Pub Date : 2023-11-29DOI: 10.1080/21642583.2023.2285292
Fengqian Pang, Xi Chen
The existing ripeness detection algorithm for strawberries suffers from low detection accuracy and high detection error rate. Considering these problems, we propose an improvement method based on YOLOv5, named MS-YOLOv5. The first step is to reconfigure the feature extraction network of MS-YOLOv5 by replacing the standard convolution with the depth hybrid deformable convolution (Ms-MDconv). In the second step, a double cooperative attention mechanism (Bc-attention) is constructed and implemented in the CSP2 module to improve the feature representation in complex environments. Finally, the Neck section of MS-YOLOv5 has been enhanced to use the fast-weighted fusion of cross-scale feature pyramid networks (FW-FPN) to replace the CSP2 module. It not only integrates multi-scale target features but also significantly reduces the number of parameters. The method was tested on the strawberry ripeness dataset, the mAP reached 0.956, the FPS reached 76, and the model size was 7.44M. The mAP and FPS are 8.4 and 1.3 percentage higher than the baseline network, respectively. The model size is reduced by 6.28M. This method is superior to mainstream algorithms in detection speed and accuracy. The system can accurately identify the ripeness of strawberries in complex environments, which could provide technical support for automated picking robots.
{"title":"MS-YOLOv5: a lightweight algorithm for strawberry ripeness detection based on deep learning","authors":"Fengqian Pang, Xi Chen","doi":"10.1080/21642583.2023.2285292","DOIUrl":"https://doi.org/10.1080/21642583.2023.2285292","url":null,"abstract":"The existing ripeness detection algorithm for strawberries suffers from low detection accuracy and high detection error rate. Considering these problems, we propose an improvement method based on YOLOv5, named MS-YOLOv5. The first step is to reconfigure the feature extraction network of MS-YOLOv5 by replacing the standard convolution with the depth hybrid deformable convolution (Ms-MDconv). In the second step, a double cooperative attention mechanism (Bc-attention) is constructed and implemented in the CSP2 module to improve the feature representation in complex environments. Finally, the Neck section of MS-YOLOv5 has been enhanced to use the fast-weighted fusion of cross-scale feature pyramid networks (FW-FPN) to replace the CSP2 module. It not only integrates multi-scale target features but also significantly reduces the number of parameters. The method was tested on the strawberry ripeness dataset, the mAP reached 0.956, the FPS reached 76, and the model size was 7.44M. The mAP and FPS are 8.4 and 1.3 percentage higher than the baseline network, respectively. The model size is reduced by 6.28M. This method is superior to mainstream algorithms in detection speed and accuracy. The system can accurately identify the ripeness of strawberries in complex environments, which could provide technical support for automated picking robots.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139214255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-27DOI: 10.1080/21642583.2023.2286302
Weiman Yang, Bo Yang, Xin Liu, Xinggui Wang, Qun Guo
The application of modular multilevel converters (MMCs) to large drive systems is subject to severe low-frequency operation restrictions. The fluctuation of capacitor voltage and the high amplitude of common mode voltage in sub-modules is a thorny problem. In this paper, a novel fly-across capacitor modular multilevel converter topology is adopted to eliminate low-frequency voltage ripples by using the fly-across capacitor as a power transfer channel between the upper and lower bridge arms of the MMC. A novel finite compensation method is proposed—instead of the traditional full compensation method—that introduces a real-time variable limiting factor to change the amplitude of the mixed injected high-frequency differential-mode voltage and high-frequency differential-mode current and reduce the amplitude of the common-mode voltage on the AC side while lowering the current stress of the power devices. Finally, a complete system simulation model is constructed, and the topology with the proposed control strategy are verified to have good output characteristics under different operating conditions; good results are achieved in suppressing the sub-module fluctuation and common-mode voltage.
