the deviation coefficient, and s represents the section of the theoretical analysis scheme of the link variable range, through the control of the optimal value coefficient to build the optimal information acquisition mechanism [22]. Considering that the maximum stress amplitude of amplitude fatigue can be used as the best form, the optimal point position control is adopted in this form, and then the theoretical analysis system is further perfected. Theoretical analysis of the resource allocation control system the filter formula is as follows [23]:
(3)Ff=∑in=1bn+sn∑s0.5.The acquisition of an optimized filtering algorithm represents the optimization of the operation of the model of reliability, and the reason is that this article built the algorithm process that is a layer by the step test mode, that is, the previous algorithm cannot determine the accuracy of further operations; therefore, after the optimization of the selection algorithm to draw conclusions, the conclusion must be reliable and feasible [24, 25]. After the optimization coefficient has been obtained, the role of automatic selection of the optimal online transaction is played out, and the next step is to output it to the user view page, as shown in Figure 1 [26].Figure 1
Innovation model and algorithm of e-commerce website structure optimization.


### 3.2. Optimization Scheme of e-Commerce Resource Allocation

After the optimized innovation model is completed, the optimization model of e-commerce resource allocation optimization is integrated. In the process of overlap, it is necessary to consider the commonality of the system, that is, whether the optimal innovation scheme can be combined with the computer algorithm to the highest degree, so that the design and operation results are matched [27]. In the process of project design and output, the staffs need to carry on the information recording work in time, the information entry of the e-commerce innovation structure is guaranteed to the maximum degree, and the accuracy of input analysis information is ensured [28]. Secondly, the analysis of the data processing is the main need to complete the online Web site resource allocation of inefficient information integration, through the algorithm to effectively deal with, in all aspects of consensus, to achieve the smooth operation of each algorithm for the operation of various algorithms to provide protection [29, 30]. Finally, from the output of the innovative optimization program directly into the resource allocation system, the algorithm collected online Web site resource allocation content and online Web site resource allocation requirements, together with the display in the user view page. During the lap up process, part of the lap is randomly selected, as shown in Table 1 [31].Table 1
Algorithm of e-commerce website structure optimization.
Information integration phaseOptimal innovation modelAccuracy rateResonant adjustmentEfficiencyOverall effectRemarks10.930.940.9492.2%20.870.970.9696.2%30.980.890.9893.1%40.910.830.9096.6%As shown in Table1, in the lap stage of the theoretical analysis scheme, using f to represent the model total data algorithm, using x,y to represent the standard data of the material model, this algorithm adds a set of models to ensure objectivity in the information integration stage. To ensure the accuracy of the results, we need to reduce the error of the algorithm [32]. This part of the design first through f to build a corresponding probability calculation, in the input of the corresponding training algorithm, and get an optimized result Y. The formula used in the model is as follows [33]:
(4)f=−1+x′2−x222−1+∑yi.By using this formula, we can get the optimization scheme of the optimization innovation model online resource allocation reform and take the value of the fitting to further operation, in which thepcl represents the optimal coefficient, u represents the standard coefficient, and y represents the set of optimization coefficients. The calculated value is the optimal innovation coefficient in the resource allocation mode of online Web site, in order to make the final calculation basis [34, 35].
(5)pcl=∑ui2+yi+ui0.5y0.8−2yiui.The above results provide the basis for the final step to obtain output instructions for the matting, through the centralized operation of all functions and finally obtain an output value, using artificial intelligence operation. The nextN type represents the e-commerce platform optimization coefficient, ϕxA represents the structure optimization strategy representing the value, λxWx represents the innovation development value of the algorithm, the βmx represents the electric quotient model label, and the f represents the innovation structure coefficient, uses these data to establish the corresponding function relation, and obtains the corresponding difference value sequence. If the corresponding classification problem is encountered, we can take the aggregate function, assuming the f value between the region (-1, 1), and the output function is [35]:
(6)NϕxA+βmxMxλxWx1−0.8N/NxWx≤f.After the optimal numerical value is determined, we aim at our hypothetical algorithmS and the theoretical analysis of all the algorithm outputs between scheme A; according to a series of optimal numerical values, we integrate them into the optimization innovation model, calculate the corresponding joint probability, and obtain the optimal scheme determining coefficient, and the specific running process is shown in Figure 2.Figure 2
Innovation model and algorithm of e-commerce website structure optimization.Through the arrangement of the optimization scheme on online Web site resource allocation, we can get the big analysis direction, carry out the reliability support provided by artificial intelligence, implement the optimization scheme of online website resource allocation, and get the final result of the theoretical analysis and optimization scheme. In this process, the theoretical analysis scheme framework as the intermediate cohesion, its design precision requirements must meet the construction principle of the algorithm to ensure the accuracy of the calculation process. Finally, the end of this link, the theoretical analysis of the optimization index collection is through the computer technology to the optimal solution number, and in this process, through the artificial intelligence formula calculation, the concentration of theoretical analysis system of the blind spot, and the use of theoretical analysis system for the management of resource allocation scheme data classification. The design of the optimization innovation scheme of the e-commerce website resource allocation is accomplished by automatic regularization.


