In the digital landscape, the language of ideological and political education for college students acquires new dimensions and faces unique challenges. Through the analysis of survey data from 1,025 college students, employing the K-prototype clustering algorithm and an enhancement of the Apriori algorithm, this study explores the significant influence of language on students’ emotional and cognitive responses. A striking 90% of participants displayed a strong affinity for media promoting patriotic themes, while over 52% regularly engaged in political discourse, highlighting the language’s potent effect on shaping civic attitudes. Nevertheless, the findings also suggest a pressing need to refine the linguistic approach regarding style and substance to maximize educational outcomes. By examining the contemporary role of language in shaping ideological and political perspectives among students, this paper sheds light on avenues for optimizing educational strategies in the Internet era.
在数字化环境下，大学生思想政治教育的语言获得了新的维度，面临着独特的挑战。本研究通过对 1025 名大学生的调查数据进行分析，采用 K 原型聚类算法和 Apriori 算法的增强版，探讨了语言对大学生情感和认知反应的重要影响。令人吃惊的是，90% 的参与者对宣传爱国主题的媒体表现出强烈的亲和力，而超过 52% 的参与者经常参与政治讨论，这凸显了语言在塑造公民态度方面的强大作用。不过，研究结果也表明，迫切需要完善有关风格和实质内容的语言方法，以最大限度地提高教育成果。通过研究语言在塑造学生意识形态和政治观点方面的当代作用，本文揭示了在互联网时代优化教育战略的途径。
{"title":"Research on the Language Value of College Students’ Ideological and Political Education in the Internet Era","authors":"Sang Zha","doi":"10.2478/amns-2024-0814","DOIUrl":"https://doi.org/10.2478/amns-2024-0814","url":null,"abstract":"\u0000 In the digital landscape, the language of ideological and political education for college students acquires new dimensions and faces unique challenges. Through the analysis of survey data from 1,025 college students, employing the K-prototype clustering algorithm and an enhancement of the Apriori algorithm, this study explores the significant influence of language on students’ emotional and cognitive responses. A striking 90% of participants displayed a strong affinity for media promoting patriotic themes, while over 52% regularly engaged in political discourse, highlighting the language’s potent effect on shaping civic attitudes. Nevertheless, the findings also suggest a pressing need to refine the linguistic approach regarding style and substance to maximize educational outcomes. By examining the contemporary role of language in shaping ideological and political perspectives among students, this paper sheds light on avenues for optimizing educational strategies in the Internet era.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140521284","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}
In the 21st century, computer technology covers human daily life, including the field of music. This paper uses a quaternion algorithm to describe the gesture posture during piano playing. Combined with the iteratively updated and extended IU-EKF algorithm, it realizes the fusion of piano playing gestures to fix the posture. The recognized piano playing gestures are output to the chord fingering automatic annotation board, the piano audio signal data are preprocessed and input to the 3D space, the annotation area is allocated, and the chord fingering features are extracted using the Boltzmann machine. Through spectral analysis and empirical investigation, we analyze the sound quality effect of the two pianos and the audience’s listening experience. The results show that in the spectral analysis of the two pianos, the time-domain waveforms of the pianos played using the gestures proposed in this paper have durations ranging from 0.75s to 1.25s, and the waveform graphs present triangular shapes, which are better in terms of sound quality. The listeners’ melodic memory of the songs played by two pianos is the best for the two pianos of Chinese art and folk songs, Chinese art and Chinese pop, with the average difference of 5.7899 and 5.6345 respectively. The two pianos form of playing can satisfy the listener’s need of listening to the piano songs to a certain extent.
