Feature selection is an essential technique which has been widely applied in data mining. Recent research has shown that a good feature subset can be obtained by using evolutionary computing (EC) approaches as a wrapper. However, most feature selection methods based on EC use a fixed-length encoding to represent feature subsets. When this fixed length representation is applied to high-dimensional data, it requires a large amount of memory space as well as a high computational cost. Moreover, this representation is inflexible and may limit the performance of EC because of a too huge search space. In this paper, we propose an Adaptive- Variable-Length Genetic Algorithm (A VLGA), which adopts a variable-length individual encoding and enables individuals with different lengths in a population to evolve in their own search space. An adaptive length changing mechanism is introduced which can extend or shorten an individual to guide it to explore in a better search space. Thus, A VLGA is able to adaptively concentrate on a smaller but more fruitful search space and yield better solutions more quickly. Experimental results on 6 high-dimensional datasets reveal that A VLGA performs significantly better than existing methods.
{"title":"High-dimensional Feature Selection in Classification: A Length-Adaptive Evolutionary Approach","authors":"Junhai Zhou, Jian-chun Lu, Quanwang Wu, Junhao Wen","doi":"10.1109/ICNSC55942.2022.10004048","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004048","url":null,"abstract":"Feature selection is an essential technique which has been widely applied in data mining. Recent research has shown that a good feature subset can be obtained by using evolutionary computing (EC) approaches as a wrapper. However, most feature selection methods based on EC use a fixed-length encoding to represent feature subsets. When this fixed length representation is applied to high-dimensional data, it requires a large amount of memory space as well as a high computational cost. Moreover, this representation is inflexible and may limit the performance of EC because of a too huge search space. In this paper, we propose an Adaptive- Variable-Length Genetic Algorithm (A VLGA), which adopts a variable-length individual encoding and enables individuals with different lengths in a population to evolve in their own search space. An adaptive length changing mechanism is introduced which can extend or shorten an individual to guide it to explore in a better search space. Thus, A VLGA is able to adaptively concentrate on a smaller but more fruitful search space and yield better solutions more quickly. Experimental results on 6 high-dimensional datasets reveal that A VLGA performs significantly better than existing methods.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114151267","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004165
Dorothy Yao, Ishani Chatterjee, Mengchu Zhou
In recent years, people use Internet as a platform to express their own ideas and opinions about various subjects or products. The data from these sites serve as sources for sentiment analysis. On e-commerce websites, the costumer product review conventionally expresses sentiment that corresponds with the given star rating; however, this is not always true; there are reviews that express sentiments opposite to the given star rating, which can be labeled as outliers. This paper builds on previous work that finds outliers in product review datasets, scraped from Amazon.com, using a statistics-based outlier detection and correction method (SODCM). This work focuses on 3-star reviews specifically and studies the correct polarity assignment of 3-star reviews. It investigates the behavior of SODCM when 3-star reviews are classified as negative and positive respectively.
{"title":"Conditioning Customers' Product Reviews for Accurate Classification Performance","authors":"Dorothy Yao, Ishani Chatterjee, Mengchu Zhou","doi":"10.1109/ICNSC55942.2022.10004165","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004165","url":null,"abstract":"In recent years, people use Internet as a platform to express their own ideas and opinions about various subjects or products. The data from these sites serve as sources for sentiment analysis. On e-commerce websites, the costumer product review conventionally expresses sentiment that corresponds with the given star rating; however, this is not always true; there are reviews that express sentiments opposite to the given star rating, which can be labeled as outliers. This paper builds on previous work that finds outliers in product review datasets, scraped from Amazon.com, using a statistics-based outlier detection and correction method (SODCM). This work focuses on 3-star reviews specifically and studies the correct polarity assignment of 3-star reviews. It investigates the behavior of SODCM when 3-star reviews are classified as negative and positive respectively.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114454127","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004134
Zhibin Li, Shuai Li, Hao Wu
Industrial robots are a critical equipment to achieve the automatic production, which have been widely employed in industrial production activities, like handling and welding. However, due to some inevitable impact factors such as machining tolerance and assembly tolerance, a robot suffers from low absolute positioning accuracy, which cannot satisfy the requirements of high-precision manufacture. To address this hot issue, a new robot calibration method incorporating an unscented Kalman filter with a variable step-size Levenberg-Marquardt algorithm is proposed. The main ideas of this paper are as follow: a) developing a novel variable step-size Levenberg-Marquardt algorithm to addresses the issue of local optimum in a Levenberg-Marquardt algorithm; b) utilizing an unscented Kalman filter to suppress the measurement noises; and c) proposing a novel calibration method based on an unscented Kalman filter with a variable step-size Levenberg-Marquardt algorithm. Moreover, the empirical studies on an ABB IRB 120 industrial robot demonstrate that the proposed method obtains much compared with state-of-the-art methods, the proposed method further outperforms each of them in terms of calibration accuracy for robot calibration. Therefore, this study is an important milestone in the field of robot calibration.