## 3.1. Optimize the Innovation Model to Build

In the beginning of the optimization innovation model, it will be advantageous for the next step to carry out the theory analysis procedure for the integration of a series of lifting space in the field of online Web resource allocation [11]. Through the current online site, a series of operational problems, distribution conflicts, and other information input into the computer system, and the use of systematic screening compressed into the data packet into the artificial intelligence, screening, and lifting operations [12]. In which the integrated retrieval link to carry out the implementation of online Web site allocation strategy, the intelligent model is computed using the computer algorithm, the information data is input into the theory analysis system according to the indication standard of each algorithm, and the model receives the data to digest processing and finally completes the construction of the whole collection model [13].In this process, using the auxiliary function of the computer system, first through the operation of artificial intelligence, get the theory analysis scheme; use the computer-specific code to classify the theory analysis scheme data, in order to provide the precondition for the next work development [14, 15]. Then, based on the theoretical analysis of the scheme coding, online Web site resource allocation optimization strategy, we will be as p theoretical analysis of the branch of the project coefficient, α for e-commerce Web site innovation optimization coefficient, bme represents the feasibility of innovative solutions, and δ as an optimization coefficient, through the following equation of the computations. The integration coefficient of the data of the e-commerce optimization scheme is obtained [16, 17]:
(1)pi=bmebδ2α1bpo=α1−bmebδ0.5bmebα1.In this formula, taking into account the reliability of the classification integration coefficient, we will continue to optimize the innovation model of the various aspects of error retrieval, to ensure the accuracy of resource allocation model, in this process using the set algorithm to organize, the independent number into the algorithm, the use of computer systems automatically integrated, and output results. The accuracy is represented by 1 and 0, respectively, of which 1 is accurate, and 0 is the error [18]. In the operation process, we use ψ to represent the number of the checked algorithm in the system. With these algorithms entered into the overall frame structure, the computer system automatically numbered every computation process [19]. In addition, M and I on behalf of its theoretical analysis of the performance of the node and the feasibility of the coefficient, y represents the e-commerce optimization coefficient and inserts the above model that is to ensure the optimization of the operating efficiency of the innovation model, but also to the formula to run the process of protection, which the inspection process as shown [20, 21]:
(2)My1=I1y1I1/y1+I2/y2×My.After guaranteeing the accuracy, finally, to determine the final solution, using the optimal screening algorithm, where the nextF is the optimal node coefficient, b represents the deviation coefficient, and s represents the section of the theoretical analysis scheme of the link variable range, through the control of the optimal value coefficient to build the optimal information acquisition mechanism [22]. Considering that the maximum stress amplitude of amplitude fatigue can be used as the best form, the optimal point position control is adopted in this form, and then the theoretical analysis system is further perfected. Theoretical analysis of the resource allocation control system the filter formula is as follows [23]:
(3)Ff=∑in=1bn+sn∑s0.5.The acquisition of an optimized filtering algorithm represents the optimization of the operation of the model of reliability, and the reason is that this article built the algorithm process that is a layer by the step test mode, that is, the previous algorithm cannot determine the accuracy of further operations; therefore, after the optimization of the selection algorithm to draw conclusions, the conclusion must be reliable and feasible [24, 25]. After the optimization coefficient has been obtained, the role of automatic selection of the optimal online transaction is played out, and the next step is to output it to the user view page, as shown in Figure 1 [26].Figure 1
Innovation model and algorithm of e-commerce website structure optimization.


