A Self-Organized Mapping Neural Network-Based Intelligent Evaluation Model for Business Capacity in Enterprise Management

In era of big data, the integration of deep learning with enterprise management has been an inevitable requirement. However, scenarios of enterprise management vary with ever-changing entities, without fixed problem format. This makes it difficult to form a universal golden dataset for training supervised models. To handle such challenge, this paper takes the “business capacity evaluation of human resources in the enterprise management” as the main situation, and explores unsupervised deep learning-based technical methods for solution. Specifically, this paper proposes a self-organized mapping neural network (SOMNN)-based intelligent evaluation model for business capacity in enterprise management. For one thing, the procedures of SOMNN are described using symbol representation. For another, the SOMNN is specifically embedded into the realistic situations of business capacity evaluation, so as to generate digital evaluation results. After that, we carry out a case study on data from a real-world enterprise, in order to make performance assessment for the proposed model. The simulation results show that the proposed model can make proper evaluation towards business capacity in enterprise management, under the unsupervised pattern.


I. INTRODUCTION
As an important element in the production and operation of enterprises, human resource management's development ability and level will greatly affect the development of enterprises [1].Under the background of low-carbon economic development, this concept has a great impact on the management and operation of enterprises [2].In the face of this background, the development of human resources also needs a certain transformation [3].Employees are required to understand the provisions on carbon emission reasons in global, national and local strategic plans [4].The low carbon The associate editor coordinating the review of this manuscript and approving it for publication was Mostafa M. Fouda .economy leads to the adjustment of the business structure of enterprises, which will definitely eliminate some posts and promote some new posts [5].These new jobs need to be qualified by employees with low carbon environmental awareness and advanced scientific knowledge and skills [6].This requires enterprises to improve the quality and ability of human resources through education and training to meet the timely needs for human resources [7].Therefore, it is required for enterprise to enhance business capacity management of human resources [8].
In this context, this paper considers developing an intelligent evaluation model for business capacity in enterprise management, with use of self-organized mapping neural network (SOMNN) [9].The SOMNN is a unsupervised neural network (NN) structure by adding the self-organized mapping (SOM) mechanism [10].It can capture the attributes and rules in the samples by itself, similar to the sensory channel of the human brain [11].When a large number of sensory units are close to the human sensory organs.The relevant specific neurons of the brain begin to excite and approach the output [12].SOMNN can extract important features or some internal laws from a group of data through learning, and classify them in a discrete time manner [13].The network can map any high-dimensional input to a low dimensional space, and make some similar properties in the input data behave as geometrically adjacent feature mapping [14].Through intelligent development and SOMNN, this paper attempts to reveal the influencing factors and trends of personnel position matching in the organization, so as to provide some reference for the design of the platform capability decision support system of human resource and human resource capability [15].To accurately predict the enterprise's human resource allocation, it is necessary to establish an accurate model [16].
The problem statement that SOM (Self-organizing map) solves in human resources is to help the organization effectively manage and coordinate the relationship between people and the company's goals to maximize business value.SOM can ensure the effective output of people through mechanisms, enable organizations and people to serve the company's strategy, coordinate the goals of organizations and people, and the relationship between the company's goals.With the power of mechanisms, all goals converge or equal to the company's goals, thereby achieving the goals and ensuring the maximization of the company's commercial value.In human resources, when faced with many employers and attributes that cannot be manually managed, computational