Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01373
Zinan Su
Abstract Under the background of the development of network technology, this paper aims to promote rural English teaching and constructs an English teaching model that combines English recognition technology and rural teaching. The main process of speech recognition is examined by analyzing different speech recognition technologies. Using a deep learning network, an English speech recognition model has been established. Combined with the English acoustic features in the network data, fluency of English speech is evaluated. Data embedding is performed on the English sequences in the network, combined with the sequence probability in the English data, so as to determine whether the English speech is correct or not. The Eval value for the English recognition model based on deep learning is 5.49%, while the test value is 5.89%, as per the results. As the English dataset increases, so does the English recognition technique proposed in this paper, and the accuracy remains above 0.6, and when the dataset is 500, the speech recognition accuracy is 0.8. The teaching model that combines speech recognition techniques with English teaching improves students’ English to a certain extent.
{"title":"Research on the Reform of the Teaching Mode of Rural English Education Assistance Based on the Technical Support of Network Technology","authors":"Zinan Su","doi":"10.2478/amns.2023.2.01373","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01373","url":null,"abstract":"Abstract Under the background of the development of network technology, this paper aims to promote rural English teaching and constructs an English teaching model that combines English recognition technology and rural teaching. The main process of speech recognition is examined by analyzing different speech recognition technologies. Using a deep learning network, an English speech recognition model has been established. Combined with the English acoustic features in the network data, fluency of English speech is evaluated. Data embedding is performed on the English sequences in the network, combined with the sequence probability in the English data, so as to determine whether the English speech is correct or not. The Eval value for the English recognition model based on deep learning is 5.49%, while the test value is 5.89%, as per the results. As the English dataset increases, so does the English recognition technique proposed in this paper, and the accuracy remains above 0.6, and when the dataset is 500, the speech recognition accuracy is 0.8. The teaching model that combines speech recognition techniques with English teaching improves students’ English to a certain extent.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"58 12","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138598242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01354
Yanling Wang
Abstract In this paper, in order to obtain a better classification evaluation effect, a feedback connection model is added to the convolutional neural network to establish the evaluation model of the integration of industry and education in colleges and universities based on FCNN. Compare the MSE loss values of the traditional BP neural network model and the FCNN model. Indicator system construction, with the help of the accuracy of the convolutional neural network, to carry out the whole process of evaluation around the indicators, weights, and the quality of the implementation results. The data of students’ micro-expression concentration recognition test is used as the evaluation data of students’ project participation, comparing the recognition rate of the participation evaluation system proposed in this paper and the traditional participation evaluation system to complete the quality evaluation of the talent cultivation model of college education. Analyze the data on the graduation rates of college graduates to determine the effectiveness of the university’s integration of college education. The analysis shows that in 2022, the professional matching employment rate of graduates was 86.28%, which reflects the high efficiency of the university’s industry-teaching integration on the cultivation of professional and applied talents, and the mechanism of industry-teaching integration is well affiliated.