{"title":"The Importance of Dual Piano Performance Forms in Piano Performance in the Context of Deep Learning","authors":"Linxi Yang","doi":"10.2478/amns-2024-0370","DOIUrl":"https://doi.org/10.2478/amns-2024-0370","url":null,"abstract":"\u0000 In the 21st century, computer technology covers human daily life, including the field of music. This paper uses a quaternion algorithm to describe the gesture posture during piano playing. Combined with the iteratively updated and extended IU-EKF algorithm, it realizes the fusion of piano playing gestures to fix the posture. The recognized piano playing gestures are output to the chord fingering automatic annotation board, the piano audio signal data are preprocessed and input to the 3D space, the annotation area is allocated, and the chord fingering features are extracted using the Boltzmann machine. Through spectral analysis and empirical investigation, we analyze the sound quality effect of the two pianos and the audience’s listening experience. The results show that in the spectral analysis of the two pianos, the time-domain waveforms of the pianos played using the gestures proposed in this paper have durations ranging from 0.75s to 1.25s, and the waveform graphs present triangular shapes, which are better in terms of sound quality. The listeners’ melodic memory of the songs played by two pianos is the best for the two pianos of Chinese art and folk songs, Chinese art and Chinese pop, with the average difference of 5.7899 and 5.6345 respectively. The two pianos form of playing can satisfy the listener’s need of listening to the piano songs to a certain extent.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140516956","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}
Currently, the impact of population aging on economic development is mainly explored from the dimension of time, ignoring the Heterogeneity between the two. In this paper, we start by measuring the regional economic development level index, use the entropy value method to solve the index weights, and calculate the regional economic development level index using the linear weighting method. The regional development level index is used as an explanatory variable to construct the baseline regression model and the dynamic panel model for the change in the age structure of the elderly population. The panel data of 31 provinces (cities/autonomous regions) in China are used as examples to explore the heterogeneous effects of age structure changes on regional economic development of the elderly population. The results show that when the age structure change of the elderly population increases by 1%, the regional economic development level rises by 0.782%, and the age structure change of the elderly population is positively and significantly affecting the quality of economic development in the central and western regions at the 1% level. The regression coefficient of population aging in the low level stage is 0.007. The effect on the regional economic development level is significantly positive at the 1%. The age structure change of the elderly population affects the regional economic development by mediating health consumption expenditure. The age structure change of the elderly population has Heterogeneity in regional economic development in terms of period, region, and level at different stages.
{"title":"The Heterogeneous Impact of Changes in the Age Structure of China’s Elderly Population on Regional Economic Development","authors":"Yi Zhang","doi":"10.2478/amns-2024-0690","DOIUrl":"https://doi.org/10.2478/amns-2024-0690","url":null,"abstract":"\u0000 Currently, the impact of population aging on economic development is mainly explored from the dimension of time, ignoring the Heterogeneity between the two. In this paper, we start by measuring the regional economic development level index, use the entropy value method to solve the index weights, and calculate the regional economic development level index using the linear weighting method. The regional development level index is used as an explanatory variable to construct the baseline regression model and the dynamic panel model for the change in the age structure of the elderly population. The panel data of 31 provinces (cities/autonomous regions) in China are used as examples to explore the heterogeneous effects of age structure changes on regional economic development of the elderly population. The results show that when the age structure change of the elderly population increases by 1%, the regional economic development level rises by 0.782%, and the age structure change of the elderly population is positively and significantly affecting the quality of economic development in the central and western regions at the 1% level. The regression coefficient of population aging in the low level stage is 0.007. The effect on the regional economic development level is significantly positive at the 1%. The age structure change of the elderly population affects the regional economic development by mediating health consumption expenditure. The age structure change of the elderly population has Heterogeneity in regional economic development in terms of period, region, and level at different stages.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140524574","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}
In the context of the information age, accelerating the modernization of rural governance has become the focus of social attention. This paper adopts the coupled coordination degree model. It applies the coefficient of variation method to standardize the evaluation index data, thus establishing a spatial measurement model for in-depth analysis of rural governance. This paper constructs a modernization evaluation index model, including five main evaluation indexes, including industrial modernization, ecological excellence, cultural modernization, effective governance, and affluent life, to form a comprehensive rural governance modernization evaluation system. Hunan Province in China is the case study, and this study explores its rural governance modernization level in detail. The results show that the development level of rural governance modernization in Hunan Province is higher than the average value of the composite index of the six central provinces, which is 0.4701. In developing rural governance modernization indicators, the indicators generally show an upward trend, with an increase of 8.7%, 5.66%, 16.43%, 4.79%, and 13.84%, respectively. However, the indicators of effective governance and cultural modernization have become the main obstacles to the modernization of rural governance in Hunan Province, with the combined obstacle degree of these two indicators reaching 67.92%. This study not only provides a practical evaluation tool and method for rural governance modernization, but also provides specific data support and policy recommendations for developing rural governance modernization in Hunan Province, which helps to promote the process of modernizing regional rural governance.
