In order to optimize the movement performance of intelligent wheelchair through narrow environment and turning obstacle avoidance, and realize the speed change of wheelchair more smooth and stable, based on the principle of speed planning, this paper designs and develops a new intelligent wheelchair movement control system, and uses STM32 control chip for hardware circuit design and main software programming. The motion control driver is applied to the power system of the wheelchair, which drives two 24V DC motors to work together. Good results are obtained through experiments, and better driving control for the intelligent wheelchair is realized.
{"title":"Design of intelligent wheelchair control system based on speed planning","authors":"S. Zeng, Xiaochong Tian","doi":"10.1117/12.2690059","DOIUrl":"https://doi.org/10.1117/12.2690059","url":null,"abstract":"In order to optimize the movement performance of intelligent wheelchair through narrow environment and turning obstacle avoidance, and realize the speed change of wheelchair more smooth and stable, based on the principle of speed planning, this paper designs and develops a new intelligent wheelchair movement control system, and uses STM32 control chip for hardware circuit design and main software programming. The motion control driver is applied to the power system of the wheelchair, which drives two 24V DC motors to work together. Good results are obtained through experiments, and better driving control for the intelligent wheelchair is realized.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"39 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121316616","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 flexible load characteristics of regenerative electric heating are studied, and firstly, its load characteristics are modelled through the analysis of its operating characteristics; secondly, the central point clustering algorithm is used to aggregate the electric heating loads, which makes the parameters of each aggregated group approximate; then, the electric heating system is clustered according to the parameters such as the radiation coefficient of the user's residence and the temperature rise coefficient of the regenerative heating system. The mathematical model of the electric heating system was established; through examples, the regulation capacity and regulation response duration of the electric heating system were simulated and analysed. Finally, the proposed load model for the operation of the thermal storage electric heating aggregates is validated, and its control potential is analysed.
{"title":"Research on the adjustable potential of flexible loads based on storage electric heating","authors":"Yu Long, Yongli Wang, Wenjun Ruan, Mingyang Zhu, Z. Yan, Yunfei Zhang, Meimei Duan","doi":"10.1117/12.2689643","DOIUrl":"https://doi.org/10.1117/12.2689643","url":null,"abstract":"In this paper, the flexible load characteristics of regenerative electric heating are studied, and firstly, its load characteristics are modelled through the analysis of its operating characteristics; secondly, the central point clustering algorithm is used to aggregate the electric heating loads, which makes the parameters of each aggregated group approximate; then, the electric heating system is clustered according to the parameters such as the radiation coefficient of the user's residence and the temperature rise coefficient of the regenerative heating system. The mathematical model of the electric heating system was established; through examples, the regulation capacity and regulation response duration of the electric heating system were simulated and analysed. Finally, the proposed load model for the operation of the thermal storage electric heating aggregates is validated, and its control potential is analysed.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121342993","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, from the four main steps of topology transformation, network topology analysis, equipment modeling and data generation strategy, the CIM/XML data including AC/DC system is converted to the input data of power flow calculation. Firstly, from the perspective of switching topology between devices, Depth First Search algorithm (DFS) search and device topology splicing are carried out to realize the conversion from switch/node model to bus/branch model. Secondly, after the active topological islands are screened and the non-live devices are eliminated, the influence of the converter modeling in CIM/XML on the selection of AC and DC nodes is emphatically analyzed, and then the selection rules of DC nodes and the strategy of DC data generation with universality are proposed. Finally, taking the CIM/XML data derived from the Southern power grid of China with a voltage of 500kV and above as an example, the power flow calculation results are compared with the measured SCADA data to verify the effectiveness of the proposed strategy.