{"title":"Research on the Innovation of Talent Cultivation Mode and Industry-Education Integration Mechanism of College Education in the Internet Era","authors":"Yanling Wang","doi":"10.2478/amns.2023.2.01354","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01354","url":null,"abstract":"Abstract In this paper, in order to obtain a better classification evaluation effect, a feedback connection model is added to the convolutional neural network to establish the evaluation model of the integration of industry and education in colleges and universities based on FCNN. Compare the MSE loss values of the traditional BP neural network model and the FCNN model. Indicator system construction, with the help of the accuracy of the convolutional neural network, to carry out the whole process of evaluation around the indicators, weights, and the quality of the implementation results. The data of students’ micro-expression concentration recognition test is used as the evaluation data of students’ project participation, comparing the recognition rate of the participation evaluation system proposed in this paper and the traditional participation evaluation system to complete the quality evaluation of the talent cultivation model of college education. Analyze the data on the graduation rates of college graduates to determine the effectiveness of the university’s integration of college education. The analysis shows that in 2022, the professional matching employment rate of graduates was 86.28%, which reflects the high efficiency of the university’s industry-teaching integration on the cultivation of professional and applied talents, and the mechanism of industry-teaching integration is well affiliated.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"136 39","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138598645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01366
Tengda Liu
Abstract With the rapid development of the catering industry, catering fume pollution has become one of the important sources of urban air pollution. How to realize the purification of catering fumes is a huge problem related to public life health and safety. This paper first constructs the structure of self-cleaning low-temperature plasma soot purification and provides the equipment, materials, and process required for soot purification experiments. Secondly, CFD simulation of the flue of the oil smoke purification device is introduced into Computational Fluid Dynamics, and the relevant physical parameters of the oil smoke flow are obtained by solving the equations of mass conservation, momentum conservation and energy conservation. The self-cleaning low-temperature plasma oil smoke purification device was also analyzed by numerical simulation using Fluent software, and the method for detecting VOCs in restaurant oil smoke was given. Lastly, the oil smoke purification device constructed in this paper was tested for its impact on oil smoke. The results show that for every 100W·m−2 increase in the intensity of oil smoke, the temperature error will increase by about 0.01℃ accordingly, and when the intensity of oil smoke reaches 500W·m−2, the temperature error of the oil smoke purification device is 0.074℃. The highest imported concentration of all kinds of VOCs in the barbecue smoke produced by the experiment reached 3762.53 μg / m3, and the average treatment efficiency of 98.69% was achieved under the actual air volume of about 800m3/h. This shows that the use of computational fluid dynamics can realize the simulation analysis of a self-cleaning low-temperature plasma fume purification device, and the fume purification device has a strong fume purification ability.
{"title":"Design of self-cleaning low-temperature plasma fume cleaning device based on computational fluid dynamics","authors":"Tengda Liu","doi":"10.2478/amns.2023.2.01366","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01366","url":null,"abstract":"Abstract With the rapid development of the catering industry, catering fume pollution has become one of the important sources of urban air pollution. How to realize the purification of catering fumes is a huge problem related to public life health and safety. This paper first constructs the structure of self-cleaning low-temperature plasma soot purification and provides the equipment, materials, and process required for soot purification experiments. Secondly, CFD simulation of the flue of the oil smoke purification device is introduced into Computational Fluid Dynamics, and the relevant physical parameters of the oil smoke flow are obtained by solving the equations of mass conservation, momentum conservation and energy conservation. The self-cleaning low-temperature plasma oil smoke purification device was also analyzed by numerical simulation using Fluent software, and the method for detecting VOCs in restaurant oil smoke was given. Lastly, the oil smoke purification device constructed in this paper was tested for its impact on oil smoke. The results show that for every 100W·m−2 increase in the intensity of oil smoke, the temperature error will increase by about 0.01℃ accordingly, and when the intensity of oil smoke reaches 500W·m−2, the temperature error of the oil smoke purification device is 0.074℃. The highest imported concentration of all kinds of VOCs in the barbecue smoke produced by the experiment reached 3762.53 μg / m3, and the average treatment efficiency of 98.69% was achieved under the actual air volume of about 800m3/h. This shows that the use of computational fluid dynamics can realize the simulation analysis of a self-cleaning low-temperature plasma fume purification device, and the fume purification device has a strong fume purification ability.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"119 28","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138599445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01347
Jinyu Liu
Abstract In this paper, the maximum Lyapunov exponent and chaotic phase space reconstruction method of the chaotic computing model are studied, the embedding dimension is obtained by using the saturated correlation dimension method, and the fractal scale of the chaotic model is determined by the DFA method. Based on the relevant policy documents, an index system for assessing the level of government digital construction is constructed, and the weights of each index are calculated. The constructed index system is used to analyze the digital construction level and digital service quality of the Chinese government, and the evolutionary characteristics of the standardized construction of China’s digital government are analyzed based on the chaotic computing model. The results show that the total score of each provincial government in the sample reaches above 90, only one provincial government has a total score below 80, and the average score of the total score reaches 85.72, which indicates that most of the provincial governments in China have a good level of digital construction. The purpose of this study is to promote and optimize the digital construction of provincial governments and improve their digital construction level, which is of greater practical significance.