{"title":"Study on the Construction of Evaluation Indicator System and Level Measurement of Rural Governance Modernization in the Information Age","authors":"Yuanping Cao","doi":"10.2478/amns-2024-0640","DOIUrl":"https://doi.org/10.2478/amns-2024-0640","url":null,"abstract":"\u0000 In the context of the information age, accelerating the modernization of rural governance has become the focus of social attention. This paper adopts the coupled coordination degree model. It applies the coefficient of variation method to standardize the evaluation index data, thus establishing a spatial measurement model for in-depth analysis of rural governance. This paper constructs a modernization evaluation index model, including five main evaluation indexes, including industrial modernization, ecological excellence, cultural modernization, effective governance, and affluent life, to form a comprehensive rural governance modernization evaluation system. Hunan Province in China is the case study, and this study explores its rural governance modernization level in detail. The results show that the development level of rural governance modernization in Hunan Province is higher than the average value of the composite index of the six central provinces, which is 0.4701. In developing rural governance modernization indicators, the indicators generally show an upward trend, with an increase of 8.7%, 5.66%, 16.43%, 4.79%, and 13.84%, respectively. However, the indicators of effective governance and cultural modernization have become the main obstacles to the modernization of rural governance in Hunan Province, with the combined obstacle degree of these two indicators reaching 67.92%. This study not only provides a practical evaluation tool and method for rural governance modernization, but also provides specific data support and policy recommendations for developing rural governance modernization in Hunan Province, which helps to promote the process of modernizing regional rural governance.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140527260","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}
Currently, in the production of cigarettes in the blade, charging export moisture control means is relatively single and can not effectively guarantee the excellent quality of cigarette filament. In this paper, first of all, the working principle of the tobacco blade charging machine is introduced, and the moisture of the tobacco leaf for the charging machine is dynamically analyzed, and the influence of the return air temperature control of the charging machine on the export moisture of the blade charging process is explored. Secondly, based on the traditional PID controller, an adaptive fuzzy PID controller is established by combining adaptive fuzzy rules, and then the stacked noise-reducing self-encoder in deep learning is combined with the adaptive fuzzy PID control to design the intelligent control structure of export moisture of leaf charging process. Finally, the effectiveness of export moisture intelligence control, process capability index, and the effect before and after application were analyzed in controlled experiments, respectively. The results show that the difference between the predicted value and the real value of blade export moisture in this paper’s method is only 0.5%, and the process capability index of this paper’s method is improved by 1.48 compared with the PID controller, and it can control the temperature of the return air of the charging machine in the range of 56.86℃~57.21℃. The intelligent control method of export moisture introduced by deep learning can accurately control the export moisture of the leaf dosing process, which effectively ensures the quality of tobacco filament making.
{"title":"Deep learning-based intelligent control of moisture at the exit of blade charging process in cigarette production","authors":"Jinsheng Rui, Dongchen Qiu, Shicong Hou, Jing Rong, Xiaoxiao Qin, Jianan Fan, Kai Wu, Guoliang Zhao, Chengwen Zhu","doi":"10.2478/amns-2024-0026","DOIUrl":"https://doi.org/10.2478/amns-2024-0026","url":null,"abstract":"\u0000 Currently, in the production of cigarettes in the blade, charging export moisture control means is relatively single and can not effectively guarantee the excellent quality of cigarette filament. In this paper, first of all, the working principle of the tobacco blade charging machine is introduced, and the moisture of the tobacco leaf for the charging machine is dynamically analyzed, and the influence of the return air temperature control of the charging machine on the export moisture of the blade charging process is explored. Secondly, based on the traditional PID controller, an adaptive fuzzy PID controller is established by combining adaptive fuzzy rules, and then the stacked noise-reducing self-encoder in deep learning is combined with the adaptive fuzzy PID control to design the intelligent control structure of export moisture of leaf charging process. Finally, the effectiveness of export moisture intelligence control, process capability index, and the effect before and after application were analyzed in controlled experiments, respectively. The results show that the difference between the predicted value and the real value of blade export moisture in this paper’s method is only 0.5%, and the process capability index of this paper’s method is improved by 1.48 compared with the PID controller, and it can control the temperature of the return air of the charging machine in the range of 56.86℃~57.21℃. The intelligent control method of export moisture introduced by deep learning can accurately control the export moisture of the leaf dosing process, which effectively ensures the quality of tobacco filament making.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140524978","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}