{"title":"A New Variable Step-Size Levenberg-Marquardt Algorithm for Industrial Robot Calibration","authors":"Zhibin Li, Shuai Li, Hao Wu","doi":"10.1109/ICNSC55942.2022.10004134","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004134","url":null,"abstract":"Industrial robots are a critical equipment to achieve the automatic production, which have been widely employed in industrial production activities, like handling and welding. However, due to some inevitable impact factors such as machining tolerance and assembly tolerance, a robot suffers from low absolute positioning accuracy, which cannot satisfy the requirements of high-precision manufacture. To address this hot issue, a new robot calibration method incorporating an unscented Kalman filter with a variable step-size Levenberg-Marquardt algorithm is proposed. The main ideas of this paper are as follow: a) developing a novel variable step-size Levenberg-Marquardt algorithm to addresses the issue of local optimum in a Levenberg-Marquardt algorithm; b) utilizing an unscented Kalman filter to suppress the measurement noises; and c) proposing a novel calibration method based on an unscented Kalman filter with a variable step-size Levenberg-Marquardt algorithm. Moreover, the empirical studies on an ABB IRB 120 industrial robot demonstrate that the proposed method obtains much compared with state-of-the-art methods, the proposed method further outperforms each of them in terms of calibration accuracy for robot calibration. Therefore, this study is an important milestone in the field of robot calibration.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127682521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The spherical search algorithm (SS) is a novel and competitive algorithm applied to real-world problems. However, the population of SS algorithm is divided equally, which requires a large number of computation resources for different problems. To alleviate the issues, we propose an immigration strategy-based spherical search algorithm, namely ISS. ISS adaptively selects individuals that are successfully updated in each generation and replaces the operator in the next iteration. The experiments were conducted on the 30 benchmark functions from the IEEE CEC2017. ISS is compared with SS to verify the effectiveness of the proposed adaptive immigration strategy. Additionally, the classical differential evolutionary algorithm (DE) and a state-of-the-art triple archive particle swarm optimization (TAPSO) are compared to test its performance further. The population diversity is analyzed to discuss the effect of ISS. The experimental results demonstrate that the proposed immigration strategy is quite effective, and ISS is significantly better than its peer's algorithms.
{"title":"An Immigration Strategy-based Spherical Search Algorithm","authors":"Qingya Sui, Sichen Tao, Lin Zhong, Haichuan Yang, Zhenyu Lei, Shangce Gao","doi":"10.1109/ICNSC55942.2022.10004149","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004149","url":null,"abstract":"The spherical search algorithm (SS) is a novel and competitive algorithm applied to real-world problems. However, the population of SS algorithm is divided equally, which requires a large number of computation resources for different problems. To alleviate the issues, we propose an immigration strategy-based spherical search algorithm, namely ISS. ISS adaptively selects individuals that are successfully updated in each generation and replaces the operator in the next iteration. The experiments were conducted on the 30 benchmark functions from the IEEE CEC2017. ISS is compared with SS to verify the effectiveness of the proposed adaptive immigration strategy. Additionally, the classical differential evolutionary algorithm (DE) and a state-of-the-art triple archive particle swarm optimization (TAPSO) are compared to test its performance further. The population diversity is analyzed to discuss the effect of ISS. The experimental results demonstrate that the proposed immigration strategy is quite effective, and ISS is significantly better than its peer's algorithms.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131717007","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004071
Peiyun Zhang, YanHao Tao, Junliang Shu
In a blockchain network, the instability of the block transmission process can affect the speed of block transmission. If blocks cannot be accepted by nodes and saved on a blockchain in time, which may lead to inconsistent blockchain ledgers stored by nodes, thus reducing the security of blockchain networks. However, when nodes transmit blocks, they often encounter problems of too large blocks and insufficient bandwidth, which results in slow block transmission speed and low efficiency. To solve the problems, it proposes a block transmission model, which encodes units into packets. Based on the model, the corresponding encoding and decoding processes are designed. The proposed method is compared with two state-of-the-art methods: Velocity and Kadcast. Experimental results show that the proposed method performs better than its peers in terms of block synchronization time, block transmission success ratio, and packet retransmission ratio.