{"title":"Standardized Construction Indicator Assessment and Practice of Digital Government for Chaos Computing Theory","authors":"Jinyu Liu","doi":"10.2478/amns.2023.2.01347","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01347","url":null,"abstract":"Abstract In this paper, the maximum Lyapunov exponent and chaotic phase space reconstruction method of the chaotic computing model are studied, the embedding dimension is obtained by using the saturated correlation dimension method, and the fractal scale of the chaotic model is determined by the DFA method. Based on the relevant policy documents, an index system for assessing the level of government digital construction is constructed, and the weights of each index are calculated. The constructed index system is used to analyze the digital construction level and digital service quality of the Chinese government, and the evolutionary characteristics of the standardized construction of China’s digital government are analyzed based on the chaotic computing model. The results show that the total score of each provincial government in the sample reaches above 90, only one provincial government has a total score below 80, and the average score of the total score reaches 85.72, which indicates that most of the provincial governments in China have a good level of digital construction. The purpose of this study is to promote and optimize the digital construction of provincial governments and improve their digital construction level, which is of greater practical significance.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"108 22","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138599865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01374
Bi Zhao
Abstract This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the dissemination of traditional culture by analyzing the embodiment of traditional culture in Chinese language literature network texts. The collection process of Chinese language and literature data in network text is analyzed from the perspective of textual data interaction. The information of node variables in a Bayesian network is used to determine the mutual relationship between Chinese language literature and traditional culture. The degree of interdependence between Chinese literature and traditional culture can be measured by combining mutual information. The results show that the correct rate of text recognition of the Bayesian text recognition model decreases slightly when the training samples are (100-300), but the correct rate always stays around 0.85, thus reflecting the effectiveness of the network recognition model in this paper. Chinese language literature has a certain role in the dissemination of traditional culture, which proves that Chinese language literature, as a carrier of traditional culture, can improve the dissemination speed of traditional culture. This study focuses on the integration of Chinese literature and traditional communication to improve a new vision.
{"title":"Exploring the Role of Chinese Language and Literature in the Transmission of Traditional Culture by Combining the Method of Internet Text Analysis","authors":"Bi Zhao","doi":"10.2478/amns.2023.2.01374","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01374","url":null,"abstract":"Abstract This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the dissemination of traditional culture by analyzing the embodiment of traditional culture in Chinese language literature network texts. The collection process of Chinese language and literature data in network text is analyzed from the perspective of textual data interaction. The information of node variables in a Bayesian network is used to determine the mutual relationship between Chinese language literature and traditional culture. The degree of interdependence between Chinese literature and traditional culture can be measured by combining mutual information. The results show that the correct rate of text recognition of the Bayesian text recognition model decreases slightly when the training samples are (100-300), but the correct rate always stays around 0.85, thus reflecting the effectiveness of the network recognition model in this paper. Chinese language literature has a certain role in the dissemination of traditional culture, which proves that Chinese language literature, as a carrier of traditional culture, can improve the dissemination speed of traditional culture. This study focuses on the integration of Chinese literature and traditional communication to improve a new vision.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"56 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138600596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01368
Xiong Yin
Abstract This paper constructs a model of the particle swarm algorithm, compares and analyzes the performance of the particle swarm algorithm under the two parameters of w and k in detail, and solves the constrained optimization problem by the particle swarm algorithm. On the basis of the local optimal value to find the global optimal value, the particle swarm algorithm is improved with reference to the particle’s motion state and behavior. Based on the particle swarm algorithm, a digital enterprise management system is constructed to plan enterprise management operations and optimize efficiency. Finally, we compare the performance of different algorithms in enterprise management risk prediction, analyze the correlation between the management system and enterprise management efficiency, and compare the management efficiency of different enterprises to explore the effect of the particle swarm algorithm in digital enterprise management. The results show that the predictive classification effect of the particle swarm algorithm model reaches more than 95% correct rate, and the management system of the particle swarm algorithm presents significance at 1% and 5% significance level for enterprise management efficiency, respectively.