tools such as SOM can help make better decisions.SOM can serve as an effective decision support tool, processing a large amount of employer and attribute data, helping to analyze, classify, and visualize data for better understanding and management of human resources.In summary, the application of SOM in human resources mainly focuses on solving the problem of goal coordination between organizations and people, as well as processing a large amount of data to support decision-making.SOMN (Self-organizing map Network) has the following important significance in business capability evaluation of human resources in enterprise management: 1) Help identify and evaluate employees' business abilities: SOMN can classify and visualize employees' abilities and performance, help human resources departments better understand employees' professional knowledge and skill levels, identify which employees have advantages and disadvantages in which areas, and better carry out personnel allocation and career development plans.
2) Promote employee personal development and team collaboration: By classifying and visualizing employees' abilities through SOMN, it can help employees better understand their strengths and weaknesses, identify areas for improvement, and promote personal development.Meanwhile, SOMN can also help team members better understand each other's professional knowledge and skills, promoting team collaboration and cooperation.
3) Improving overall performance of the enterprise: By evaluating and analyzing the abilities of employees through SOMN, it can help the enterprise better allocate and optimize human resources, and improve overall performance.For example, arranging different employees with similar skills and experience in different job positions can promote knowledge sharing and skill enhancement, improve work efficiency and performance.
There are three basic tasks for SOMNN algorithm to improve the medium capacity of regional human resource capacity: human resource team capacity, human resource market capacity and human resource government capacity building [17].The topological organization of neurons in SOM network is its most fundamental feature [18].For the subset of neurons formed by topological correlation, the updating of weights is similar, and in this learning process under the intelligent development, the subset so selected will contain different neurons.From the perspective of human resource capacity, the SOMNN algorithm is used according to the three ''forces'' of regional human resource team capacity, human resource market capacity, and human resource government capacity, Build a medium capacity model of human resource capacity [19].Because an enterprise that has developed through intelligence is a complex system and is affected by many internal factors of the enterprise, such as enterprise culture, economic strength and external environment.
It is difficult to model the dynamic human resource allocation relationship in the enterprise with conventional mathematical methods, which not only requires a lot of work, but also is difficult to ensure the accuracy.If a position of SOMNN changes, this change will affect the nearest neighbor of this neuron.However, the further away from the neuron, the less this effect will be.Therefore, with the help of this model, we can understand the formation process of human resource capacity in middle platform, and then build a more complete evaluation index system of human resource capacity level, so as to make a more accurate comparison of the intelligent development of human resource capacity in middle platform in China's provinces and cities.The following three innovations are proposed in this paper, and the specific contents are as follows: • This paper constructs a human resource capability middle office capability model based on SOMNN.
• This paper analyzes the influence of intelligent development on the development of human resource capacity.
• This paper aims to realize the innovation of human resource management for enterprises and provide guidance for their long-term development.
111802 VOLUME 11, 2023 Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.
The overall structure of this paper consists of five parts.The first section describes the background and significance of the medium capacity of human resource capacity.The second section mainly introduces the relevant research on the medium capacity of human resource capacity.The third section describes the principles of human resource capacity building and the realization of human resource capacity based on SOMNN algorithm model.The fourth section is the experimental part.The fifth section is the summary of the full text.