The construction of the evaluation system of English translation teaching in colleges and universities under the cross-cultural perspective to improve the quality of translation education. The focus is on integrating the LMBP neural network algorithm and quantitative judgment indexes to provide an adequate evaluation model for English translation teaching. The study adopts the neural network algorithm based on LMBP, combined with the quantitative processing methods of “AHP+DEA” and “Entropy Assignment Method+Euclidean Distance Method”, to systematically construct and empirically analyze the evaluation indexes of teaching. It is found that teaching construction, application and effect are the core indicators of evaluation. Regarding teaching construction, classroom content integrity (correlation coefficient 0.428) and learning resources integrity (correlation coefficient 0.439) are the key factors. Teaching application analysis showed that hybrid teaching positively correlated with student achievement (r=0.569). Conducting effectiveness analysis showed that student discussion and in-class performance were significantly and positively correlated with teaching evaluation (p<0.005). These results prove the effectiveness and usefulness of the constructed evaluation system.
{"title":"Construction of Evaluation System for English Translation Teaching in Colleges and Universities under Cross-cultural Perspective","authors":"Tong He","doi":"10.2478/amns-2024-0653","DOIUrl":"https://doi.org/10.2478/amns-2024-0653","url":null,"abstract":"\u0000 The construction of the evaluation system of English translation teaching in colleges and universities under the cross-cultural perspective to improve the quality of translation education. The focus is on integrating the LMBP neural network algorithm and quantitative judgment indexes to provide an adequate evaluation model for English translation teaching. The study adopts the neural network algorithm based on LMBP, combined with the quantitative processing methods of “AHP+DEA” and “Entropy Assignment Method+Euclidean Distance Method”, to systematically construct and empirically analyze the evaluation indexes of teaching. It is found that teaching construction, application and effect are the core indicators of evaluation. Regarding teaching construction, classroom content integrity (correlation coefficient 0.428) and learning resources integrity (correlation coefficient 0.439) are the key factors. Teaching application analysis showed that hybrid teaching positively correlated with student achievement (r=0.569). Conducting effectiveness analysis showed that student discussion and in-class performance were significantly and positively correlated with teaching evaluation (p<0.005). These results prove the effectiveness and usefulness of the constructed evaluation system.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140520379","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}
This study utilizes the Larsen-Freeman three-dimensional theory of grammar teaching to quantitatively analyze the grammatical attributes “form”, “meaning” and “usage” in the Chinese writing process. The study uses the PCFG model to extract the syntactic dependency tree and represents the features of the tree structure with the help of TF-IDF. Meanwhile, the Transformer model extracts the semantic and syntactic features of sentences. At the same time, the positional encoder is removed to ensure that the model obtains information from the syntactic level. Further, an unsupervised method for generating grammatical textual recapitulation for Chinese Writing is proposed, as well as a Grammar Tree Generator for generating recapitulated sentences, which efficiently extracts the features of the input grammatical sequences. In addition, the study also includes writing feature analysis based on grammatical function matching, using a hierarchical clustering algorithm to analyze the similarity of 60 grammatical functions. Finally, validation was performed on 30 Chinese writing text collections, each containing 10 compositions, and the results showed high accuracy of unlabeled grammatical function recognition. The LDA model determined the optimal number of writing topics to be 150. This study highlights the potential application of intelligent analysis techniques in improving the quality of Chinese Writing. It provides new perspectives for an in-depth understanding of the interplay between grammatical structures and functions in the Chinese writing.