{"title":"A Novel Block Transmission Model in Blockchain Networks","authors":"Peiyun Zhang, YanHao Tao, Junliang Shu","doi":"10.1109/ICNSC55942.2022.10004071","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004071","url":null,"abstract":"In a blockchain network, the instability of the block transmission process can affect the speed of block transmission. If blocks cannot be accepted by nodes and saved on a blockchain in time, which may lead to inconsistent blockchain ledgers stored by nodes, thus reducing the security of blockchain networks. However, when nodes transmit blocks, they often encounter problems of too large blocks and insufficient bandwidth, which results in slow block transmission speed and low efficiency. To solve the problems, it proposes a block transmission model, which encodes units into packets. Based on the model, the corresponding encoding and decoding processes are designed. The proposed method is compared with two state-of-the-art methods: Velocity and Kadcast. Experimental results show that the proposed method performs better than its peers in terms of block synchronization time, block transmission success ratio, and packet retransmission ratio.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129799520","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}
With the development of economy, residential power users account for a higher and higher proportion in the power system. The modern power system focusing on residential load needs to realize the stability of load demand changes by combining forecasting information with long and short term dispatching. However, residential micro grid load usually has high fluctuation, so it is a challenging problem to achieve accurate prediction. Based on the characteristics of residential power load, this paper studies the short-term forecasting task of residential power load. BILSTM-MDN hybrid prediction models were constructed by BiLSTM's ability to learn long-term dependence and underlying correlation logic. Finally, 50 apartment load data sets are used to verify the great potential of the model based on BiLSTM-MDN in residential short-term power load prediction with high fluctuation. The accuracy of prediction reached MAPE 18.25% and RMSE 30.53%.
{"title":"A Short-term Residential Load Forecast Model Based on BiLSTM-MDN","authors":"Rushan Zheng, Jian Yu, Yizhen Wang, Xiongbing Chen","doi":"10.1109/ICNSC55942.2022.10004172","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004172","url":null,"abstract":"With the development of economy, residential power users account for a higher and higher proportion in the power system. The modern power system focusing on residential load needs to realize the stability of load demand changes by combining forecasting information with long and short term dispatching. However, residential micro grid load usually has high fluctuation, so it is a challenging problem to achieve accurate prediction. Based on the characteristics of residential power load, this paper studies the short-term forecasting task of residential power load. BILSTM-MDN hybrid prediction models were constructed by BiLSTM's ability to learn long-term dependence and underlying correlation logic. Finally, 50 apartment load data sets are used to verify the great potential of the model based on BiLSTM-MDN in residential short-term power load prediction with high fluctuation. The accuracy of prediction reached MAPE 18.25% and RMSE 30.53%.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126683376","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004050
Chadi M'Sila, R. Ayad, N. A. Oufroukh
The presence of Foreign Object Debris (FOD) on airport platforms constitutes a big risk, both for aircraft and for personnel. This debris, whatever its nature or size, whether it's a private effect, a tool, a component from an aircraft, or any object, As soon because it isn't observed and removed, it's liable becoming a FOD within the moving area. FOD can even be violently projected by jet blast, which might cause damage to other aircraft and injure personnel on the bottom, This paper discuss briefly FOD detection systems and the use of unmanned aerial systems for an automated FOD detection system on runways, which involves taking images of the runway with an Unmanned Aerial Vehicle (UAV), which could be detected and identified using artificial intelligence techniques. The method for determining an exact FOD position from aerial data is described in this study using a perspective projection transformation is used to determine the object's location in the field. For accurate findings, a strong object detection is essential, which is why the cutting-edge deep neural network YOLOV5 is used with both DeepSort Object tracking method. The paper represent an Automated UAV Navigation with PID control based for path tracking. A GUI that has been developed alow the operator to select the runway's intended path to be scanned and visualize the tracked FOD that has been found and its position in order to send a report that the operator can erase from the runway. The proposed system was assessed in real-time testing and a built-in Simulation under GAZEBO using the commercial quad copter Bebop connected to a base station operating under the Robot Operating System (ROS). our approach successfully identified several FODs using a combination of YOLOv5 and deepsort with an inference speed of 30 fps with a high accuarcy over 80%. The advantages of this system is the fulfilment of the FAA performance criteria of an AFDS, it facilitate the FOD scanning operation by using a graphical user interface that allow the operator to start the FOD scanning operation by selecting only the interested area in the runway, drone navigation tests with a 10 m/s wind speed were satisfactory, as well as it's ability to locate and send report of the detected FODs with small distance error less than 40 cm while a drone navigate with a 5m/s speed.