{"title":"Low-frequency operation control method for medium-voltage high-capacity FC-MMC type frequency converter","authors":"Weiman Yang, Bo Yang, Xin Liu, Xinggui Wang, Qun Guo","doi":"10.1080/21642583.2023.2286302","DOIUrl":"https://doi.org/10.1080/21642583.2023.2286302","url":null,"abstract":"The application of modular multilevel converters (MMCs) to large drive systems is subject to severe low-frequency operation restrictions. The fluctuation of capacitor voltage and the high amplitude of common mode voltage in sub-modules is a thorny problem. In this paper, a novel fly-across capacitor modular multilevel converter topology is adopted to eliminate low-frequency voltage ripples by using the fly-across capacitor as a power transfer channel between the upper and lower bridge arms of the MMC. A novel finite compensation method is proposed—instead of the traditional full compensation method—that introduces a real-time variable limiting factor to change the amplitude of the mixed injected high-frequency differential-mode voltage and high-frequency differential-mode current and reduce the amplitude of the common-mode voltage on the AC side while lowering the current stress of the power devices. Finally, a complete system simulation model is constructed, and the topology with the proposed control strategy are verified to have good output characteristics under different operating conditions; good results are achieved in suppressing the sub-module fluctuation and common-mode voltage.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139233972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-27DOI: 10.1080/21642583.2023.2233535
Xiaowei Fan, Jianfeng Xiao, Haifeng Yang, Long Yao, Jiaxin Luo, Wen Jiang, Piao Du, Decheng Cao
This paper proposes a Nash bargaining cooperative game model for a microgrid cluster system with double re-energy-load delay considering electricity, heat and gas multi-energy synergies. With the minimization of the operating cost of each microgrid as the objective function, a low-carbon operation model of a multi-energy complementary integrated energy microgrid considering fuzzy opportunity constraints is developed, an optimal operation mechanism including carbon quota and carbon trading is assessed, and a carbon capture system and an electricity-gas conversion device are added to the improved cogeneration unit model. Source-load uncertainty in microgrids is described in terms of new fuzzy parameters of new energy and undefined parameters of load demand. Each microgrid plays a second game with the marginal contribution rate and carbon trading cost rate as the bargaining power. The model is solved in a distributed manner using the ADMM-RGE algorithm. Finally, the simulation results show that the proposed multi-microgrid power-sharing way maximizes the benefits of microgrid alliances; the cooperative help of microgrid alliances is pretty distributed according to the size of each microgrid's energy contribution; carbon capture joint power-gas systems and energy sharing methods between microgrids can effectively reduce carbon emissions during microgrid operation.
{"title":"Research on the operation of integrated energy microgrid based on cluster power sharing mechanism","authors":"Xiaowei Fan, Jianfeng Xiao, Haifeng Yang, Long Yao, Jiaxin Luo, Wen Jiang, Piao Du, Decheng Cao","doi":"10.1080/21642583.2023.2233535","DOIUrl":"https://doi.org/10.1080/21642583.2023.2233535","url":null,"abstract":"This paper proposes a Nash bargaining cooperative game model for a microgrid cluster system with double re-energy-load delay considering electricity, heat and gas multi-energy synergies. With the minimization of the operating cost of each microgrid as the objective function, a low-carbon operation model of a multi-energy complementary integrated energy microgrid considering fuzzy opportunity constraints is developed, an optimal operation mechanism including carbon quota and carbon trading is assessed, and a carbon capture system and an electricity-gas conversion device are added to the improved cogeneration unit model. Source-load uncertainty in microgrids is described in terms of new fuzzy parameters of new energy and undefined parameters of load demand. Each microgrid plays a second game with the marginal contribution rate and carbon trading cost rate as the bargaining power. The model is solved in a distributed manner using the ADMM-RGE algorithm. Finally, the simulation results show that the proposed multi-microgrid power-sharing way maximizes the benefits of microgrid alliances; the cooperative help of microgrid alliances is pretty distributed according to the size of each microgrid's energy contribution; carbon capture joint power-gas systems and energy sharing methods between microgrids can effectively reduce carbon emissions during microgrid operation.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139233229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.1080/21642583.2023.2276416
Song Liu, Shiyuan Feng, Yan Wang, Dennis Z. Yu, Shan Jiang, Xianting Ma, Yong Peng
In response to the challenge of optimizing customized passenger transport paths for airport connections while taking carbon emissions constraints into account, this paper proposes an optimization model that minimizes the total cost by addressing passenger time window constraints, determining optimal passenger transport paths, and optimizing factors like the number of drop-off stations and vehicle occupancy rates. The total cost comprises the operational expenses of customized passenger transport businesses and travel time costs per passenger. We develop an annealing genetic algorithm to solve the model and provide a case analysis. Our findings indicate that the algorithm and the model empower decision-makers to swiftly select passenger transport path schemes that minimize the total cost with their specific requirements.