{"title":"Research on the Innovative Application of Particle Swarm Algorithm in the Improvement of Management Efficiency of Digital Enterprises","authors":"Xiong Yin","doi":"10.2478/amns.2023.2.01368","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01368","url":null,"abstract":"Abstract This paper constructs a model of the particle swarm algorithm, compares and analyzes the performance of the particle swarm algorithm under the two parameters of w and k in detail, and solves the constrained optimization problem by the particle swarm algorithm. On the basis of the local optimal value to find the global optimal value, the particle swarm algorithm is improved with reference to the particle’s motion state and behavior. Based on the particle swarm algorithm, a digital enterprise management system is constructed to plan enterprise management operations and optimize efficiency. Finally, we compare the performance of different algorithms in enterprise management risk prediction, analyze the correlation between the management system and enterprise management efficiency, and compare the management efficiency of different enterprises to explore the effect of the particle swarm algorithm in digital enterprise management. The results show that the predictive classification effect of the particle swarm algorithm model reaches more than 95% correct rate, and the management system of the particle swarm algorithm presents significance at 1% and 5% significance level for enterprise management efficiency, respectively.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"21 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138598005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01352
Fengmei Shang, You Li
Abstract This paper analyzes the “encoder-decoder” framework in neural machine translation and clarifies that the task of natural language processing is sequence learning. Secondly, recurrent neural networks are used to combine the historical hidden layer output information with the current input information, which is specialized in processing sequence data to achieve good translation results. Applying the attention mechanism to the field of natural language processing, a Transformer model based on the full attention mechanism is constructed in order to achieve the purpose of translating the source language while also performing alignment operations on the target language. The evaluation and analysis of the Transformer model based on the full-attention mechanism concludes that the Transformer model has 0.0152 Pearson correlation coefficients higher than the Bilingual Expert model, which is also 2.92% higher than the Bilingual Expert model, with the participation of f feature in both models. This further proves the Transformer model’s ability to correctly and effectively translate English sentences. At the same time, it also shows that the application of natural language processing technology can improve the efficiency of English long-sentence translation and comprehensively improve the quality of long-sentence translation.
{"title":"Exploring English Long Sentence Translation Methods by Applying Natural Language Processing Techniques","authors":"Fengmei Shang, You Li","doi":"10.2478/amns.2023.2.01352","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01352","url":null,"abstract":"Abstract This paper analyzes the “encoder-decoder” framework in neural machine translation and clarifies that the task of natural language processing is sequence learning. Secondly, recurrent neural networks are used to combine the historical hidden layer output information with the current input information, which is specialized in processing sequence data to achieve good translation results. Applying the attention mechanism to the field of natural language processing, a Transformer model based on the full attention mechanism is constructed in order to achieve the purpose of translating the source language while also performing alignment operations on the target language. The evaluation and analysis of the Transformer model based on the full-attention mechanism concludes that the Transformer model has 0.0152 Pearson correlation coefficients higher than the Bilingual Expert model, which is also 2.92% higher than the Bilingual Expert model, with the participation of f feature in both models. This further proves the Transformer model’s ability to correctly and effectively translate English sentences. At the same time, it also shows that the application of natural language processing technology can improve the efficiency of English long-sentence translation and comprehensively improve the quality of long-sentence translation.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"11 9","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138600854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01376
Baiying Chen
Abstract This paper firstly analyzes the basic composition of intercultural communication ability, discusses the specific function of cultural promotion of urban tourism, and gives the promotion effect of intercultural communication on urban tourism. Secondly, the connotation of multimodal discourse analysis is given, and the technical analysis of text, audio, and visual features is carried out for the analysis of urban tourism discourse. Then, the TF-IDF algorithm is used to realize the feature extraction of tourism culture text, the MFCC algorithm is used to extract the audio features of tourism culture, and the modal classification network is used to realize the recognition of the visual features of urban tourism culture video. Finally, to verify the effectiveness of the application of multimodal discourse analysis in urban cross-cultural communication, three aspects were tested and analyzed respectively. The results show that the F1 value of the TF-IDF algorithm is 0.912, which is 17.07% higher than that of the CTF-TF-IDF algorithm. When the amount of audio recognition is 5GB, the recognition time of the MFCC audio recognition method is 10.4 s. When the weight value of the visual feature extraction network is set to 1.0, the highest visual feature extraction error rate is only 3.96%. Using multimodal discourse analysis to carry out urban tourism discourse analysis can realize more comprehensive urban tourism feature extraction, help tourists strengthen their tourism perception, and then promote the enhancement of urban cross-cultural communication ability.
