Pub Date : 2022-10-12DOI: 10.1080/21642583.2022.2110539
Wenshuai Lin, Bin Zhang, Hongyi Li, Renquan Lu
ABSTRACT In order to realize short-time load forecasting, an Adaboost-BP method with a weight update mechanism is proposed based on ensemble learning theory. Firstly, the original historical load power is decomposed into a set of sub-series with diverse characteristics via using ensemble empirical mode decomposition. Then, BP neural network is performed as a weak learner to predict the load power of test samples. At the same time, the prediction results are used to update the weight of the weak learner and test sample and then construct a strong learner to obtain the final prediction results. According to the analysis results of the characteristics of each sub-series, the load forecasting model is established. The result of analysing the calculation example shows that the proposed prediction model outperforms all other algorithms in accuracy, which has high engineering application value.
{"title":"Short-term load forecasting based on EEMD-Adaboost-BP","authors":"Wenshuai Lin, Bin Zhang, Hongyi Li, Renquan Lu","doi":"10.1080/21642583.2022.2110539","DOIUrl":"https://doi.org/10.1080/21642583.2022.2110539","url":null,"abstract":"ABSTRACT In order to realize short-time load forecasting, an Adaboost-BP method with a weight update mechanism is proposed based on ensemble learning theory. Firstly, the original historical load power is decomposed into a set of sub-series with diverse characteristics via using ensemble empirical mode decomposition. Then, BP neural network is performed as a weak learner to predict the load power of test samples. At the same time, the prediction results are used to update the weight of the weak learner and test sample and then construct a strong learner to obtain the final prediction results. According to the analysis results of the characteristics of each sub-series, the load forecasting model is established. The result of analysing the calculation example shows that the proposed prediction model outperforms all other algorithms in accuracy, which has high engineering application value.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41620733","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 : 2022-10-12DOI: 10.1080/21642583.2022.2129507
Cheng Wang, Y. Liu, Fei-xiang Chang, Ming Lu
Multi-sensor fusion has essential applications in the field of target detection. Considering the current actual demand for miniaturization of on-board computers for driverless vehicles, this paper uses the multimodal data YOLOv3 (MDY) algorithm for pedestrian detection on embedded devices. The MDY algorithm uses YOLOv3 as the basic framework to improve pedestrian detection accuracy by optimizing anchor frames and adding small target detection branches. Then the algorithm is accelerated by using TensorRT technology to improve the real-time performance in embedded devices. Finally, a hybrid fusion framework is used to fuse the LIDAR point cloud data with the improved YOLOv3 algorithm to compensate for the shortcomings of a single sensor and improve the detection accuracy while ensuring speed. The improved YOLOv3 improves AP by 6.4% and speed by 11.3 FPS over the original algorithm. The MDY algorithm achieves better performance on the KITTI dataset. To further verify the feasibility of the MDY algorithm, an actual test was conducted on an unmanned vehicle with Jetson TX2 embedded device as the on-board computer within the campus scenario, and the results showed that the MDY algorithm achieves 90.8% accuracy under real-time operation and can achieve adequate detection accuracy and real-time performance on the embedded device.
