Journal of Computational Methods in Sciences and Engineering最新文献

{"title":"Malfunction diagnosis of main station of power metering system using LSTM-ResNet with SMOTE method","authors":"Qianqian Cai, Yong Sun, Youpeng Huang, Jingming Zhao, Jingru Li, Shiqi Yi","doi":"10.3233/jcm-226883","DOIUrl":"https://doi.org/10.3233/jcm-226883","url":null,"abstract":"The power metering system is an important part of the smart grid for data acquisition and analysis. The fault state of the main station directly affects the stable and safe operation of the power metering system. Hinged on the real-world data supplied by the monitoring platform of the Metrology Center of Guangdong Power Grid Co., Ltd., we present a novel malfunction diagnosis method for the main station of the power metering system. The proposed method utilizes the synthetic mi-nority over-sampling technique (SMOTE) and designs a combined model of long short-term memory (LSTM) network and ResNet. SMOTE solves the sample imbalance problem. Furthermore, the combined LSTM-ResNet model employs LSTM to extract the time-dependent signal feature and exploits ResNet to optimize data flow. Consequently, the proposed LSTM-ResNet model improves training efficiency and malfunction diagnosis accuracy. The proposed diagnosis mthod is verifird on the real-world data, which proves the proposed method’s surpass traditional methods. A specific analysis of results and the practical application of the proposed method is also elaborated.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2621-2633"},"PeriodicalIF":0.5,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041753","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}

{"title":"Research on the prediction of short time series based on EMD-LSTM","authors":"Yongzhi Liu, Gang Wu","doi":"10.3233/jcm-226860","DOIUrl":"https://doi.org/10.3233/jcm-226860","url":null,"abstract":"An algorithm based on EMD-LSTM (Empirical Mode Decision – Long Short Term Memory) is proposed for predicting short time series with uncertainty, rapid changes, and no following cycle. First, the algorithm eliminates the abnormal data; second, the processed time series are decomposed into basic modal components for different characteristic scales, which can be used for further prediction; finally, an LSTM neural network is used to predict each modal component, and the prediction results for each modal component are summed to determine a final prediction. Experiments are performed on the public datasets available at UCR and compared with a machine learning algorithm based on LSTMs and SVMs. Several experiments have shown that the proposed EMD-LSTM-based short-time series prediction algorithm performs better than LSTM and SVM prediction methods and provides a feasible method for predicting short-time series.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"22 1","pages":"2511-2524"},"PeriodicalIF":0.5,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041465","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}

{"title":"Economic growth factors of industrial and commercial enterprises in coastal cities based on the model of unexpected super efficiency","authors":"Huize Chen, Guixian Tian","doi":"10.3233/jcm-226852","DOIUrl":"https://doi.org/10.3233/jcm-226852","url":null,"abstract":"In order to improve the economic growth efficiency of industrial and commercial enterprises in coastal cities and realize the GDP growth of coastal cities, this paper studies the economic growth factors of industrial and commercial enterprises in coastal cities based on the unexpected super efficiency model. Based on the research and analysis of the previous economic growth theories, this paper finds out the main factors that affect the economic growth of industrial and commercial enterprises in coastal cities, and uses the advanced econometric method to establish the relevant test model to analyze the correlation between the time series of economic growth factors and the time series of coastal cities, so as to realize the economic growth factors of industrial and commercial enterprises in coastal cities Element study. The empirical results show that the main factors affecting the economic growth of industrial and commercial enterprises in coastal cities are capital and labor force, with labor force as the main body; Technical and institutional factors also contribute to the GDP of industrial and commercial enterprises in coastal cities, but the impact is not significant and needs further improvement. In general, these factors can promote the economic growth of industrial and commercial enterprises in coastal cities. The time series and time series of each factor variable are first-order non-stationary series with long-term cointegration relationship.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2795-2809"},"PeriodicalIF":0.5,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041497","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}