II. RELATED WORK
The cultivation of low-carbon talents by enterprises is not enough.Under the influence of low-carbon economy, enterprises must increase more ''low-carbon posts''.And more ''Low carbon employees in these positions need employees with high comprehensive quality, including educational background, knowledge structure and practical skills.In order to make human resources competent for the requirements of low carbon development of enterprises, it is necessary to invest in human capital.However, many enterprises lack awareness of human capital investment, just industrial and technical talents and carbon trading talents engaged in emission reduction mechanisms [20].Because there is no special training in society under the high carbon development mode The enterprise has not reserved relevant talents for the above low-carbon professionals.This poses a challenge to the existing human resource structure of enterprises, and the existing professional structure of human resources needs to be adjusted.Increase the proportion of low-carbon professionals in the enterprise's human resource structure to meet the requirements of low-carbon business.
Dahliah D believes that the executor and promoter of the building activities of middle platform capacity of enterprise HR is the HR functional department.The enterprise determines the strategic development direction, and the HR functional department carries out the strategic planning of HR capacity, and then formulates corresponding strategies and plans to carry out specific work to promote the smooth implementation of the development strategy of middle platform capacity of enterprise HR capacity [21].Xu J, et al. shows that human resource ability is the sum of labor ability in the population, and the ability of middle and middle platform is in a dominant position in economic activities, controlling and dominating the development and utilization of other resources.Therefore, the capacity building of HR in middle platform plays an important role in the coordinated development of a country's society, economy, culture, politics and other aspects, and is the driving force of a country's economic and social development [22].
Yue W has carried out research on the middle platform capacity building of HR in enterprises, which plays a catalytic role in realizing enterprise strategy.Because the process of enterprises' competition is mainly a process in which a group of competitors grab, utilize and increase the value of resources, the different abilities of competitors to discover, grab and utilize resources determine the different results of the competition [23].Liu Y believes that there is a growing demand for the measurement of middle platform capability of HR.From the comparison of HR capabilities in macroregions to the comparison of capabilities among individual HR in micro-organizations, a more scientific method and system are required to make a rough estimate of middle platform capability of HR, even within an acceptable range.Therefore, the importance of HR capability measurement is becoming increasingly prominent [24].Yi pointed out that at present, with the rapid development of economy and science and technology, the demand for middle platform HR capacity is multi-faceted, which requires relevant personnel to make corresponding adjustments.This kind of structural adjustment will also change the number of personnel.If it is downsizing, those with unbalanced capacity structure will face unemployment.These are all formed by ''unbalanced capacity structure'' [25].
Jia Y, et al. shows that the cost of input must be taken into account when collecting the index parameters of human resource capability measurement.If collecting the index parameters requires a lot of manpower and material resources, it may constitute a major obstacle to the measurement of human resource capability.After all, the cost and input of human resource capability measurement are also a problem worthy of attention [26].Letiagina E, et al.Building its HR capacity helps to strengthen its core competitiveness.The competition among enterprises in the market is the competition of product and service quality on the surface, but it is actually the competition of talent.The more fully the human resource ability and active role are played, the one who has it will occupy a dominant position [27].Zheng J, et al. shows that the construction of HR capacity to adapt to the development of economy and science and technology is a comprehensive and open work, which requires the participation of the government, enterprises and all sectors of society, and forms a good mechanism for joint participation and benefit [28].
Xu J, et al. proposed to build a modern economic system, speed up the healthy economic development, technological innovation, and build a system for the common development of modern finance and HR.Capital and other services will promote growth and generate new kinetic energy.It is the scientific and technological talents with moderate HR ability that enable young scientific and technological talents and large international innovation teams to cultivate a variety of technical strategies and talents, and cultivate skilled, innovative and knowledge-based talents [22].Arfaee M, et al. thinks that the capacity building of HR in China and middle platform is to continuously improve the ability of HR to contribute to society by shaping, improving, cultivating and expanding the environment and space in which HR play their role.The development of middle platform capacity building in human resource capacity is the key to the sustainable development of national economy [16].