{"title":"Pedestrian detection based on YOLOv3 multimodal data fusion","authors":"Cheng Wang, Y. Liu, Fei-xiang Chang, Ming Lu","doi":"10.1080/21642583.2022.2129507","DOIUrl":"https://doi.org/10.1080/21642583.2022.2129507","url":null,"abstract":"Multi-sensor fusion has essential applications in the field of target detection. Considering the current actual demand for miniaturization of on-board computers for driverless vehicles, this paper uses the multimodal data YOLOv3 (MDY) algorithm for pedestrian detection on embedded devices. The MDY algorithm uses YOLOv3 as the basic framework to improve pedestrian detection accuracy by optimizing anchor frames and adding small target detection branches. Then the algorithm is accelerated by using TensorRT technology to improve the real-time performance in embedded devices. Finally, a hybrid fusion framework is used to fuse the LIDAR point cloud data with the improved YOLOv3 algorithm to compensate for the shortcomings of a single sensor and improve the detection accuracy while ensuring speed. The improved YOLOv3 improves AP by 6.4% and speed by 11.3 FPS over the original algorithm. The MDY algorithm achieves better performance on the KITTI dataset. To further verify the feasibility of the MDY algorithm, an actual test was conducted on an unmanned vehicle with Jetson TX2 embedded device as the on-board computer within the campus scenario, and the results showed that the MDY algorithm achieves 90.8% accuracy under real-time operation and can achieve adequate detection accuracy and real-time performance on the embedded device.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48016056","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 : 2022-10-03DOI: 10.1080/21642583.2022.2110540
Chao Wang, Bingyou Liu, Xuan Fan, Pan Yang
ABSTRACT To achieve fast, accurate control of the position angle of the rotor of permanent magnet synchronous motor (PMSM), traditional auto disturbance rejection control often has many adjustable parameters and complex tuning problems. Sliding mode control technology is introduced into the extended state observer (ESO) part of the auto disturbance rejection controller, and a new sliding mode approach law is designed based on several typical sliding mode approaches, which simplifies parameter tuning while retaining the original anti-interference performance of auto disturbance. In addition, the nonlinear state error feedback control law in active disturbance rejection control is enhanced to improve the component order PID control law, which can improve the response speed and robustness of the system, and prove the stability of the controller. Finally, the simulation of the PMSM rotor position control system based on the sliding mode ESO is carried out, and the results verify the validity of the method.
{"title":"Rotor position angle control of permanent magnet synchronous motor based on sliding mode extended state observer","authors":"Chao Wang, Bingyou Liu, Xuan Fan, Pan Yang","doi":"10.1080/21642583.2022.2110540","DOIUrl":"https://doi.org/10.1080/21642583.2022.2110540","url":null,"abstract":"ABSTRACT To achieve fast, accurate control of the position angle of the rotor of permanent magnet synchronous motor (PMSM), traditional auto disturbance rejection control often has many adjustable parameters and complex tuning problems. Sliding mode control technology is introduced into the extended state observer (ESO) part of the auto disturbance rejection controller, and a new sliding mode approach law is designed based on several typical sliding mode approaches, which simplifies parameter tuning while retaining the original anti-interference performance of auto disturbance. In addition, the nonlinear state error feedback control law in active disturbance rejection control is enhanced to improve the component order PID control law, which can improve the response speed and robustness of the system, and prove the stability of the controller. Finally, the simulation of the PMSM rotor position control system based on the sliding mode ESO is carried out, and the results verify the validity of the method.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44327852","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 : 2022-09-26DOI: 10.1080/21642583.2022.2123059
Zhenyong Li, Ting Li, Wei-jun Xu, Yan Shao
ABSTRACT A dynamic model of herd behaviour with delay time and media is established and analysed to discover the latent mechanism that represents how capital flows in the stock market. We prove that solutions of the model are uniformly bounded, and the contagion threshold is obtained. The stability of positive equilibrium points of the model with zero and nonzero delay is discussed. An optimal control problem with media is formulated, and Pontryagin's maximum principle is applied to find an optimal strategy to control herding. Several numerical simulations show the effect of media and delay on herd behaviour. Finally, the practical meaning of the presented model is briefly discussed.
{"title":"Dynamic modelling and optimal control of herd behaviour with time delay and media","authors":"Zhenyong Li, Ting Li, Wei-jun Xu, Yan Shao","doi":"10.1080/21642583.2022.2123059","DOIUrl":"https://doi.org/10.1080/21642583.2022.2123059","url":null,"abstract":"ABSTRACT A dynamic model of herd behaviour with delay time and media is established and analysed to discover the latent mechanism that represents how capital flows in the stock market. We prove that solutions of the model are uniformly bounded, and the contagion threshold is obtained. The stability of positive equilibrium points of the model with zero and nonzero delay is discussed. An optimal control problem with media is formulated, and Pontryagin's maximum principle is applied to find an optimal strategy to control herding. Several numerical simulations show the effect of media and delay on herd behaviour. Finally, the practical meaning of the presented model is briefly discussed.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47069925","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 : 2022-09-26DOI: 10.1080/21642583.2022.2123058
Qiuni Li, Fawei Wang, Zongcheng Liu, Yuqin Li
ABSTRACT In view of the huge strategy space and high real-time requirement for multi-fighter air combat maneouvre decisions, the target allocation and the manoeuvre decision model are established, respectively and the air combat strategy solving algorithm is proposed based on two-layer game decision-making and the distributed Monte Carlo strategy search method with double game trees. Moreover, the two-layer game decision-making method can precut the huge game tree strategy space, which improves the efficiency of strategy search. The distributed Monte Carlo strategy search method with double game trees can quickly search out the optimal decision scheme of an air combat game based on the opponent’s strategy. The experiment results show that the designed algorithm is effective and improves the efficiency of the decision compared with the Monte Carlo search algorithm of single-layer decision-making.