本文从拓扑转换、网络拓扑分析、设备建模和数据生成策略四个主要步骤，将包括交直流系统在内的CIM/XML数据转换为潮流计算的输入数据。首先，从设备间交换拓扑的角度出发，进行深度优先搜索算法(Depth First Search algorithm, DFS)搜索和设备拓扑拼接，实现交换机/节点模型到总线/分支模型的转换;其次，在筛选出有源拓扑孤岛、剔除非带电设备后，重点分析了CIM/XML中变流器建模对交直流节点选择的影响，提出了直流节点选择规则和通用性DC数据生成策略;最后，以中国南方500kV及以上电压电网的CIM/XML数据为例，将潮流计算结果与实测的SCADA数据进行对比，验证了所提策略的有效性。
{"title":"Data generation strategy of power flow calculation for AC/DC hybrid system","authors":"Yaohui Huang, Zhiqiang Song, Jianzhong Xu, Xiufang Jia","doi":"10.1117/12.2689819","DOIUrl":"https://doi.org/10.1117/12.2689819","url":null,"abstract":"In this paper, from the four main steps of topology transformation, network topology analysis, equipment modeling and data generation strategy, the CIM/XML data including AC/DC system is converted to the input data of power flow calculation. Firstly, from the perspective of switching topology between devices, Depth First Search algorithm (DFS) search and device topology splicing are carried out to realize the conversion from switch/node model to bus/branch model. Secondly, after the active topological islands are screened and the non-live devices are eliminated, the influence of the converter modeling in CIM/XML on the selection of AC and DC nodes is emphatically analyzed, and then the selection rules of DC nodes and the strategy of DC data generation with universality are proposed. Finally, taking the CIM/XML data derived from the Southern power grid of China with a voltage of 500kV and above as an example, the power flow calculation results are compared with the measured SCADA data to verify the effectiveness of the proposed strategy.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126479377","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 decision-making trial and evaluation of laboratory method (DEMATEL) can effectively analyze the relationship between the intrinsic factors of complex systems, so it is widely used in many fields. In this paper, based on a new ordered weighted average operator of three-parameter interval grey number (TPIGN-OWA), a novel DEMATEL model is given, which has three advantages: The first one is that the three-parameter interval grey number (TPIGN) can reflect the real intention of the decision maker more than the interval grey number. The second one is that the new TPIGN-OWA takes into account the weight of the two intervals assembly, thus, the intention of experts can be more accurately expressed. The last one is that in the decision-making process, it is not necessary for the decision-maker to have strong mathematical knowledge background, but only to give the corresponding TPIGN according to the scale of the importance of factors, which is easier for the decision-maker to operate. Finally, this method is applied to the evaluation of fire safety management, and its the effectiveness and practicability is verified.
{"title":"Research on DEMATEL method based on three-parameter interval grey number and its application","authors":"Huabin Cheng, Ping Xiong","doi":"10.1117/12.2689338","DOIUrl":"https://doi.org/10.1117/12.2689338","url":null,"abstract":"The decision-making trial and evaluation of laboratory method (DEMATEL) can effectively analyze the relationship between the intrinsic factors of complex systems, so it is widely used in many fields. In this paper, based on a new ordered weighted average operator of three-parameter interval grey number (TPIGN-OWA), a novel DEMATEL model is given, which has three advantages: The first one is that the three-parameter interval grey number (TPIGN) can reflect the real intention of the decision maker more than the interval grey number. The second one is that the new TPIGN-OWA takes into account the weight of the two intervals assembly, thus, the intention of experts can be more accurately expressed. The last one is that in the decision-making process, it is not necessary for the decision-maker to have strong mathematical knowledge background, but only to give the corresponding TPIGN according to the scale of the importance of factors, which is easier for the decision-maker to operate. Finally, this method is applied to the evaluation of fire safety management, and its the effectiveness and practicability is verified.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125734564","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}
This article introduces deep learning into the multiple-input multiple-output (MIMO) sparse code multiple access (SCMA) system and proposes a MIMO-SCMA detection scheme based on deep neural networks (DNN) to improve bit error rate (BER) performance. The DNN learns the codebook of each user through channel feature learning on different transmission antennas. The fully connected DNN is designed as the decoder at the receiving end, which does not require traditional multi-antenna detection and multi-user detection, and can obtain user data with one decoding operation. The encoder and decoder are trained using an end-to-end training method. All learning models of the DNN are generated offline and the learned models are used for online testing. In this model, the received signal and channel coefficients are set as input data, and the label corresponding to the transmitted symbol is set as output data for offline learning. After offline learning is completed, the model can be deployed online with fixed weights and biases. Through simulation experiments, the proposed DNN encoder-decoder method can reduce the BER and computational complexity of the receiver in the MIMO-SCMA system.