{"title":"Reliability control and calculation for agri-equipments based on an intelligent algorithm","authors":"Zhengmao Luo, Dachong Dong, Z. Cai, Y. Wan","doi":"10.3233/jcm-226885","DOIUrl":"https://doi.org/10.3233/jcm-226885","url":null,"abstract":"In the research, an agricultural machinery reliability analysis method based on fusion algorithm is proposed, a optimal radial basis function neural network and M-C statistical test method are mixed to obtain an agricultural machinery reliability. This mixed model is used to reliability design and calculation of a cotton picker, the simulation model of reliability control and calculation for a cotton picker based on the mixed algorithm is set up, and reliability of the level spindle of a cotton picker is computed through the mixed method, and the effect of important factors on the cotton picker is predicted. The level spindle is critical force-bearing parts of a cotton picker and breakdown occurs frequently, their reliability control and optimization are key problems that need to be solved urgently, this study builds an innovative approach for the reliability optimization and design of agricultural equipments.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2635-2643"},"PeriodicalIF":0.5,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041767","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}

{"title":"Predicament and strategy of campus football teaching under the background of artificial intelligence and deep learning","authors":"Chongjiang Zhan, Pengtao Cui","doi":"10.3233/jcm-226840","DOIUrl":"https://doi.org/10.3233/jcm-226840","url":null,"abstract":"In recent years, the application of artificial intelligence in various fields of education has increasingly become a social hotspot, and people have begun to use the research of artificial intelligence as a means to promote the development of education. Promoting teaching equality and improving the quality of education through AI is an important breakthrough in achieving educational development. Soccer is the number one sport in the world, and generally speaking the level of development of soccer indicates the level of development of sports in that country. This study combines artificial intelligence technology and deep learning methods with school soccer to solve school soccer development problems from a technical perspective, which has certain practical significance, fills the research gap in this field, and promotes the development of this field. Therefore, how to use artificial intelligence and deep learning to develop soccer teaching in schools is of great significance. The article proceeds according to the idea of asking questions to solve problems, this paper firstly explains the research on technologies such as artificial intelligence and deep learning, after that, we deeply investigate the dilemma of school soccer development, through questionnaire method and field interview method we come up with the current situation of low overall satisfaction of school soccer participation, concentration of participation grades and low level of skill learning, for which we propose to improve the underlying data of artificial intelligence for these problems, the Promote the integration of AI and education, and the development of AI in education driven by big data strategies. Finally, the research content of the paper is summarized. This paper is innovative and professional in addressing the dilemmas in education from a technical perspective.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2437-2449"},"PeriodicalIF":0.5,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041356","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}

{"title":"Exploiting social context awareness for intelligent data forwarding in social Internet of Things","authors":"Min Deng, Fang Xu, Z. Xiong, Qiong Xu, Z. Liu, Hairu Guo","doi":"10.3233/jcm-226833","DOIUrl":"https://doi.org/10.3233/jcm-226833","url":null,"abstract":"In the social internet of things, community structure exists objectively and affects the transmission of network messages. If the social context such as community is fully utilized, the efficiency of data forwarding will be effectively improved. A community-based routing algorithm (MSAR) is proposed by studying the multiple social relationships. First, we propose four measures of social relationships. They are social closeness degree, in-community activeness, cross-community activeness and community interaction. Then, the design of routing algorithm considers two stages. One is in-community forwarding and the other is cross-community forwarding. The measurement of node forwarding capability depends on closeness degree and in-community activeness in the in-community forwarding stage. In the cross-community stage, the measurement of node forwarding capability depends on closeness degree, cross-community activeness and community interaction. The relay node with higher cross-community forwarding utility will be selected. This prevents messages from being limited to the local community. Therefore, messages can always travel in the direction of the destination node’s community. Finally, a lot of simulation experiments and analyses are carried out. The analysis results show that the proposed algorithm has good performance in the following two aspects, the average latency and the message delivery rate respectively.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2361-2375"},"PeriodicalIF":0.5,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041290","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}

{"title":"Global optimisation matching method for multi-representation buildings constrained by road network","authors":"Guowei Luo, K. Qin","doi":"10.3233/jcm-226820","DOIUrl":"https://doi.org/10.3233/jcm-226820","url":null,"abstract":"Entity matching is one of the key technologies for geospatial data update and fusion. In response to the shortcomings of most spatial entity matching methods that use local optimisation strategies, a global optimisation matching method for multi-representation buildings using road network constraints is proposed. First, the road network is used for region segmentation to obtain candidate matches. Second, the spatial similarity among the candidate matching objects is calculated and the characteristic similarity weights are determined using the entropy weight method. Third, the matching of building entities is transformed into an allocation problem using integer programming ideas, and the Hungarian algorithm is solved to obtain the optimal matching combination with minimum global variance. Finally, two test areas are selected to validate the proposed method, and the precision, recall, and F-measure values of the experiments are 96.35%, 97.11%, and 96.73% versus 95.96%, 97.03%, and 96.49%, respectively. The matching accuracy is greatly improved compared with the local search strategy.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2413-2424"},"PeriodicalIF":0.5,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041135","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}