{"title":"The Application of Multimodal Discourse Analysis in Urban Intercultural Communication","authors":"Baiying Chen","doi":"10.2478/amns.2023.2.01376","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01376","url":null,"abstract":"Abstract This paper firstly analyzes the basic composition of intercultural communication ability, discusses the specific function of cultural promotion of urban tourism, and gives the promotion effect of intercultural communication on urban tourism. Secondly, the connotation of multimodal discourse analysis is given, and the technical analysis of text, audio, and visual features is carried out for the analysis of urban tourism discourse. Then, the TF-IDF algorithm is used to realize the feature extraction of tourism culture text, the MFCC algorithm is used to extract the audio features of tourism culture, and the modal classification network is used to realize the recognition of the visual features of urban tourism culture video. Finally, to verify the effectiveness of the application of multimodal discourse analysis in urban cross-cultural communication, three aspects were tested and analyzed respectively. The results show that the F1 value of the TF-IDF algorithm is 0.912, which is 17.07% higher than that of the CTF-TF-IDF algorithm. When the amount of audio recognition is 5GB, the recognition time of the MFCC audio recognition method is 10.4 s. When the weight value of the visual feature extraction network is set to 1.0, the highest visual feature extraction error rate is only 3.96%. Using multimodal discourse analysis to carry out urban tourism discourse analysis can realize more comprehensive urban tourism feature extraction, help tourists strengthen their tourism perception, and then promote the enhancement of urban cross-cultural communication ability.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"80 5","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138600315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01361
Xue Wu
Abstract This paper analyzes the three-level inclusion relationship of high-level innovative talents and combs the structure of high-level scientific and technological talent evaluation models based on big data technology. Aiming at the evaluation problems of high-level scientific and technological talents, a fuzzy neural network model is constructed, and at the same time, the R&D middle school effect is utilized to evaluate the innovation achievements of high-level scientific and technological talents. Construct the evaluation index system of high-level scientific and technological innovative talents by utilizing 6 first-level indexes, 14 second-level indexes and 48 third-level indexes. Create a hierarchical analysis structure model, evaluate the indicator data through a judgment matrix and consistency test, and output the indicator weights. Analyze the relevance of the indicator model for different input layer neurons in fuzzy hierarchical analysis through comparative experiments. Use empirical analysis to analyze the innovative evaluation scores of high-level scientific and technological talents in Group A. The experimental results show that when the input layer contains 48 neurons, the loss value ranges from [0.132,1.765], the loss decreases the fastest, the stronger the indicator correlation, the stronger the generalization ability of the fuzzy neural network regression model. The overall scores of the evaluation of high-level scientific and technological talents of Group A for the first and second-level indicators are 3.54 and 3.869, respectively, and the overall view of Group A’s high-level scientific and technological talent innovative ability is better. Good.