{"title":"Deep neural network for MIMO-SCMA detection","authors":"Shiwei Zhang, Wenping Ge","doi":"10.1117/12.2689814","DOIUrl":"https://doi.org/10.1117/12.2689814","url":null,"abstract":"This article introduces deep learning into the multiple-input multiple-output (MIMO) sparse code multiple access (SCMA) system and proposes a MIMO-SCMA detection scheme based on deep neural networks (DNN) to improve bit error rate (BER) performance. The DNN learns the codebook of each user through channel feature learning on different transmission antennas. The fully connected DNN is designed as the decoder at the receiving end, which does not require traditional multi-antenna detection and multi-user detection, and can obtain user data with one decoding operation. The encoder and decoder are trained using an end-to-end training method. All learning models of the DNN are generated offline and the learned models are used for online testing. In this model, the received signal and channel coefficients are set as input data, and the label corresponding to the transmitted symbol is set as output data for offline learning. After offline learning is completed, the model can be deployed online with fixed weights and biases. Through simulation experiments, the proposed DNN encoder-decoder method can reduce the BER and computational complexity of the receiver in the MIMO-SCMA system.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126169981","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}
A lightweight network based on YOLOv5 is proposed in this paper to improve the real-time detection ability of underwater targets for fishing gear and to solve the difficulty of deploying model algorithms on embedded devices. First, the Shuffle_Block module replaces the leading feature extraction network in YOLOv5, reducing parameters and improving the algorithm's inference speed. Second, this module is combined with depthwise separable convolution to construct the feature fusion Shuffle-PANet, significantly reducing network parameters and improving detection speed while ensuring accuracy. The proposed method in this paper has been verified to reduce the parameter count by 89% compared to the YOLOv5 source code while doubling the detection speed of the source code. Additionally, the weight file size is reduced by 83%. The mAP50 reaches 96.3%, which is only a 2% decrease compared to YOLOv5. The lightweight network proposed in this paper can recognize sea cucumbers well and has fast recognition speed and lightweight design characteristics. Shuffle-YOLOv5 has significant advantages compared to the original model and can complete real-time target detection on low-power embedded devices.
{"title":"A sea cucumber recognition network based on improved YOLOv5","authors":"Qian Xiao, Lide Zhao, Hao Chen, Qian Li","doi":"10.1117/12.2689413","DOIUrl":"https://doi.org/10.1117/12.2689413","url":null,"abstract":"A lightweight network based on YOLOv5 is proposed in this paper to improve the real-time detection ability of underwater targets for fishing gear and to solve the difficulty of deploying model algorithms on embedded devices. First, the Shuffle_Block module replaces the leading feature extraction network in YOLOv5, reducing parameters and improving the algorithm's inference speed. Second, this module is combined with depthwise separable convolution to construct the feature fusion Shuffle-PANet, significantly reducing network parameters and improving detection speed while ensuring accuracy. The proposed method in this paper has been verified to reduce the parameter count by 89% compared to the YOLOv5 source code while doubling the detection speed of the source code. Additionally, the weight file size is reduced by 83%. The mAP50 reaches 96.3%, which is only a 2% decrease compared to YOLOv5. The lightweight network proposed in this paper can recognize sea cucumbers well and has fast recognition speed and lightweight design characteristics. Shuffle-YOLOv5 has significant advantages compared to the original model and can complete real-time target detection on low-power embedded devices.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121009828","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}
Motion modeling and temporal modeling are crucial issues for video behavior recognition. When extracting motion information in two-stream network, the optical flow diagram needs to be calculated in advance and the end-to-end training cannot be realized. 3D CNNs can extract spatiotemporal information, but it requires huge computational resources. To solve these problems, we propose a plug-and-play motion capture and enhancement network (MCE) in this paper, which consists of a temporal motion capture module (TMC) and a multi-scale spatiotemporal enhancement module (MSTE). The TMC module calculates the temporal difference of the feature-level and captures the key motion information in the short temporal range. The MSTE module simulates long-range temporal information by equivalent enlarging the temporal sensitive field through multi-scale hierarchical sub-convolution architecture, and then further enhances the significant motion features by referring to the maxpooling branch. Finally, several experiments are carried out on the behavior recognition standard datasets of Something-Something-V1 and Jester, and the recognition accuracy rates are 49.6% and 96.9%, respectively. Experimental results show that the proposed method is effective and efficient.