{"title":"Automated Foreign Object Debris Detection System based on UAV","authors":"Chadi M'Sila, R. Ayad, N. A. Oufroukh","doi":"10.1109/ICNSC55942.2022.10004050","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004050","url":null,"abstract":"The presence of Foreign Object Debris (FOD) on airport platforms constitutes a big risk, both for aircraft and for personnel. This debris, whatever its nature or size, whether it's a private effect, a tool, a component from an aircraft, or any object, As soon because it isn't observed and removed, it's liable becoming a FOD within the moving area. FOD can even be violently projected by jet blast, which might cause damage to other aircraft and injure personnel on the bottom, This paper discuss briefly FOD detection systems and the use of unmanned aerial systems for an automated FOD detection system on runways, which involves taking images of the runway with an Unmanned Aerial Vehicle (UAV), which could be detected and identified using artificial intelligence techniques. The method for determining an exact FOD position from aerial data is described in this study using a perspective projection transformation is used to determine the object's location in the field. For accurate findings, a strong object detection is essential, which is why the cutting-edge deep neural network YOLOV5 is used with both DeepSort Object tracking method. The paper represent an Automated UAV Navigation with PID control based for path tracking. A GUI that has been developed alow the operator to select the runway's intended path to be scanned and visualize the tracked FOD that has been found and its position in order to send a report that the operator can erase from the runway. The proposed system was assessed in real-time testing and a built-in Simulation under GAZEBO using the commercial quad copter Bebop connected to a base station operating under the Robot Operating System (ROS). our approach successfully identified several FODs using a combination of YOLOv5 and deepsort with an inference speed of 30 fps with a high accuarcy over 80%. The advantages of this system is the fulfilment of the FAA performance criteria of an AFDS, it facilitate the FOD scanning operation by using a graphical user interface that allow the operator to start the FOD scanning operation by selecting only the interested area in the runway, drone navigation tests with a 10 m/s wind speed were satisfactory, as well as it's ability to locate and send report of the detected FODs with small distance error less than 40 cm while a drone navigate with a 5m/s speed.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115574651","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004138
Qiang-Zhang, Wen-Feng Li, Jingyu Zhou
To improve the efficiency of container terminal transshipment, the process of dual AGV's no-load formation running to the handling point from the control point of view is studied in this paper. It focuses on the formation process stability and the accuracy of dual AGVs parking at the destination. In this study, the leader-follower formation strategy is used to calculate the desired position and posture of the follower AGV. The position and posture errors are analyzed based on the kinematics model of AGV with nonholonomic constraints. Moreover, the sliding mode controller is designed, which uses position and posture errors as the control parameters. Finally, linear and curvilinear conditions are used to test the comprehensive performance of the formation strategy and controller. Simulation results show that the designed controller achieves fast formation and stable formation kept of dual AGVs with different initial errors. Foremost, the high accuracy in position and posture of dual AGVs parking at the destination can shorten adaptation time between the spreader and AGVs, which proves the dual AGVs formation scheme and controller designed in this paper are feasible and effective.