{"title":"Customized passenger path optimization for airport connections under carbon emissions restrictions","authors":"Song Liu, Shiyuan Feng, Yan Wang, Dennis Z. Yu, Shan Jiang, Xianting Ma, Yong Peng","doi":"10.1080/21642583.2023.2276416","DOIUrl":"https://doi.org/10.1080/21642583.2023.2276416","url":null,"abstract":"In response to the challenge of optimizing customized passenger transport paths for airport connections while taking carbon emissions constraints into account, this paper proposes an optimization model that minimizes the total cost by addressing passenger time window constraints, determining optimal passenger transport paths, and optimizing factors like the number of drop-off stations and vehicle occupancy rates. The total cost comprises the operational expenses of customized passenger transport businesses and travel time costs per passenger. We develop an annealing genetic algorithm to solve the model and provide a case analysis. Our findings indicate that the algorithm and the model empower decision-makers to swiftly select passenger transport path schemes that minimize the total cost with their specific requirements.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135432584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.1080/21642583.2023.2268121
Zhang Yaofang, Chen Jian, Qiu Zhixuan
With the rapid development of economy, the increasing number of motor vehicles and the total road mileage, which leads to the increasingly prominent traffic safety problems. In order to explore the quantitative relationship between the built environment and the risk of urban road traffic safety, this paper reconstructs the built environment system based on the ‘5D' element model of the built environment combined with the factors influencing traffic safety risks, and describes the built environment from multiple aspects such as density, diversity &traffic design etc, and then build the gradient lift decision tree model to explore the importance and dependency of variables. The empirical analysis selects a district in Chongqing as the research unit, and the results show that: the RMSE the model was 0.0036, the MAPE was 1.9%, and the determination coefficient R2 was 0.84. GBDT algorithm results shows: the cumulative importance of population density, road facilities, intersection density, secondary road and branch road density, average intersection distance, land use mix, and economic density reaches 77.87%. Some variables show obvious nonlinearity and threshold effect.
{"title":"Nonlinear impact analysis of built environment on urban road traffic safety risk","authors":"Zhang Yaofang, Chen Jian, Qiu Zhixuan","doi":"10.1080/21642583.2023.2268121","DOIUrl":"https://doi.org/10.1080/21642583.2023.2268121","url":null,"abstract":"With the rapid development of economy, the increasing number of motor vehicles and the total road mileage, which leads to the increasingly prominent traffic safety problems. In order to explore the quantitative relationship between the built environment and the risk of urban road traffic safety, this paper reconstructs the built environment system based on the ‘5D' element model of the built environment combined with the factors influencing traffic safety risks, and describes the built environment from multiple aspects such as density, diversity &traffic design etc, and then build the gradient lift decision tree model to explore the importance and dependency of variables. The empirical analysis selects a district in Chongqing as the research unit, and the results show that: the RMSE the model was 0.0036, the MAPE was 1.9%, and the determination coefficient R2 was 0.84. GBDT algorithm results shows: the cumulative importance of population density, road facilities, intersection density, secondary road and branch road density, average intersection distance, land use mix, and economic density reaches 77.87%. Some variables show obvious nonlinearity and threshold effect.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136262307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-11DOI: 10.1080/21642583.2023.2268153
Yafei Chen, Tao Deng
To solve the problems of backstepping error and poor dynamic tracking approach rate in traditional PID neural network control in UAV formation flight control, a Leader-Follower UAV formation flight control method based on feature modelling is proposed,and the pose relationship model between virtual follower and pilot is established by trajectory tracking and pose dynamic fitting. The pose distribution of thefollower is analyzed in the ground coordinate system, and the parameter information of linear velocity and angular velocity control of UAV is obtained, and the backstepping sliding mode formation controller is formed. The variable structure PID neural network controller is used to design the flight control law of UAV formation, and the fast piecewise power approaching factor is introduced into the PID controller to eliminate the chattering of sliding mode control. The simulation results show that this method can ensure the rapidity of UAV formation flight control also show strong anti-jamming ability. Due to the fast piecewise power approach rate, the UAVs can complete the UAV formation reorganization under disturbance and buffeting in a short time, and the trajectory tracking error approaches zero, and it has good anti-buffeting ability.