{"title":"Air combat manoeuvre strategy algorithm based on two-layer game decision-making and the distributed MCTS method with double game trees","authors":"Qiuni Li, Fawei Wang, Zongcheng Liu, Yuqin Li","doi":"10.1080/21642583.2022.2123058","DOIUrl":"https://doi.org/10.1080/21642583.2022.2123058","url":null,"abstract":"ABSTRACT In view of the huge strategy space and high real-time requirement for multi-fighter air combat maneouvre decisions, the target allocation and the manoeuvre decision model are established, respectively and the air combat strategy solving algorithm is proposed based on two-layer game decision-making and the distributed Monte Carlo strategy search method with double game trees. Moreover, the two-layer game decision-making method can precut the huge game tree strategy space, which improves the efficiency of strategy search. The distributed Monte Carlo strategy search method with double game trees can quickly search out the optimal decision scheme of an air combat game based on the opponent’s strategy. The experiment results show that the designed algorithm is effective and improves the efficiency of the decision compared with the Monte Carlo search algorithm of single-layer decision-making.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41305700","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 : 2022-09-26DOI: 10.1080/21642583.2022.2123063
Lixiong Lin
This article focuses on the design of a proportional integral observer (PIO) for fault detection in uncertain systems. For multi-output linear systems with actuator fault and disturbances, an approach using two PIOs is designed to estimate both the system states and disturbances simultaneously when the actuator fault is free. Then a residual generator based on the output function is used to identify whether the fault is occurring. For a class of nonlinear systems with constant disturbances, a full-order PIO is designed to estimate the disturbances. Similarly, the residual generator is used to identify whether the fault is occurring. Numerical examples are given to show the efficiency of the proposed approach.
{"title":"Fault detection in uncertain systems via proportional integral observer","authors":"Lixiong Lin","doi":"10.1080/21642583.2022.2123063","DOIUrl":"https://doi.org/10.1080/21642583.2022.2123063","url":null,"abstract":"This article focuses on the design of a proportional integral observer (PIO) for fault detection in uncertain systems. For multi-output linear systems with actuator fault and disturbances, an approach using two PIOs is designed to estimate both the system states and disturbances simultaneously when the actuator fault is free. Then a residual generator based on the output function is used to identify whether the fault is occurring. For a class of nonlinear systems with constant disturbances, a full-order PIO is designed to estimate the disturbances. Similarly, the residual generator is used to identify whether the fault is occurring. Numerical examples are given to show the efficiency of the proposed approach.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44650922","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 : 2022-09-26DOI: 10.1080/21642583.2022.2123060
Hong Fang, Guangjie Jiang, Desheng Li
Driven by the rapid development of Internet, more e-commerce product reviews are available on e-commerce platforms, which can help enterprises make business decisions. Currently, bidirectional encoder representations from transformers (BERT) applied in the embedding layer contributes to achieve promising results in English text sentiment analysis (SA). This paper proposes a novel model Chinese BERT with fused deep neural networks (CBERT-FDNN), extracting richer and more accurate semantic and grammatical information in Chinese text. First, Chinese BERT with whole word masking (Chinese-BERT-wwm) is used in the embedding layer to generate dynamic sentence representation vectors. It is a Chinese pre-training model based on the whole word masking (WWM) technology, which is more effective for Chinese text contextual embedding. Second, multi-channel and multi-scale convolutional neural networks (CNN) and bidirectional long short-term memory (BiLSTM) are designed to capture further crucial features in the feature extraction layer. To obtain more comprehensive sentence attributes, these features are concatenated together. Last, the model is evaluated on 100,000 sentence-level Chinese e-commerce product reviews for sentiment binary classification. The accuracy and F1 score can achieve 94.37% and 94.34%, respectively. Compared with the baseline models, the experiments show that our proposed model has higher accuracy and better prediction performance.