{"title":"No-Load Formation Control of Dual AGVs Based on Container Terminals","authors":"Qiang-Zhang, Wen-Feng Li, Jingyu Zhou","doi":"10.1109/ICNSC55942.2022.10004138","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004138","url":null,"abstract":"To improve the efficiency of container terminal transshipment, the process of dual AGV's no-load formation running to the handling point from the control point of view is studied in this paper. It focuses on the formation process stability and the accuracy of dual AGVs parking at the destination. In this study, the leader-follower formation strategy is used to calculate the desired position and posture of the follower AGV. The position and posture errors are analyzed based on the kinematics model of AGV with nonholonomic constraints. Moreover, the sliding mode controller is designed, which uses position and posture errors as the control parameters. Finally, linear and curvilinear conditions are used to test the comprehensive performance of the formation strategy and controller. Simulation results show that the designed controller achieves fast formation and stable formation kept of dual AGVs with different initial errors. Foremost, the high accuracy in position and posture of dual AGVs parking at the destination can shorten adaptation time between the spreader and AGVs, which proves the dual AGVs formation scheme and controller designed in this paper are feasible and effective.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128231652","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004176
G. Tommasi, Carlo Motta, A. Petrillo, S. Santini
When dealing with security and safety problems, Discrete Events Systems (DESs) could be a convenient way to model the behavior of distributed dynamical systems. The aim of this work is to tailor the DES framework to Autonomous Connected vehicles (ACVs) applications so that it can model their behavior when approaching an unsignalized intersection. Specifically, in this paper, DES networked supervisors are de-signed for managing the interactions among self-driving cars when negotiating access to a traffic junction in the presence of communication delays. By exploiting the concepts of delay observability and controllability, we propose different supervisor solutions to assess the resilience of the intersection crossing to communication delays and we disclose the best suitable for the automotive application, as well as its effectiveness.
{"title":"Design of Resilient Supervisory Control for Autonomous Connected Vehicles Approaching Unsignalized Intersection in presence of Communication Delays","authors":"G. Tommasi, Carlo Motta, A. Petrillo, S. Santini","doi":"10.1109/ICNSC55942.2022.10004176","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004176","url":null,"abstract":"When dealing with security and safety problems, Discrete Events Systems (DESs) could be a convenient way to model the behavior of distributed dynamical systems. The aim of this work is to tailor the DES framework to Autonomous Connected vehicles (ACVs) applications so that it can model their behavior when approaching an unsignalized intersection. Specifically, in this paper, DES networked supervisors are de-signed for managing the interactions among self-driving cars when negotiating access to a traffic junction in the presence of communication delays. By exploiting the concepts of delay observability and controllability, we propose different supervisor solutions to assess the resilience of the intersection crossing to communication delays and we disclose the best suitable for the automotive application, as well as its effectiveness.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130877135","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 : 2022-12-15DOI: 10.1109/ICNSC55942.2022.10004137
Xiaolin Wang, Q. Kang, Mengchu Zhou
Multi-task optimization (MTO) is a novel emerging evolutionary computation paradigm that is used for solving multiple optimization tasks concurrently. Most MTO algorithms limit each individual to one task, and thus weaken the performance of information exchange. To address this issue and improve the efficiency of knowledge transfer, this work proposes an efficient MTO framework named individually-guided multi-task optimization (IMTO). It divides evolutions into vertical and horizontal ones. To further improve the efficiency of knowledge transfer, a partial individuals' learning scheme is used to choose suitable individuals to learn from other tasks. Experimental results show its superior advantages over the multifactorial evolutionary algorithm and its variants.
{"title":"Individually-guided Evolutionary Algorithm for Solving Multi-task Optimization Problems","authors":"Xiaolin Wang, Q. Kang, Mengchu Zhou","doi":"10.1109/ICNSC55942.2022.10004137","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004137","url":null,"abstract":"Multi-task optimization (MTO) is a novel emerging evolutionary computation paradigm that is used for solving multiple optimization tasks concurrently. Most MTO algorithms limit each individual to one task, and thus weaken the performance of information exchange. To address this issue and improve the efficiency of knowledge transfer, this work proposes an efficient MTO framework named individually-guided multi-task optimization (IMTO). It divides evolutions into vertical and horizontal ones. To further improve the efficiency of knowledge transfer, a partial individuals' learning scheme is used to choose suitable individuals to learn from other tasks. Experimental results show its superior advantages over the multifactorial evolutionary algorithm and its variants.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125409551","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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