{"title":"Leader-Follower UAV formation flight control based on feature modelling","authors":"Yafei Chen, Tao Deng","doi":"10.1080/21642583.2023.2268153","DOIUrl":"https://doi.org/10.1080/21642583.2023.2268153","url":null,"abstract":"To solve the problems of backstepping error and poor dynamic tracking approach rate in traditional PID neural network control in UAV formation flight control, a Leader-Follower UAV formation flight control method based on feature modelling is proposed,and the pose relationship model between virtual follower and pilot is established by trajectory tracking and pose dynamic fitting. The pose distribution of thefollower is analyzed in the ground coordinate system, and the parameter information of linear velocity and angular velocity control of UAV is obtained, and the backstepping sliding mode formation controller is formed. The variable structure PID neural network controller is used to design the flight control law of UAV formation, and the fast piecewise power approaching factor is introduced into the PID controller to eliminate the chattering of sliding mode control. The simulation results show that this method can ensure the rapidity of UAV formation flight control also show strong anti-jamming ability. Due to the fast piecewise power approach rate, the UAVs can complete the UAV formation reorganization under disturbance and buffeting in a short time, and the trajectory tracking error approaches zero, and it has good anti-buffeting ability.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136210839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.1080/21642583.2023.2249934
Yanwen Li, Juxia Li, Tengxiao Na, Hua Yang
Attack behaviour detection of the pig is a valid method to protect the health of pig. Due to the farm conditions and the illumination changes of the piggery, the images of the pig in the videos are often being overlapped, which lead to difficulties in recognizing pig attack behaviour. We propose an improved YOLOX target detection model to overcome these difficulties. The improvements of the proposed model are: (1) the normalization attention mechanism is adopted to gain global information in the last block of the neck network and (2) the loss function IoU in YOLOX is replaced by DIoU to improve the detection accuracy. The pig attack behaviour considered in this paper includes the ear biting, the tail biting, the head to head collision and the head to body collision. The dataset is builded from the artificially observed attack video segments by using the inter-frame difference method. In the pig attack behaviour detection experiments, the improved YOLOX model achieves 93.21% precision which is 5.30% higher than the YOLOX model. The experiment results show that the improved YOLOX can realize pig attack behaviour detection with high precision.
{"title":"Detection of attack behaviour of pig based on deep learning","authors":"Yanwen Li, Juxia Li, Tengxiao Na, Hua Yang","doi":"10.1080/21642583.2023.2249934","DOIUrl":"https://doi.org/10.1080/21642583.2023.2249934","url":null,"abstract":"Attack behaviour detection of the pig is a valid method to protect the health of pig. Due to the farm conditions and the illumination changes of the piggery, the images of the pig in the videos are often being overlapped, which lead to difficulties in recognizing pig attack behaviour. We propose an improved YOLOX target detection model to overcome these difficulties. The improvements of the proposed model are: (1) the normalization attention mechanism is adopted to gain global information in the last block of the neck network and (2) the loss function IoU in YOLOX is replaced by DIoU to improve the detection accuracy. The pig attack behaviour considered in this paper includes the ear biting, the tail biting, the head to head collision and the head to body collision. The dataset is builded from the artificially observed attack video segments by using the inter-frame difference method. In the pig attack behaviour detection experiments, the improved YOLOX model achieves 93.21% precision which is 5.30% higher than the YOLOX model. The experiment results show that the improved YOLOX can realize pig attack behaviour detection with high precision.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136235222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-20DOI: 10.1080/21642583.2023.2223227
Fei Song, Yong Li, Wei Cheng, Limeng Dong
The detection and tracking of small and weak maneuvering radar targets in complex electromagnetic environments is still a difficult problem to effectively solve. To address this problem, this paper proposes a dynamic programming tracking-before-detection method based on long short-term memory (LSTM) network value function(VL-DP-TBD). With the help of the estimated posterior probability provided by the designed LSTM network, the calculation of the posterior value function of the traditional DP-TBD algorithm can be more accurate, and the detection and tracking effect achieved for maneuvering small and weak targets is improved. Utilizing the LSTM network to model the posterior probability estimation of the target motion state, the posterior probability moving features of the maneuvering target can be learned from the noisy input data. By incorporating these posterior probability estimation values into the traditional DP-TBD algorithm, the accuracy and