## 3.2. Optimization Scheme of e-Commerce Resource Allocation

After the optimized innovation model is completed, the optimization model of e-commerce resource allocation optimization is integrated. In the process of overlap, it is necessary to consider the commonality of the system, that is, whether the optimal innovation scheme can be combined with the computer algorithm to the highest degree, so that the design and operation results are matched [27]. In the process of project design and output, the staffs need to carry on the information recording work in time, the information entry of the e-commerce innovation structure is guaranteed to the maximum degree, and the accuracy of input analysis information is ensured [28]. Secondly, the analysis of the data processing is the main need to complete the online Web site resource allocation of inefficient information integration, through the algorithm to effectively deal with, in all aspects of consensus, to achieve the smooth operation of each algorithm for the operation of various algorithms to provide protection [29, 30]. Finally, from the output of the innovative optimization program directly into the resource allocation system, the algorithm collected online Web site resource allocation content and online Web site resource allocation requirements, together with the display in the user view page. During the lap up process, part of the lap is randomly selected, as shown in Table 1 [31].Table 1
Algorithm of e-commerce website structure optimization.
Information integration phaseOptimal innovation modelAccuracy rateResonant adjustmentEfficiencyOverall effectRemarks10.930.940.9492.2%20.870.970.9696.2%30.980.890.9893.1%40.910.830.9096.6%As shown in Table1, in the lap stage of the theoretical analysis scheme, using f to represent the model total data algorithm, using x,y to represent the standard data of the material model, this algorithm adds a set of models to ensure objectivity in the information integration stage. To ensure the accuracy of the results, we need to reduce the error of the algorithm [32]. This part of the design first through f to build a corresponding probability calculation, in the input of the corresponding training algorithm, and get an optimized result Y. The formula used in the model is as follows [33]:
(4)f=−1+x′2−x222−1+∑yi.By using this formula, we can get the optimization scheme of the optimization innovation model online resource allocation reform and take the value of the fitting to further operation, in which thepcl represents the optimal coefficient, u represents the standard coefficient, and y represents the set of optimization coefficients. The calculated value is the optimal innovation coefficient in the resource allocation mode of online Web site, in order to make the final calculation basis [34, 35].
(5)pcl=∑ui2+yi+ui0.5y0.8−2yiui.The above results provide the basis for the final step to obtain output instructions for the matting, through the centralized operation of all functions and finally obtain an output value, using artificial intelligence operation. The nextN type represents the e-commerce platform optimization coefficient, ϕxA represents the structure optimization strategy representing the value, λxWx represents the innovation development value of the algorithm, the βmx represents the electric quotient model label, and the f represents the innovation structure coefficient, uses these data to establish the corresponding function relation, and obtains the corresponding difference value sequence. If the corresponding classification problem is encountered, we can take the aggregate function, assuming the f value between the region (-1, 1), and the output function is [35]:
(6)NϕxA+βmxMxλxWx1−0.8N/NxWx≤f.After the optimal numerical value is determined, we aim at our hypothetical algorithmS and the theoretical analysis of all the algorithm outputs between scheme A; according to a series of optimal numerical values, we integrate them into the optimization innovation model, calculate the corresponding joint probability, and obtain the optimal scheme determining coefficient, and the specific running process is shown in Figure 2.Figure 2
Innovation model and algorithm of e-commerce website structure optimization.Through the arrangement of the optimization scheme on online Web site resource allocation, we can get the big analysis direction, carry out the reliability support provided by artificial intelligence, implement the optimization scheme of online website resource allocation, and get the final result of the theoretical analysis and optimization scheme. In this process, the theoretical analysis scheme framework as the intermediate cohesion, its design precision requirements must meet the construction principle of the algorithm to ensure the accuracy of the calculation process. Finally, the end of this link, the theoretical analysis of the optimization index collection is through the computer technology to the optimal solution number, and in this process, through the artificial intelligence formula calculation, the concentration of theoretical analysis system of the blind spot, and the use of theoretical analysis system for the management of resource allocation scheme data classification. The design of the optimization innovation scheme of the e-commerce website resource allocation is accomplished by automatic regularization.


