Journal of Computational Methods in Sciences and Engineering最新文献_第8页

Neural network-based motion vector estimation algorithm for dynamic image sequences 基于神经网络的动态图像序列运动矢量估计算法

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226848

Yongjian Zhang

{"title":"Neural network-based motion vector estimation algorithm for dynamic image sequences","authors":"Yongjian Zhang","doi":"10.3233/jcm-226848","DOIUrl":"https://doi.org/10.3233/jcm-226848","url":null,"abstract":"With the rapid development of deep learning, convolutional neural networks have gradually become the main means to extract features of dynamic image sequences. The motion vector estimation algorithm, as the key to the stability of image sequences, directly affects the performance of image stabilization systems, so the motion estimation algorithm for convolutional neural networks is necessary. The study proposes an improved convolutional neural network based on loss-free function, and applies it to the extraction of dynamic image features. On this basis, the motion estimation algorithm is then optimised by combining grey-scale projection and block matching methods. The experimental results show that the new loss-free function-based convolutional neural network has better recognition capability with an error rate of only 15% in dynamic image recognition. The accuracy of the optimised motion estimation algorithm is as high as 95.1% with a PSNR value of 16.636, which is higher than that of the traditional grey-scale projection algorithm. In terms of video processing, the improved algorithm has a higher PSNR value than the search block matching method, the bit-plane matching method and the full search block matching method, with a higher steady image accuracy and high operational efficiency, providing a new research idea for the improvement of motion estimation algorithms. In general, the proposed algorithm is a significant improvement over the current mainstream algorithms in terms of image accuracy, processing performance and number of operations, and it provides a new research idea for the improvement of motion estimation algorithms.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2347-2360"},"PeriodicalIF":0.5,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041440","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}

引用次数: 0

A speech enhancement method combining beamforming with RNN for hearing aids 一种将波束成形与RNN相结合的助听器语音增强方法

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226897

Zhiqian Qiu, Fei Chen, Junyu Ji

引用次数: 0

Malfunction diagnosis of main station of power metering system using LSTM-ResNet with SMOTE method 基于SMOTE方法的LSTM-ResNet电力计量系统主站故障诊断

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226883

Qianqian Cai, Yong Sun, Youpeng Huang, Jingming Zhao, Jingru Li, Shiqi Yi

{"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}

引用次数: 0

Research on the prediction of short time series based on EMD-LSTM 基于EMD-LSTM的短时间序列预测研究

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226860

Yongzhi Liu, Gang Wu

引用次数: 0

Economic growth factors of industrial and commercial enterprises in coastal cities based on the model of unexpected super efficiency 基于非预期超效率模型的沿海城市工商业经济增长要素分析

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226852

Huize Chen, Guixian Tian

{"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}

引用次数: 0

The investigation of a fuzzy-internal mode PID-based temperature control system for solid state electric storage heaters 基于模糊内模pid的固态蓄热器温度控制系统研究

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226856

Chunlei Liu, Yi Wang, Mengru Zhang, Peng Wang, Shaokai Liu, W. Wu, Yong Sun

引用次数: 0

Reliability control and calculation for agri-equipments based on an intelligent algorithm 基于智能算法的农业设备可靠性控制与计算

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-31 DOI: 10.3233/jcm-226885

Zhengmao Luo, Dachong Dong, Z. Cai, Y. Wan

引用次数: 0

Predicament and strategy of campus football teaching under the background of artificial intelligence and deep learning 人工智能与深度学习背景下校园足球教学的困境与策略

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-30 DOI: 10.3233/jcm-226840

Chongjiang Zhan, Pengtao Cui

{"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}

引用次数: 0

Exploiting social context awareness for intelligent data forwarding in social Internet of Things 利用社会情境感知实现社交物联网智能数据转发

IF 0.5

Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-30 DOI: 10.3233/jcm-226833

Min Deng, Fang Xu, Z. Xiong, Qiong Xu, Z. Liu, Hairu Guo

{"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}

引用次数: 0

Global optimisation matching method for multi-representation buildings constrained by road network 路网约束下多表征建筑的全局优化匹配方法

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Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-05-29 DOI: 10.3233/jcm-226820

Guowei Luo, K. Qin

引用次数: 1