III. METHODOLOGY
Using SOMN or cluster tools can more easily process large amounts of data and visualize Data and information visualization for better understanding and analysis.Without using these tools, manual processing and analysis of data are required, resulting in lower efficiency.Using SOMN or clustering tools can group employers to better understand their characteristics and needs.This can help enterprises better understand and manage human resources, and develop more accurate human resource plans.Without using these tools, manual employer classification and management may be required, resulting in lower efficiency.SOMN or cluster tools can provide more accurate data and analysis results, helping enterprises make better decisions, such as personnel allocation, career development plans, etc.Without using these tools, subjective experience and manual analysis may be required, resulting in lower accuracy and reliability of decision-making.
Before describing digital evaluation method for business capacity in enterprise management, it is expected to introduce contents for training principle of human resource construction in enterprise management.From the perspective of personal ability, a certain ability corresponds to a certain right, responsibility and interest, and a certain post also corresponds to a certain right, responsibility and interest, which is defined from the perspective of post responsibility system.The training of capacity building in HR capacity is shown in Figure 1.On this basis, this paper develops a SOMNN-based business capacity evaluation model, and its mathematical description is given below.
The input layer in the SOMNN collects external relevant information and transmits the input information to the competition layer.This layer classifies and combines these information again to find the rules and arrange them in order.SOMNN is a description of the first-order characteristics of human brain system and a method of artificial intelligence research.It can be said to be a mathematical model, which can be realized by electronic circuits or simulated by computer programs [29].The SOMNN also has the characteristics of being able to memorize the effective information units before and after, organically connecting them into a ring, and has strong dynamic, sequential, computational and other unique advantages.
At the same time, the NN uses input and output related information data for training, timely and accurate analysis of data rules, and independent learning of the analyzed data to form a relatively stable ring structure.The impact of factors on the value of HR is not a simple linear relationship, but a complex relationship of interdependence and restriction, and an unknown nonlinear and complex mapping relationship, which brings difficulties to the evaluation of HR middle office capacity [30].In this paper, SOMNN algorithm is introduced into the field of human resource evaluation, and combined with the actual data of a company to build a human resource capability interpretation structure model, which has achieved good results.The construction of human resource capability middle office capability model based on SOMNN is shown in Figure 2.
In the basic structure of SOM, the output layer of the network is a two-dimensional planar structure, and all neurons in the input layer and the competition layer are interconnected, that is, there are connections between each output node and all input nodes, and each connection has a connection weight, which is used to indicate the strength of this connection.The connection weight of each neuron has a certain distribution, and each input node is connected with the output node through connection weight w, and the connection weight w ij of output node j and input node x i (i = 1, 2, . . ., N ); It is the cluster center of class j.Set the input mode, and determine the winning unit in the competition layer to set the input mode: The output response of neurons in the competitive layer is: The connection weight vector between competitive layer neuron j and input layer neuron I is: And the connection weights between neurons in the input layer of neurons are modified: In the learning process, the learning factor α(t) and the neighborhood Nc(t) gradually decrease.The middle platform competence model of human resource competence vividly demonstrates the whole process of how the main body of human resource competence training influences the middle platform competence of human resource competence through human resource development, elimination of obstacles and allocation of market resources under the action of system elements [31].This model can help middle platform managers of HR to clarify the development path, broaden their thinking, and discover the problems.At the same time, this model also shows the whole process of HR from input to output, which lays the foundation for the construction of middle platform evaluation system of HR.