{"title":"Behavior recognition algorithm based on motion capture and enhancement","authors":"Yuqi Yang, Jianping Luo","doi":"10.1117/12.2689663","DOIUrl":"https://doi.org/10.1117/12.2689663","url":null,"abstract":"Motion modeling and temporal modeling are crucial issues for video behavior recognition. When extracting motion information in two-stream network, the optical flow diagram needs to be calculated in advance and the end-to-end training cannot be realized. 3D CNNs can extract spatiotemporal information, but it requires huge computational resources. To solve these problems, we propose a plug-and-play motion capture and enhancement network (MCE) in this paper, which consists of a temporal motion capture module (TMC) and a multi-scale spatiotemporal enhancement module (MSTE). The TMC module calculates the temporal difference of the feature-level and captures the key motion information in the short temporal range. The MSTE module simulates long-range temporal information by equivalent enlarging the temporal sensitive field through multi-scale hierarchical sub-convolution architecture, and then further enhances the significant motion features by referring to the maxpooling branch. Finally, several experiments are carried out on the behavior recognition standard datasets of Something-Something-V1 and Jester, and the recognition accuracy rates are 49.6% and 96.9%, respectively. Experimental results show that the proposed method is effective and efficient.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122661132","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 radio spectrum technology, the modulated signals are susceptible to multipath interference, the bit error rate is increased under multipath conditions, and the signal is distorted. The article proposes a modulation signal transmission interference suppression method based on passive time reversal mirror technology in radio spectrum technology, the interference signal is suppressed during transmission to realize lossless transmission. Firstly, a multipath transmission channel model is established in information transmission. Fractional interval balanced technology is used for channel equalization design, and passive time reversal mirror is used for intercode interference suppression and blind signal separation, The lossless transmission of modulated signals is improved by passive time reversal mirror method in wireless spread spectrum communication system. Finally, System performance is tested by simulation method. The channel balance performance is better, the intercode interference is better, and communication symbol error is lower than conventional method.
{"title":"Based on reverse mirror research on lossless transmission technology of modulated signal in wireless spread spectrum communication","authors":"X. He, Shengbo He","doi":"10.1117/12.2689561","DOIUrl":"https://doi.org/10.1117/12.2689561","url":null,"abstract":"In radio spectrum technology, the modulated signals are susceptible to multipath interference, the bit error rate is increased under multipath conditions, and the signal is distorted. The article proposes a modulation signal transmission interference suppression method based on passive time reversal mirror technology in radio spectrum technology, the interference signal is suppressed during transmission to realize lossless transmission. Firstly, a multipath transmission channel model is established in information transmission. Fractional interval balanced technology is used for channel equalization design, and passive time reversal mirror is used for intercode interference suppression and blind signal separation, The lossless transmission of modulated signals is improved by passive time reversal mirror method in wireless spread spectrum communication system. Finally, System performance is tested by simulation method. The channel balance performance is better, the intercode interference is better, and communication symbol error is lower than conventional method.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131392285","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 unmanned underwater vehicle (UUV) based on waypoint navigation is used as the research object to optimize the multi-objective trajectory for the smooth operation, low energy consumption and low smooth impact required in the patrol task. The spatial trajectory of the unmanned underwater vehicle is constructed by a quintuple polynomial, and the motion trajectory is optimally solved using a quadratic programming algorithm by combining the position, velocity and acceleration requirements of the unmanned underwater vehicle at the beginning and end moments as well as the continuity constraints among the waypoints. The results show that the multi-objective quintuple polynomial-based algorithm achieves an effective multi-objective optimization of the unmanned underwater vehicle trajectory.