{"title":"Algorithm Design and Application of Grammatical Structure and Function Learning in Chinese Writing for Intelligent Analysis","authors":"Jingtao Ma, Liang Chen","doi":"10.2478/amns-2024-0500","DOIUrl":"https://doi.org/10.2478/amns-2024-0500","url":null,"abstract":"\u0000 This study utilizes the Larsen-Freeman three-dimensional theory of grammar teaching to quantitatively analyze the grammatical attributes “form”, “meaning” and “usage” in the Chinese writing process. The study uses the PCFG model to extract the syntactic dependency tree and represents the features of the tree structure with the help of TF-IDF. Meanwhile, the Transformer model extracts the semantic and syntactic features of sentences. At the same time, the positional encoder is removed to ensure that the model obtains information from the syntactic level. Further, an unsupervised method for generating grammatical textual recapitulation for Chinese Writing is proposed, as well as a Grammar Tree Generator for generating recapitulated sentences, which efficiently extracts the features of the input grammatical sequences. In addition, the study also includes writing feature analysis based on grammatical function matching, using a hierarchical clustering algorithm to analyze the similarity of 60 grammatical functions. Finally, validation was performed on 30 Chinese writing text collections, each containing 10 compositions, and the results showed high accuracy of unlabeled grammatical function recognition. The LDA model determined the optimal number of writing topics to be 150. This study highlights the potential application of intelligent analysis techniques in improving the quality of Chinese Writing. It provides new perspectives for an in-depth understanding of the interplay between grammatical structures and functions in the Chinese writing.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140525014","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}
Jing Bai, Jianlin Jiao, Meng Han, Xianfei Zhou, Chao Liu
Substation network security is the key to maintaining the stable operation of power systems. In the face of growing threats of network attacks, traditional security protection measures have been brutal to meet the needs of modern power systems. Research on substation network security, situational awareness strategies, and remote operation and maintenance of equipment is essential to improve network defense capability and ensure the continuity and reliability of power supply. This study explores effective security situational awareness methods and remote operation and maintenance techniques to provide new solutions for substation network security. This paper builds an efficient network attack detection model by introducing linear discriminant analysis (LDA) and radial basis function (RBF) neural networks. The experiment uses the KDD Cup99 dataset, which is preprocessed to provide the model training and testing data. The LDA-RBF model in this paper outperforms the traditional RNF neural and BP neural networks regarding recognition rate. Specifically, the recognition rate reaches 90.2% for the Smurf attack and 100% for the Ipsweep attack. The proposed model of the study also performs well in terms of leakage and false alarm rates, with an overall recognition rate of 97.00%. This study proposes a network security situational awareness strategy and equipment remote operation and maintenance method that can effectively enhance substation networks’ security and operation and maintenance efficiency.
{"title":"Research on Substation Network Security Situational Awareness Strategy and Equipment Remote Operation and Maintenance","authors":"Jing Bai, Jianlin Jiao, Meng Han, Xianfei Zhou, Chao Liu","doi":"10.2478/amns-2024-0714","DOIUrl":"https://doi.org/10.2478/amns-2024-0714","url":null,"abstract":"\u0000 Substation network security is the key to maintaining the stable operation of power systems. In the face of growing threats of network attacks, traditional security protection measures have been brutal to meet the needs of modern power systems. Research on substation network security, situational awareness strategies, and remote operation and maintenance of equipment is essential to improve network defense capability and ensure the continuity and reliability of power supply. This study explores effective security situational awareness methods and remote operation and maintenance techniques to provide new solutions for substation network security. This paper builds an efficient network attack detection model by introducing linear discriminant analysis (LDA) and radial basis function (RBF) neural networks. The experiment uses the KDD Cup99 dataset, which is preprocessed to provide the model training and testing data. The LDA-RBF model in this paper outperforms the traditional RNF neural and BP neural networks regarding recognition rate. Specifically, the recognition rate reaches 90.2% for the Smurf attack and 100% for the Ipsweep attack. The proposed model of the study also performs well in terms of leakage and false alarm rates, with an overall recognition rate of 97.00%. This study proposes a network security situational awareness strategy and equipment remote operation and maintenance method that can effectively enhance substation networks’ security and operation and maintenance efficiency.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140520002","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}
By analyzing the dust safety of open-pit mines, five primary indicators and 20 secondary indicators are determined for evaluation, and the subjective weights determined by the hierarchical analysis method and the objective weights determined by the entropy weighting method are combined to determine the subjective and objective weights; the scores of experts are integrated using fuzzy numbers to determine the final scores, and the combination of the two is used to construct the evaluation model of the dust safety of open-pit mines. Taking three mines as an example, the results show that the open pit mine dust safety of Mine is A 1 significantly better than that of the remaining two mines. The study shows that the model is suitable for open pit mine dust safety evaluation, considering the typical characteristics of subjectivity and objectivity, better reflecting the intention of the decision makers and the actual importance of the indicators, and making the results more scientific and objective. The proposed method provides a reference for determining dust safety in open pit mines.