The new requirements of intelligent development on personnel allocation will inevitably lead to the gradual improvement of productivity.At the same time, the original business subject of production and operation posts will gradually change from operation to equipment operation status monitoring and production process control.Intelligent operation is based on the full maturity of equipment and process stability.It is necessary to strengthen the monitoring and operation maintenance of intelligent equipment, but the lack of operation and maintenance personnel affects the development of relevant work.The enterprise is faced with severe challenges such as overcapacity, industrial restructuring, environmental protection and production restriction, and homogeneous competition.The enterprise complies with the requirements of the times, constantly explores the construction of intelligent chemical plants on the basis of a high level of automation.After years of efforts, it has formulated a roadmap for the development of automation, informatization, digitization, and intelligence, and gradually implemented the development of human resource capacity [32].The personal goals of enterprise employees and the long-term goals of the department are mutually reinforcing and interdependent.If the government departments consider their own long-term plans and goals, they should pay attention to the career planning of enterprise employees and the improvement of their abilities in all aspects.
The career planning process of enterprise employees is shown in Figure 3. Chang et al. used Self-organizing map (SOM) neural network to visualize the correction of failure mode and impact analysis (FMEA).SOM neural network can classify and visualize fault modes, helping enterprises better understand the characteristics and processing methods of different fault modes, in order to better carry out fault prevention and maintenance.SOM neural networks can classify and visualize the impact of faults, helping enterprises better understand the characteristics and scope of different fault impacts, in order to better develop response strategies and corrective measures.SOM neural networks can display the effectiveness of different corrective measures on a visual platform, helping enterprises better evaluate the effectiveness and feasibility of corrective measures, in order to select the best corrective measures [1].
The intelligent development of human resource capability not only refers to the ''human'' capability, but also includes the external environment of the region where human capabilities are actually used.Therefore, under the intelligent development, human resource capacity must examine the activities in two aspects and three dimensions.The first aspect is the ability of the people in the region; The second aspect is the social conditions for intelligent development in which human capabilities can be fully and effectively utilized.The social conditions here mainly focus on the two dimensions of ''market'' and ''government'', so as to build a network with the core of human resource team capabilities, human resource market capabilities and human resource government capabilities to measure the error of the entire sample set: The difference between the actual output O 2p and the corresponding ideal output Y p is calculated, and the weight matrix V and W is adjusted by minimizing the error.On the error measure of the p sample of the network: The elements of regional human resource capability reasonably selected, and the element set N of regional human resource capability is gotten, which is recorded as: where S i represents the i component in the system.The antecedent set of N i elements is represented as:  The reachable set of elements is represented as: Collective C is represented as: They belong to two connected domains respectively.After completing the network structure design, it is necessary to train the network model, that is, to adjust the connection weights of nodes between layers according to the sample data.Under the development of intelligence, the evaluation index system of human resource ability takes human resource team ability, human resource market ability, human resource government ability and economic development level as evaluation factors.In the comprehensive evaluation of the established multi-index system, it is important to give each index a reasonable weight, indicating the importance of the index.The proportion of the index value of the i object under the j index is: x ij (11) The entropy value of the j index is: The variation degree of the j index is: And the entropy weight of the j index is: The larger the positive index value, the stronger the human resource ability.The standardized formula is as follows: 111806 VOLUME 11, 2023 Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.
The larger the reverse index value, the weaker the human resource ability.The standardized formula is as follows: Among them, x ij is the original data, x i(max) is the maximum value of the original data of item i, x i(min) is the minimum value of the original data of item i, and v ij is the standardized value of the original data.
Human resource capacity has increasingly become a decisive factor in promoting the overall development of intelligent development of social economy.Human resource capacity building meets the inherent requirements of the transformation from material economy to knowledge economy.It is a conventional path for HR to contribute to economic growth and an inevitable choice to take a new path of industrialization.It conforms to both the scientific concept of development and the objective law of coordinated development of people and society.Under the intelligent development, in view of the low skill level of employees, the transformation of operators to management and control workers, the transformation of multi skilled talents, and even the transformation of professional and technical talents, we will continue to improve the training system, promote the training of human resource capacity in the middle office, and help the development of human resource capacity in the middle office.