{"title":"Research on the construction of evaluation system for high-level scientific and technological talents based on big data analysis","authors":"Xue Wu","doi":"10.2478/amns.2023.2.01361","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01361","url":null,"abstract":"Abstract This paper analyzes the three-level inclusion relationship of high-level innovative talents and combs the structure of high-level scientific and technological talent evaluation models based on big data technology. Aiming at the evaluation problems of high-level scientific and technological talents, a fuzzy neural network model is constructed, and at the same time, the R&D middle school effect is utilized to evaluate the innovation achievements of high-level scientific and technological talents. Construct the evaluation index system of high-level scientific and technological innovative talents by utilizing 6 first-level indexes, 14 second-level indexes and 48 third-level indexes. Create a hierarchical analysis structure model, evaluate the indicator data through a judgment matrix and consistency test, and output the indicator weights. Analyze the relevance of the indicator model for different input layer neurons in fuzzy hierarchical analysis through comparative experiments. Use empirical analysis to analyze the innovative evaluation scores of high-level scientific and technological talents in Group A. The experimental results show that when the input layer contains 48 neurons, the loss value ranges from [0.132,1.765], the loss decreases the fastest, the stronger the indicator correlation, the stronger the generalization ability of the fuzzy neural network regression model. The overall scores of the evaluation of high-level scientific and technological talents of Group A for the first and second-level indicators are 3.54 and 3.869, respectively, and the overall view of Group A’s high-level scientific and technological talent innovative ability is better. Good.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"125 24","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138599229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-05DOI: 10.2478/amns.2023.2.01355
Yongsheng Wang
Abstract This paper adjusts the coupling model to analyze the variables in order to measure the degree of coupling between overseas alumni donation behavior and university strategies. The entropy weighting method is used for the determination of indicator weights and systematic, comprehensive evaluation function. The replicated dynamic equations of alumni entrepreneurs and colleges and universities are explored separately to verify the relationship between the probability of alumni donations, the probability of colleges and universities willing to accept donations and the probability of entrepreneurs’ willingness to donate. To simulate the impact of three types of university incentive strategies, namely, tax incentives, reputational gains, and networking resources, on the donation decisions of overseas alumni and to explore the ranking of the three types of incentive strategies in a single incentive strategy implementation environment. In order to explore the cooperative evolution process of multi-channel coupling, the group structure, size, degree of interaction and cognition are modeled with appropriate parameterization, and the evolution results of the independent and coupled scenarios are compared. The simulation data show that in the environment of single university incentive strategy implementation, the ranking of incentive effects is, in order, tax benefits > networking resources > reputational gains.
{"title":"Exploring Strategies for Promoting Overseas Alumni Giving Activities in Colleges and Universities Based on Coupled Models","authors":"Yongsheng Wang","doi":"10.2478/amns.2023.2.01355","DOIUrl":"https://doi.org/10.2478/amns.2023.2.01355","url":null,"abstract":"Abstract This paper adjusts the coupling model to analyze the variables in order to measure the degree of coupling between overseas alumni donation behavior and university strategies. The entropy weighting method is used for the determination of indicator weights and systematic, comprehensive evaluation function. The replicated dynamic equations of alumni entrepreneurs and colleges and universities are explored separately to verify the relationship between the probability of alumni donations, the probability of colleges and universities willing to accept donations and the probability of entrepreneurs’ willingness to donate. To simulate the impact of three types of university incentive strategies, namely, tax incentives, reputational gains, and networking resources, on the donation decisions of overseas alumni and to explore the ranking of the three types of incentive strategies in a single incentive strategy implementation environment. In order to explore the cooperative evolution process of multi-channel coupling, the group structure, size, degree of interaction and cognition are modeled with appropriate parameterization, and the evolution results of the independent and coupled scenarios are compared. The simulation data show that in the environment of single university incentive strategy implementation, the ranking of incentive effects is, in order, tax benefits > networking resources > reputational gains.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":"111 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138599977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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