{"title":"Influence of mobile technology and smart classroom environment on learning engagement","authors":"Bingzhuan Peng","doi":"10.3233/jcm-226827","DOIUrl":"https://doi.org/10.3233/jcm-226827","url":null,"abstract":"To expand the application of mobile technology and smart classroom environment in education, and explore their influence on learning engagement, this paper, based on the Situated Cognition Theory, took 296 sophomores from six universities in China as the research objects and investigated the relationship between mobile technology, smart classroom environment, and learning engagement. The findings show that: (1) in the mobile technology and smart classroom environment, the frequency of learning by mobile devices in class, the frequency of learning by mobile devices after class, the duration of learning by mobile devices in class, the duration of learning by mobile devices after class, the hardware environment, software resources, and technology acceptance have positive effects on learning engagement; (2) mobile technology and smart classroom environment can better mobilize learners’ interest and initiative in learning and increase learners’ engagement in learning; (3) mobile technology and smart classroom environment can greatly improve college learners’ behavioural engagement, emotional engagement, and cognitive engagement respectively. This study helps turn the learners’ external learning needs into their internal learning motivation, thus enhancing their learning engagement.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2323-2333"},"PeriodicalIF":0.5,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041176","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}

{"title":"High-dimensional robust principal component analysis and its applications","authors":"Xiaobo Jiang, Jie Gao, Zhongming Yang","doi":"10.3233/jcm-226829","DOIUrl":"https://doi.org/10.3233/jcm-226829","url":null,"abstract":"Principal component analysis method is one of the most widely used statistical procedures for data dimension reduction. The traditional principal component analysis method is sensitive to outliers since it is based on the sample covariance matrix. Meanwhile, the deviation of the principal component analysis based on the Minimum Covariance Determinant (MCD) estimation is significantly increased as the data dimension increases. In this paper, we propose a high-dimensional robust principal component analysis based on the Rocke estimator. Simulation studies and a real data analysis illustrate that the finite sample performance of the proposed method is significantly better than those of the existing methods.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2303-2311"},"PeriodicalIF":0.5,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041271","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}

{"title":"Construction of the flipped classroom teaching mode of British and American literature in the context of big data and IoT","authors":"Xiangnan Xu, Shuhui Shi","doi":"10.3233/jcm-226816","DOIUrl":"https://doi.org/10.3233/jcm-226816","url":null,"abstract":"With the advancement of cultural globalization, China has increased its support for the study of British and American literature. However, due to the great differences in the forms of expression and thinking logic between British and American literature and Chinese local literature, it is difficult for Chinese students to learn British and American literature. In order to solve the dilemma of Chinese students learning English and American literature, the team constructed a smart classroom model with flipped classroom as the core based on big data and Internet of Things technology. The smart classroom model is constructed according to the four-layer architecture of the Internet of Things, which is divided into perception layer, network layer, platform layer and application layer. The flipped classroom is in the application layer. The flipped classroom is designed according to the three processes before, during and after class, which has certain theoretical significance. In order to verify the effectiveness of this model, a university in H city was selected for research. Through the control experiment, it was concluded that within a certain error range, the flipped classroom teaching mode can significantly improve the teaching effect of British and American literature compared with the traditional teaching mode. Finally, based on the problems of English and American literature learning, we further deepen the model of flipped classroom. In the pre-course pre-study stage, teachers should play their organizational role and enhance students’ pre-study effect through interesting pre-study methods. Teachers should also pay attention to students’ pre-study status and make timely adjustments. In the classroom, teachers need to find students’ questions in time and answer common questions in a unified manner and answer individual questions in private, in an effort to improve classroom efficiency and promote the process of internalizing students’ knowledge. At the end of the flipped classroom, the classroom should also summarize the lesson, recognize the strengths and weaknesses of the lesson implementation based on the feedback from the students, and clarify the room for improvement of the lesson. At the same time, teachers should also reflect on the flipped classroom model and comprehensively assess its strengths and weaknesses to ensure that this model can be applied to its full value.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2451-2461"},"PeriodicalIF":0.5,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041078","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}