IV. RESULT ANALYSIS AND DISCUSSION
The enterprise shall clearly define the key behaviors of incentives or constraints, so that employees can achieve low carbonization in their personal life and work behaviors.The human resource management department of the enterprise should include the low carbon behavior performance of employees into the evaluation system.On the basis of formulating the overall goal of the enterprise's low-carbon economic performance, it will be broken down layer by layer, and according to the enterprise's cost budget and lowcarbon goals, the assessment rules will be formulated.Finally, a low carbon behavior assessment system for employees will be formed to constrain their behaviors through assessment.On the basis of the assessment, the human resource management department of the enterprise should also establish a salary management system corresponding to the low carbon behavior performance evaluation indicators.
Comprehensive use of a variety of incentive mechanisms to improve the enthusiasm and initiative of employees to participate in low-carbon business.Employees who have made direct contributions to the low carbon performance of the enterprise can be given material and spiritual rewards according to the degree of cost reduction or social benefits.And establish the image of bid price to drive all employees to actively participate in the low carbon development of the enterprise.In this paper, SOMNN is used to calculate the flow probability of technicians as the output node, and the total output value, economic benefits, total number of employees and the proportion of technicians are used as the input nodes.Based on the data of an enterprise from 2016 to 2019, the turnover probability and proportion of technicians in 2016-2019 are predicted, as shown in Table 1.
Before training, the data needs to be normalized.Since the input sample is a 4-dimensional input vector, representing the total output value, economic benefits, total number of employees and the proportion of technicians respectively, the training frequency is 1000, the training goal is 0.001, and other parameters are set as default values.The trained SOMNN is used to fit and predict the situation in 2020-2021, and the comparison between the fitting value and the actual value is obtained, as shown in Table 2.It can be seen that when the hidden layer node is 10, the error is the minimum, and the prediction accuracy requirements are met.It can be seen that the greater the number of hidden layer nodes, the higher the accuracy.
Based on the above index interpretation and the equation of the equivalent coefficient of human resource capacity, the method of human resource capacity evaluation is established.Based on the data of the fourth population census, the equivalent coefficient of human resource capacity of all provinces, cities and autonomous regions in China is calculated.This experiment was conducted on the data of Shanghai, Beijing, Zhejiang, Hangzhou and Hubei, Wuhan from 2014 to 2021.The data chart of human resource capacity equivalence coefficient is shown in Figure 4. Figure 4 shows that there is a big gap between Shanghai's human resource capacity equivalent coefficient and the national average, with the average equivalent coefficient of 5.34, Beijing's human resource capacity equivalent coefficient of 3.99, Zhejiang's Hangzhou's human resource equivalent coefficient of 3.26 and Hubei's Wuhan's human resource equivalent coefficient of 2.53.Compared with the other three regions, Shanghai's human resource equivalent coefficient is generally higher.
Physical ability, the most basic ability of human beings, refers to the physical ability that human beings need to  engage in various activities.The most direct manifestation of physical fitness is people's physical health.Whether physical fitness is healthy directly affects a person's ability to work and indirectly affects how much social wealth a person creates.Poor physical quality of HR is closely related to medical treatment, health care and nutrition.Therefore, this experiment has carried out research on population mortality, and the experimental results are shown in Figure 5.The value range of human resource capability coefficient is one, and the basic classification is shown in Table 3.
From the perspective of HR' contribution to society, different types of ''people'' have different contributions to society.''Intelligent'' people contribute the most to society, ''skilled'' people are the most, and ''physical'' people are the least.From the perspective of human ability structure, human comprehensive ability is mainly composed of physical ability, skills and intelligence, and physical ability is the basic ability of human.The change of population mortality is shown in Figure 6. Figure 6 shows that the national mortality rate is 7.45%, the highest mortality rate is 7.43% in Wuhan, Hubei, 4.54% in Hangzhou, Zhejiang, 4.98% in Beijing and 4.19% in Shanghai.The national life expectancy is about 71.8 years, and the life expectancy in Shanghai is 67.48 years.
Skill refers to an automatic action mode and mental mode that workers can successfully complete certain activities through repeated practice, and the technical experience and operational ability formed by workers in the process.As for the present situation of skills and abilities, I analyze the indicators of the proportion of primary industry population, secondary industry population and tertiary industry population in Shanghai.The data shows that among the three industries in Shanghai, the primary industry accounts for the highest proportion, followed by the tertiary industry, It is the abbreviation of intelligent ability, which refers to the ability of workers to analyze and solve problems by using knowledge and experience.Intelligence construction refers to the process of improving, promoting and enhancing people's intellectual ability by means of certain methods and means.Therefore, this experiment investigated elementary schools, junior high schools, senior high schools, colleges and above in Shanghai, and the experimental results are shown in Figure 7. Figure 7 shows that the average number of college, undergraduate and graduate students with college education is 452797, the average number of people with high school education including technical secondary school education is 498488, and the average number of people with middle school education is 4566784.The average number of people with primary school education, including technical secondary schools, is 641471.From the above evaluation indicators, it is found that Shanghai's intelligence level is at a medium level, and further efforts are needed.
Human resource capabilities are classified according to recruitment, training, salary, performance, employee relations and career planning, so as to find out the real needs of business departments for human resource capabilities.The business department's requirements for the HR module are shown in Figure 8.The data in Figure 8 shows that the overall demand of business departments for HR capability is high, with recruitment, training and performance accounting for 56.68%, 46.20% and 23.6% respectively, ranking the top three in the demand of business departments.In this survey, there are 257 participants in the business group, accounting for 63% of the business personnel.However, the company is in a period of rising business, and each division has an urgent need for personnel introduction.
The human resource management function of enterprises should not only promote the low-carbon behavior of employees, but also achieve the low-carbon management activities.The concept of ''low carbon'' should be implemented in human resource planning, recruitment, training, performance appraisal, salary management and other links.The lowcarbon human resource planning requires systematic analysis of the structural changes of the low-carbon economy on the demand for human resources of enterprises, and the formulation of the supply and demand balance strategy for low-carbon talents of enterprises to support the low-carbon development strategy of enterprises.Low carbon recruitment requires the adoption of low carbon processes and means to complete recruitment tasks with the lowest recruitment cost and the most environmentally friendly way.For example, electronic recruitment greatly saves the consumption of various social resources, greatly improves the work efficiency and reduces the management cost.