robustness of the calculation of the posterior value function can be enhanced, so that the improved architecture is capable of effectively recursively accumulating the movement trend of the target. Simulation results show that the improved architecture is able to effectively reduce the aggregation effect of a posterior value function and improve the detection and tracking ability for non-cooperative nonlinear maneuvering dim small target.AbbreviationsLSTM: Long short-term memory; DP-TBD: Dynamic programming-based tracking before detection; DBT: Detection before tracking; TBD: Tracking before detection; HT-TBD: Tracking-before-detection algorithm based on the Hough transform; PF-TBD: Tracking-before-detection algorithm based on particle filtering; RFS-TBD: Tracking-before-detection algorithm based on random finite sets; SNR: Signal-to-noise ratio; DP: Dynamic programming; EVT: Extreme value theory; EVT: Generalized extreme value theory; GLRT: Generalized likelihood ratio detection; KT: Keystone transformation; PGA: Phase gradient autofocusing; CFAR: Constant false-alarm rate; J-CA-CFAR: Joint intensity-spatial CFAR; MF: Merit function; CP-DP-TBD: Candidate plot-based DP-TBD; CIT: Coherent integration time; RNN: Recurrent neural network; CS: Current statistical; Pd: Detection probability; Pt: Tracking probability.
{"title":"An improved dynamic programming tracking-before-detection algorithm based on LSTM network value function","authors":"Fei Song, Yong Li, Wei Cheng, Limeng Dong","doi":"10.1080/21642583.2023.2223227","DOIUrl":"https://doi.org/10.1080/21642583.2023.2223227","url":null,"abstract":"The detection and tracking of small and weak maneuvering radar targets in complex electromagnetic environments is still a difficult problem to effectively solve. To address this problem, this paper proposes a dynamic programming tracking-before-detection method based on long short-term memory (LSTM) network value function(VL-DP-TBD). With the help of the estimated posterior probability provided by the designed LSTM network, the calculation of the posterior value function of the traditional DP-TBD algorithm can be more accurate, and the detection and tracking effect achieved for maneuvering small and weak targets is improved. Utilizing the LSTM network to model the posterior probability estimation of the target motion state, the posterior probability moving features of the maneuvering target can be learned from the noisy input data. By incorporating these posterior probability estimation values into the traditional DP-TBD algorithm, the accuracy and robustness of the calculation of the posterior value function can be enhanced, so that the improved architecture is capable of effectively recursively accumulating the movement trend of the target. Simulation results show that the improved architecture is able to effectively reduce the aggregation effect of a posterior value function and improve the detection and tracking ability for non-cooperative nonlinear maneuvering dim small target.AbbreviationsLSTM: Long short-term memory; DP-TBD: Dynamic programming-based tracking before detection; DBT: Detection before tracking; TBD: Tracking before detection; HT-TBD: Tracking-before-detection algorithm based on the Hough transform; PF-TBD: Tracking-before-detection algorithm based on particle filtering; RFS-TBD: Tracking-before-detection algorithm based on random finite sets; SNR: Signal-to-noise ratio; DP: Dynamic programming; EVT: Extreme value theory; EVT: Generalized extreme value theory; GLRT: Generalized likelihood ratio detection; KT: Keystone transformation; PGA: Phase gradient autofocusing; CFAR: Constant false-alarm rate; J-CA-CFAR: Joint intensity-spatial CFAR; MF: Merit function; CP-DP-TBD: Candidate plot-based DP-TBD; CIT: Coherent integration time; RNN: Recurrent neural network; CS: Current statistical; Pd: Detection probability; Pt: Tracking probability.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135186987","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 : 2022-12-31DOI: 10.1080/21642583.2022.2052996
Amir Karbassi Yazdi, C. Spulbar, T. Hanne, Ramona Birau
This research aims to identify performance indicators and use them to prioritize banks in Iran. Today, the banking industry is severely challenged by decreasing revenues, especially during crisis such as the COVID-19 pandemic. Hence, evaluating banks to find their weaknesses is vital and shows how banks with flaws can be benchmarked from best practice banks. For this work, data is collected from Iranian banks and then evaluated based on the Delphi method. Since the importance of the considered factors is quite diverse, they should be ranked. We use Evaluation by an Area-Based Method of Ranking (EAMR) for this research study. As this method requires factor-specific weights, the Stepwise Weight Assessment Ratio Analysis (SWARA) method is used for determining these weights. This paper looks forward to introducing new hybrid MADM methods in an uncertain environment with high reliability in the results. This new model leads to ensure managers that they can make their decisions accurately. The results reveal the performance of Iranian banks and a respective ranking of them including a model for benchmarking. This empirical research study also provides useful guidance to a better understanding of performance measurement in the banking sector in Iran.