{"title":"Sentiment analysis based on Chinese BERT and fused deep neural networks for sentence-level Chinese e-commerce product reviews","authors":"Hong Fang, Guangjie Jiang, Desheng Li","doi":"10.1080/21642583.2022.2123060","DOIUrl":"https://doi.org/10.1080/21642583.2022.2123060","url":null,"abstract":"Driven by the rapid development of Internet, more e-commerce product reviews are available on e-commerce platforms, which can help enterprises make business decisions. Currently, bidirectional encoder representations from transformers (BERT) applied in the embedding layer contributes to achieve promising results in English text sentiment analysis (SA). This paper proposes a novel model Chinese BERT with fused deep neural networks (CBERT-FDNN), extracting richer and more accurate semantic and grammatical information in Chinese text. First, Chinese BERT with whole word masking (Chinese-BERT-wwm) is used in the embedding layer to generate dynamic sentence representation vectors. It is a Chinese pre-training model based on the whole word masking (WWM) technology, which is more effective for Chinese text contextual embedding. Second, multi-channel and multi-scale convolutional neural networks (CNN) and bidirectional long short-term memory (BiLSTM) are designed to capture further crucial features in the feature extraction layer. To obtain more comprehensive sentence attributes, these features are concatenated together. Last, the model is evaluated on 100,000 sentence-level Chinese e-commerce product reviews for sentiment binary classification. The accuracy and F1 score can achieve 94.37% and 94.34%, respectively. Compared with the baseline models, the experiments show that our proposed model has higher accuracy and better prediction performance.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41423007","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 : 2022-09-20DOI: 10.1080/21642583.2022.2123061
Weiqiang Tang, Haiyan Gao, Tianpeng Xu
ABSTRACT Reducing the fluctuation of slurry concentration is the key to improve the quality of mine filling. This study aims to develop a novel sliding mode control strategy to improve the accuracy of slurry concentration. A mathematical model of a slurry preparation process is firstly established by using the system response method. Secondly, the preview information is integrated into the model by constructing an augmented system. Then, a sliding mode controller is designed by using an improved exponential reaching law. Besides, the uncertainty of the system is estimated and compensated. The results show that the designed control system has excellent dynamic performance, high accuracy and strong robustness. The problem of the large fluctuation range of the slurry con-centration has been preliminarily solved. Finally, the effectiveness of the developed control strategy is verified by the numerical and experimental results.
{"title":"Improved sliding mode control of mine filling slurry concentration based on preview information","authors":"Weiqiang Tang, Haiyan Gao, Tianpeng Xu","doi":"10.1080/21642583.2022.2123061","DOIUrl":"https://doi.org/10.1080/21642583.2022.2123061","url":null,"abstract":"ABSTRACT Reducing the fluctuation of slurry concentration is the key to improve the quality of mine filling. This study aims to develop a novel sliding mode control strategy to improve the accuracy of slurry concentration. A mathematical model of a slurry preparation process is firstly established by using the system response method. Secondly, the preview information is integrated into the model by constructing an augmented system. Then, a sliding mode controller is designed by using an improved exponential reaching law. Besides, the uncertainty of the system is estimated and compensated. The results show that the designed control system has excellent dynamic performance, high accuracy and strong robustness. The problem of the large fluctuation range of the slurry con-centration has been preliminarily solved. Finally, the effectiveness of the developed control strategy is verified by the numerical and experimental results.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48473769","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 : 2022-09-17DOI: 10.1080/21642583.2022.2123062
Brayan Andru Montenegro, J. F. Flórez, Elena Muñoz
Dynamic scene reconstruction in real environments is still an ongoing research challenge; moving objects affect the performance of static environment-based simultaneous localization and mapping and impede a correct scene reconstruction. This paper proposes a method for dynamic scene reconstruction using sensor fusion for dynamic simultaneous localization and mapping. It employs two-dimensional LIDAR statistical behaviour to detect and segment high variability point cloud areas containing a dynamic object. The method is computationally low cost, allowing a 6.6 Hz execution rate. It obtains point cloud reconstruction of a static scene by reducing, segmenting, and concatenating successive point clouds of a dynamic environment. The tests were in real indoor environments with a robotic vehicle and a person traversing a scene. The correlation between the static environment point cloud and successive reconstructed point clouds demonstrates that the proposed method reconstructs different environments in the presence of dynamic objects. GRAPHICAL ABSTRACT