V. CONCLUSION
This paper evaluates the performance of employees and guides them to produce low-carbon behaviors that are conducive to improving the environmental performance of enterprises.Low carbon salary management requires enterprises to design a salary system linked to low carbon performance, and encourage and constrain employees' behavior through the combination of positive reinforcement and negative reinforcement.This paper conducts research on the influence of intelligent development on the construction of human resource capacity in the SOMNN algorithm model.The research shows that the overall demand of business departments for human resource capacity is high.Recruitment, training and performance account for 56.68%, 46.20% and 23.6% respectively, ranking first in the demand of business departments.In this survey, 257 people participated in the business cluster, accounting for 63% of the business personnel.
At present, the company is in the business growth period, and all business divisions are in urgent need of personnel introduction.From the system formulation, job rotation, training promotion, salary incentive and other aspects, the paper puts forward the countermeasures to improve the medium and middle platform capacity building of human resource capacity.Combined with the current situation and existing problems of human resource capacity building in SOMNN, this paper conducts a relatively indepth understanding and research, and puts forward ideas on human resource capacity and countermeasures to improve human resource capacity building in middle platform from the macro and micro perspectives, so that it can provide effective guarantee for the sound operation of intelligent development of human resource management from multiple aspects, and provide power for the rapid development of enterprises.
The SOMN human resources model can help enterprises better understand the abilities and characteristics of employees, allocate them to the most suitable positions, leverage their advantages, and improve work efficiency and performance.At the same time, the SOMN model can also help employees understand their abilities and characteristics, and choose the most suitable career development path.SOMN human resource model can help Corporate identity identify skills and knowledge that employees lack.Develop targeted training and development plans to improve employees' overall quality and professional abilities.This model helps enterprises better understand the abilities and characteristics of team members, promotes collaboration and cooperation among team members, and improves the overall performance of the team.
In the assessment of human resources business capabilities in enterprise management, SOMN can effectively assist enterprises in classification and visualization, thereby improving the accuracy and efficiency of decision-making.However, there are also some limitations that need further discussion and research in this process: SOMN needs to process a large amount of data and conduct model construction and training, which may require a significant amount of time and computational resources.At the same time, the accuracy and completeness of data also have a significant impact on the accuracy and reliability of the model.The parameter settings and adjustments of SOMN have a significant impact on the results, and different parameter settings may result in different results.Therefore, it is necessary to select appropriate parameters and adjust them to obtain the best results.With the changes in enterprise business and personnel, SOMN needs to be continuously updated and adapted to maintain its accuracy and reliability.

FIGURE 1 .
FIGURE 1. Training diagram of the principle of capacity building in the middle of HR capacity.

FIGURE 2 .
FIGURE 2. Middle platform capability model of human resource capability based on SOMNN.

FIGURE 3 .
FIGURE 3. Flow chart of enterprise staff career planning.

FIGURE 4 .
FIGURE 4. Data Map of Equivalent Coefficient of Human Resource Capability.

FIGURE 5 .
FIGURE 5. Change trend of population proportion and number of people engaged in various industries.

FIGURE 6 .
FIGURE 6. Changes of population mortality rate.

FIGURE 7 .
FIGURE 7. Comparison of Education Level of Population.

FIGURE 8 .
FIGURE 8. Demand of business department for HR module.

TABLE 1 .
Relevant data of an enterprise from 2018 to 2021.

TABLE 2 .
Comparison of real data and forecast data.

TABLE 3 .
Grading of human resource capacity.