## 4. Result Analysis and Discussion

The application of the innovation model can be used in the platform of electronic commerce to seek a broader choice for the majority of the participants. In this paper, transaction volume was used as a variable of test, which could optimize the advantage of the innovation system through the objective test data. To participate in the company’s running water as the test basis for the participation in online Web site models of participants to collect information, as a test participant before and after evaluation of the basis, at the same time, before carrying out the test, it is necessary to test the system fluency of the artificial intelligence system, to make a random numerical input to the online resource allocation model, and to observe the reliability of the system, so as to get the best performance in the process of resource allocation. Then, the online Web site resource allocation variables are simulated, and the simulation method is used to test the scheme. This simulation test will be based on the database, through the simulation of the resource allocation process, as well as the optimization of the use of innovative models and the employment of professional financial staff to observe the record. The acquisition and rating of the communication are made, and the final error data are shown in Table2.Table 2
Innovation model test of e-commerce website structure optimization.
Financial risk early warning systemOptimal innovation modelFactorDetectionOperatingEffectSmoothDesignSuccessOptimal innovation model10.92.93.24.26.220.82.74.14.04.630.91.92.75.33.5Traditional manual processing41.80.92.46.26.352.31.04.57.03.261.91.12.07.11.4It can be seen from the data in Table2, the optimization innovation model is in the application process of superiority. In the course of this test, there were some errors, but at the same time, the error occurred, the investment judgment error backup was immediately entered into the optimization innovation model, and this aspect shows that, if the original communication process, to do the simulation, the above analysis error will not appear because in the process of testing, mistakes have been optimized by innovative models that are automatically repaired.This is the advantage of the optimization innovation model that is superior to the dynamic algorithm, which can continuously enlarge the advantage of memory performance, can continuously optimize the system in the process of application, and constantly adjust and optimize according to the investment atmosphere. Therefore, in the idle time of the scheme, the scheme is open and continues to simulate the exchange of data artificially entry, adds practical allocation and actual application of investment and theoretical analysis, and the continuous filling, using the optimization innovation model of self-improvement and repair function, continuously improve the accuracy of the optimization innovation model. The use of the optimized innovation model takes time to accumulate, but it is one of the advantages that it will not be replaced until it is put into use. The test results of the e-commerce website structure optimization innovation model is shown in Figure3.Figure 3
Test results of the innovation model of electronic commerce website structure optimization.It can be seen from Figure3, in the process of testing, that the theoretical analysis of the system can be optimized by the innovation model automatic repair. The system can continuously enlarge the memory performance advantage and can optimize the system continuously according to the resource distribution atmosphere. Therefore, in the idle time of the scheme, open the system and continuously artificially input analogy exchange data, arbitrarily add the actual case of resource allocation and theoretical analysis information, to continuously fill, and can ensure the operation of the system. While testing for convergence, we intercepted some of the data as a flowchart, as shown in Figure 4.Figure 4
Test results of the structural optimization innovation model.As can be seen from Figure4, as the resource allocation link weakens, the optimization innovation model algorithm will enter into a theoretical analysis state when the bottom line is reached; then, the efficiency of each resource allocation in the optimization innovation model will be greatly improved. At the same time, the resource allocation optimization system should be considered to expand, through the maximum scheme screening, increase the space to collect more available algorithm resources, and easy to achieve optimal performance in this process. Test results under different network environments are shown in Figure 5.Figure 5
Test results under different network environments.It can be seen from Figure5 that the test result that the decision result based on the principle of electronic commerce can provide support for the public psychological demand, not only guarantee the implementation of the Internet economic principle but also can take into account the psychological satisfaction of the participants. As shown above, in the single variable to ensure the implementation of Internet economic principles, the labor intensity of the participants does not fluctuate greatly, but the degree of psychological satisfaction is far less than the mode of optimizing the innovation system. It can be found that the artificial intelligence system is an auxiliary system, which can only have positive effect on the participants and has no effect on the distribution of e-commerce and the results of our country. e-Commerce network test results under different test scenarios are shown in Figure 6.Figure 6
e-Commerce network test results under different test scenarios.Through the above experimental results, it can be observed that the use of the optimization innovation system as an auxiliary system not only does not increase the financial burden of the country but to some extent, for the country’s economic allocations to provide more flexible space. On the premise of ensuring the distribution of resources on the online website, the two-variable model can be processed, and the corresponding judgment should be made according to the analysis and the participant status information. Therefore, the resource allocation theory analysis model, whether in dealing with a single variable or multivariable situation, can ensure the stability of the national economy on the basis of the interests of the majority of participants to maximize.


## 5. Conclusions

This paper optimizes the e-commerce system to maximize the efficiency and objectivity of the computer system. Then, the analysis to the electronic commerce website resource allocation model is carried on. Through the theory analysis system construction, the analysis flaw integration retrieval link is utilized, to the theory analysis project uncertainty factor carries on the collection. Then, according to each flaw that represents the outstanding problem that is classified to the classification, the entire theory analysis model frame is completed. At the same time, it is necessary to make further efforts to deal with the theoretical analysis system of the design and to set up the evaluation standard as well as the statistical calculation of the resource allocation vulnerabilities of online websites.



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*Source: 8825825-2020-11-02.xml*