{"title":"Multi-objective quintuple polynomial trajectory optimization for unmanned underwater vehicles based on waypoint navigation","authors":"Tianyu Zhang, Yongliang Li","doi":"10.1117/12.2689506","DOIUrl":"https://doi.org/10.1117/12.2689506","url":null,"abstract":"The unmanned underwater vehicle (UUV) based on waypoint navigation is used as the research object to optimize the multi-objective trajectory for the smooth operation, low energy consumption and low smooth impact required in the patrol task. The spatial trajectory of the unmanned underwater vehicle is constructed by a quintuple polynomial, and the motion trajectory is optimally solved using a quadratic programming algorithm by combining the position, velocity and acceleration requirements of the unmanned underwater vehicle at the beginning and end moments as well as the continuity constraints among the waypoints. The results show that the multi-objective quintuple polynomial-based algorithm achieves an effective multi-objective optimization of the unmanned underwater vehicle trajectory.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131552519","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}
Many biomedical ontologies develop regularly and change over time. An ontology new release will update its data, containing that fix some errors in the previous version and add many new concepts to adapt to the development in the domain. Insertion of new concepts into their proper positions on a terminology is a challenging problem in the automatic enrichment of ontologies. In the past, the new concepts are always created by domain experts. Then the experts will run a traditional classifier or manual operation to insert the new concepts in proper place. With the development of technology, the methods based on Machine learning (ML) have been proposed to help terminology researchers to develop and maintain the ontologies. We propose an new approach that is based on providing only the concept name and using a Graph Convolutional Network (GCN) aggregated the sub-string neighbor information learning method. We chose a Bidirectional Long Short-term Memory Networks (Bi-LSTM) model as our classifier for the predicted task. We first tested this method within Gene Ontology (GO) 2020 January release and achieved an average of 89.68% precision and an F1 score of 0.9081 in task of predicting direct IS-A links. In comparing the January 2020 release with the March 2022 release, we predicted the links related to new concepts, our average Accuracy score was 0.6996.
{"title":"GOGCN: using deep learning to support insertion of new concepts into gene ontology","authors":"Cheng Chen, Lingyun Luo","doi":"10.1117/12.2689526","DOIUrl":"https://doi.org/10.1117/12.2689526","url":null,"abstract":"Many biomedical ontologies develop regularly and change over time. An ontology new release will update its data, containing that fix some errors in the previous version and add many new concepts to adapt to the development in the domain. Insertion of new concepts into their proper positions on a terminology is a challenging problem in the automatic enrichment of ontologies. In the past, the new concepts are always created by domain experts. Then the experts will run a traditional classifier or manual operation to insert the new concepts in proper place. With the development of technology, the methods based on Machine learning (ML) have been proposed to help terminology researchers to develop and maintain the ontologies. We propose an new approach that is based on providing only the concept name and using a Graph Convolutional Network (GCN) aggregated the sub-string neighbor information learning method. We chose a Bidirectional Long Short-term Memory Networks (Bi-LSTM) model as our classifier for the predicted task. We first tested this method within Gene Ontology (GO) 2020 January release and achieved an average of 89.68% precision and an F1 score of 0.9081 in task of predicting direct IS-A links. In comparing the January 2020 release with the March 2022 release, we predicted the links related to new concepts, our average Accuracy score was 0.6996.","PeriodicalId":118234,"journal":{"name":"4th International Conference on Information Science, Electrical and Automation Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131991187","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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