{"title":"A safety evaluation model of open-pit mine dust based on subjective and objective weighting method","authors":"Jun Li","doi":"10.2478/amns-2024-0329","DOIUrl":"https://doi.org/10.2478/amns-2024-0329","url":null,"abstract":"\u0000 By analyzing the dust safety of open-pit mines, five primary indicators and 20 secondary indicators are determined for evaluation, and the subjective weights determined by the hierarchical analysis method and the objective weights determined by the entropy weighting method are combined to determine the subjective and objective weights; the scores of experts are integrated using fuzzy numbers to determine the final scores, and the combination of the two is used to construct the evaluation model of the dust safety of open-pit mines. Taking three mines as an example, the results show that the open pit mine dust safety of Mine is A\u0000 1 significantly better than that of the remaining two mines. The study shows that the model is suitable for open pit mine dust safety evaluation, considering the typical characteristics of subjectivity and objectivity, better reflecting the intention of the decision makers and the actual importance of the indicators, and making the results more scientific and objective. The proposed method provides a reference for determining dust safety in open pit mines.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140520004","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}
In recent years, rural tourism has developed rapidly and has become an important growth point for rural tourism economic development. This paper is based on the fuzzy comprehensive evaluation method to construct the evaluation indexes and evaluation levels of rural tourism development suitability, taking the rural tourism development suitability of place Z from 2016 to 2020 as the research object, combining the analysis of gray correlation and gray fuzzy comprehensive evaluation calculation to get the weights of the indicators, the comprehensive scores and the level results of each year, and scoring and analyzing the suitability of the tourism of the 15 villages of place Z, and dividing these rural tourism suitability were divided into different levels. The score of rural tourism development suitability in Land Z during 2016-2020 showed an overall increasing trend, and the rate of increase in 2018 was 6.76%, which was the fastest rate of improvement. Economic development receives the highest weighting among first-level indicators with 0.837, followed by tourism resources, infrastructure, and human resources with 0.758 and 0.734, respectively. In terms of the overall composite score, the tourism suitability of 2016-2020 has increased as a whole, and the composite scores of 2017 and 2018 are both greater than 0.7, with an evaluation grade of “medium”, and the comprehensive scores of 2018-2020 are all greater than 0.8, with an evaluation grade of “good”.
{"title":"Empirical research on the suitability of rural tourism development based on fuzzy comprehensive evaluation method","authors":"Binbin Zhang, Shiheng Yang","doi":"10.2478/amns-2024-0119","DOIUrl":"https://doi.org/10.2478/amns-2024-0119","url":null,"abstract":"\u0000 In recent years, rural tourism has developed rapidly and has become an important growth point for rural tourism economic development. This paper is based on the fuzzy comprehensive evaluation method to construct the evaluation indexes and evaluation levels of rural tourism development suitability, taking the rural tourism development suitability of place Z from 2016 to 2020 as the research object, combining the analysis of gray correlation and gray fuzzy comprehensive evaluation calculation to get the weights of the indicators, the comprehensive scores and the level results of each year, and scoring and analyzing the suitability of the tourism of the 15 villages of place Z, and dividing these rural tourism suitability were divided into different levels. The score of rural tourism development suitability in Land Z during 2016-2020 showed an overall increasing trend, and the rate of increase in 2018 was 6.76%, which was the fastest rate of improvement. Economic development receives the highest weighting among first-level indicators with 0.837, followed by tourism resources, infrastructure, and human resources with 0.758 and 0.734, respectively. In terms of the overall composite score, the tourism suitability of 2016-2020 has increased as a whole, and the composite scores of 2017 and 2018 are both greater than 0.7, with an evaluation grade of “medium”, and the comprehensive scores of 2018-2020 are all greater than 0.8, with an evaluation grade of “good”.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140518772","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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