{"title":"Dynamic reconstruction in simultaneous localization and mapping based on the segmentation of high variability point zones","authors":"Brayan Andru Montenegro, J. F. Flórez, Elena Muñoz","doi":"10.1080/21642583.2022.2123062","DOIUrl":"https://doi.org/10.1080/21642583.2022.2123062","url":null,"abstract":"Dynamic scene reconstruction in real environments is still an ongoing research challenge; moving objects affect the performance of static environment-based simultaneous localization and mapping and impede a correct scene reconstruction. This paper proposes a method for dynamic scene reconstruction using sensor fusion for dynamic simultaneous localization and mapping. It employs two-dimensional LIDAR statistical behaviour to detect and segment high variability point cloud areas containing a dynamic object. The method is computationally low cost, allowing a 6.6 Hz execution rate. It obtains point cloud reconstruction of a static scene by reducing, segmenting, and concatenating successive point clouds of a dynamic environment. The tests were in real indoor environments with a robotic vehicle and a person traversing a scene. The correlation between the static environment point cloud and successive reconstructed point clouds demonstrates that the proposed method reconstructs different environments in the presence of dynamic objects. GRAPHICAL ABSTRACT","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48850513","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 : 2022-09-12DOI: 10.1080/21642583.2022.2119440
Ning Wang, Jiafa Mao, Lixin Wang, Yahong Hu
Identity recognition technology is a type of technology that realizes identity verification based on certain biological characteristics. After entering the Internet era, this technology has become a popular research direction in the computer field. In this paper, the image of the tooth print is used as the biological feature to carry out the research on the identification algorithm. This paper adopts the target detection algorithm based on neural network to detect a single tooth imprint area of the target, build a target detection network. The experimental results show that the method has a good segmentation effect on the target area, and the accuracy rate is 91.66%. According to the contour features of the collected tooth print images, a set of tooth pore area ratio feature extraction methods are designed. To objectively evaluate the recognition and classification method, the support vector machine is used as the final classifier. The recognition accuracy rate is 94.09%, and the verification accuracy rate is 94.09%. The test accuracy rate is 91.46%, and the classification effect is excellent. This paper has made a lot of breakthroughs and obvious progress based on the previous research on the tooth impression model.
{"title":"Identification technology based on geometric features of tooth print images","authors":"Ning Wang, Jiafa Mao, Lixin Wang, Yahong Hu","doi":"10.1080/21642583.2022.2119440","DOIUrl":"https://doi.org/10.1080/21642583.2022.2119440","url":null,"abstract":"Identity recognition technology is a type of technology that realizes identity verification based on certain biological characteristics. After entering the Internet era, this technology has become a popular research direction in the computer field. In this paper, the image of the tooth print is used as the biological feature to carry out the research on the identification algorithm. This paper adopts the target detection algorithm based on neural network to detect a single tooth imprint area of the target, build a target detection network. The experimental results show that the method has a good segmentation effect on the target area, and the accuracy rate is 91.66%. According to the contour features of the collected tooth print images, a set of tooth pore area ratio feature extraction methods are designed. To objectively evaluate the recognition and classification method, the support vector machine is used as the final classifier. The recognition accuracy rate is 94.09%, and the verification accuracy rate is 94.09%. The test accuracy rate is 91.46%, and the classification effect is excellent. This paper has made a lot of breakthroughs and obvious progress based on the previous research on the tooth impression model.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47423962","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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