{"title":"Ranking performance indicators related to banking by using hybrid multicriteria methods in an uncertain environment: a case study for Iran under COVID-19 conditions","authors":"Amir Karbassi Yazdi, C. Spulbar, T. Hanne, Ramona Birau","doi":"10.1080/21642583.2022.2052996","DOIUrl":"https://doi.org/10.1080/21642583.2022.2052996","url":null,"abstract":"This research aims to identify performance indicators and use them to prioritize banks in Iran. Today, the banking industry is severely challenged by decreasing revenues, especially during crisis such as the COVID-19 pandemic. Hence, evaluating banks to find their weaknesses is vital and shows how banks with flaws can be benchmarked from best practice banks. For this work, data is collected from Iranian banks and then evaluated based on the Delphi method. Since the importance of the considered factors is quite diverse, they should be ranked. We use Evaluation by an Area-Based Method of Ranking (EAMR) for this research study. As this method requires factor-specific weights, the Stepwise Weight Assessment Ratio Analysis (SWARA) method is used for determining these weights. This paper looks forward to introducing new hybrid MADM methods in an uncertain environment with high reliability in the results. This new model leads to ensure managers that they can make their decisions accurately. The results reveal the performance of Iranian banks and a respective ranking of them including a model for benchmarking. This empirical research study also provides useful guidance to a better understanding of performance measurement in the banking sector in Iran.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42795604","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 this paper, the non-fragile joint state and fault estimation problem is investigated for a class of nonlinear time-varying complex networks (NTVCNs) with uncertain inner coupling and mixed time-delays. Compared with the constant inner coupling strength in the existing literature, the inner coupling strength is permitted to vary within certain intervals. A new non-fragile model is adopted to describe the parameter perturbations of the estimator gain matrix which is described by zero-mean multiplicative noises. The attention of this paper is focussed on the design of a locally optimal estimation method, which can estimate both the state and the fault at the same time. Then, by reasonably designing the estimator gain matrix, the minimized upper bound of the state estimation error covariance matrix (SEECM) can be obtained. In addition, the boundedness analysis is taken into account, and a sufficient condition is provided to ensure the boundedness of the upper bound of the SEECM by using the mathematical induction. Lastly, a simulation example is provided to testify the feasibility of the joint state and fault estimation scheme.
{"title":"Joint state and fault estimation for nonlinear complex networks with mixed time-delays and uncertain inner coupling: non-fragile recursive method","authors":"Shuyang Feng, Huijun Yu, Chaoqing Jia, Pingping Gao","doi":"10.1080/21642583.2022.2086183","DOIUrl":"https://doi.org/10.1080/21642583.2022.2086183","url":null,"abstract":"In this paper, the non-fragile joint state and fault estimation problem is investigated for a class of nonlinear time-varying complex networks (NTVCNs) with uncertain inner coupling and mixed time-delays. Compared with the constant inner coupling strength in the existing literature, the inner coupling strength is permitted to vary within certain intervals. A new non-fragile model is adopted to describe the parameter perturbations of the estimator gain matrix which is described by zero-mean multiplicative noises. The attention of this paper is focussed on the design of a locally optimal estimation method, which can estimate both the state and the fault at the same time. Then, by reasonably designing the estimator gain matrix, the minimized upper bound of the state estimation error covariance matrix (SEECM) can be obtained. In addition, the boundedness analysis is taken into account, and a sufficient condition is provided to ensure the boundedness of the upper bound of the SEECM by using the mathematical induction. Lastly, a simulation example is provided to testify the feasibility of the joint state and fault estimation scheme.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44070975","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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