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2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)最新文献

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Multifactorial Bare Bones Sine Cosine algorithm with Chaotic-based elite learning for Multi-tasking Optimization 基于混沌精英学习的多任务优化多因子裸正弦余弦算法
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731138
Ning Li, Lei Wang, Qiaoyong Jiang, Xiaoyu Li, Bin Wang, Guangnan Zhang
{"title":"Multifactorial Bare Bones Sine Cosine algorithm with Chaotic-based elite learning for Multi-tasking Optimization","authors":"Ning Li, Lei Wang, Qiaoyong Jiang, Xiaoyu Li, Bin Wang, Guangnan Zhang","doi":"10.1109/acait53529.2021.9731138","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731138","url":null,"abstract":"The problem of multi-task optimization is a new research topic in the field of evolutionary computing in recent years, and it has attracted more and more attention from the academic community. Compared with single-objective optimization and multi-objective optimization, multi-task optimization can use the similarity and complementarity between tasks to solve different optimization tasks at the same time. However, as the population evolves to the later stage, the ability of the two tasks to learn from each other gradually declines. In order to solve this problem and enhance the effectiveness of knowledge transfer between different tasks, this paper combines the bare bone sine cosine algorithm (BBSCA) and the elite learning strategy based on chaos mapping (ELM) into MFEA, and proposes the MFBBSCA-ELM algorithm. Since BBSCA and ELM have different search neighborhoods and are highly complementary to the analog binary crossover used in the classic MFEA algorithm, this article combines BBSCA and ELM, which is also the motivation of this article. In addition, the integration of BBSCA and ELM can reduce the probability of MFEA falling into a local optimum. Finally, this article verifies the effectiveness of integrating BBSCA and ELM into MFEA on the classic MTO benchmark problem. The experimental results show that compared with the classic MFEA, the performance of the MFBBSCA-ELM proposed in this paper has been significantly improved.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133975514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Minimal-envy Conference Paper Assignment: Formulation and a Fast Iterative Algorithm 最小嫉妒会议论文分配:公式和快速迭代算法
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731163
M. Tan, Zhuocen Dai, Yuling Ren, T. Walsh, M. Aleksandrov
{"title":"Minimal-envy Conference Paper Assignment: Formulation and a Fast Iterative Algorithm","authors":"M. Tan, Zhuocen Dai, Yuling Ren, T. Walsh, M. Aleksandrov","doi":"10.1109/acait53529.2021.9731163","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731163","url":null,"abstract":"In conference review management, it is very common that many papers being assigned are not liked by some reviewers due to their specialties or personal interests. In this paper, we consider a reviewer might only envy other reviewers who get a better set of papers than his. In this context, we proposes a new bi-objective optimization assignment model to efficiently and fairly assign papers to many competing reviewers, in which an index that measures the amount of envy is introduced. A fast iterative algorithm is proposed to solve the problem. The experimental results on real datasets shows that the algorithm achieves efficient and fair results and good computing performance, especially on large scale problems. This work is also meaningful for a number of similar allocation or matching problems.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131239320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Building and Using a Supply Chain Knowledge Graph applied to the rail transit industry 供应链知识图谱的构建与应用在轨道交通行业中的应用
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731237
Shuo Li, Yu Zhang, Mengxing Huang, Hongwen Wu, Weihua Cai
{"title":"Building and Using a Supply Chain Knowledge Graph applied to the rail transit industry","authors":"Shuo Li, Yu Zhang, Mengxing Huang, Hongwen Wu, Weihua Cai","doi":"10.1109/acait53529.2021.9731237","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731237","url":null,"abstract":"In recent years, data-driven research in specific vertical fields has gained tremendous momentum. There is a huge amount of supply chains data spread across the enterprise information systems and web that we can use to build knowledge graphs. For the rail transit industry, the knowledge graph can systematically, structure and integrate the basic facts of the rail transit field, and it is also a powerful tool for storing, querying, and processing big data. However, analyzing these data to build knowledge graphs is difficult due to the heterogeneity of the sources and scale of the amount of data. This article proposes an approach to building supply chain knowledge graph by exploiting semantic technologies to reconcile the data continuously crawled from diverse sources and to support interactive queries on the data and further assist decision-making. The graph realizes the reconstruction and storage of important data, and uses Neo4j to realize the visualization of the graph. Case studies on a realistic example have shown that the approach has major potential in building supply chain knowledge graph, therefore improving the supply chain performance of the rail transit industry.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121807960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Efficient Greedy Boosting for Chinese Textbook Readability 语文教材可读性的有效贪婪增强
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731229
Fan Yang, HaoPeng Lei, Ling Tu, Min Zhang, Min Wang, ZhengJie Deng
{"title":"Efficient Greedy Boosting for Chinese Textbook Readability","authors":"Fan Yang, HaoPeng Lei, Ling Tu, Min Zhang, Min Wang, ZhengJie Deng","doi":"10.1109/acait53529.2021.9731229","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731229","url":null,"abstract":"Readability means how easy it is for learners to know the written text, and highly readable articles are easier to understand. Readability research is one of the important topics in the field of linguistics and psychology, and text readability analysis is the core of readability research. At present, the research on English readability has been relatively mature, but the research on Chinese readability is still relatively few. In this paper, a new algorithm called Fully Corrective Greedy Multi-classification Boosting(FCGM for short) is proposed to study the readability. Let FCGM and the four traditional machine learning methods which are SVM, logistic regression, Naive Bayes and random forest trained on the corpus we established. By comparing with multiple measurement indicators, it is proved that our method FCGM can achieve preferable results.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122252136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Anti-Swing Controller for Aerial Transportation System with Flexible Suspending Rope 柔性悬索空中运输系统的防摆动控制器
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731307
Zhao-xiang Zhang, Xiao Liang, Zhuangzhi Zhang, Jianda Han
{"title":"An Anti-Swing Controller for Aerial Transportation System with Flexible Suspending Rope","authors":"Zhao-xiang Zhang, Xiao Liang, Zhuangzhi Zhang, Jianda Han","doi":"10.1109/acait53529.2021.9731307","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731307","url":null,"abstract":"Numerous researches on aerial transportation uses the assumption that the payload is connected via a rigid rope. Although this assumption makes sense in most situations, it will still lose effectiveness occasionally. Therefore, this paper considers the dynamics and control of a system with flexible rope. Based on assumed mode method(AMM) and the assumption that the length of the rope remains unchanged, the dynamic model of this system is established by Euler-Lagrange techniques. Subsequently, through the energy-based analysis method, we design a nonlinear anti-swing controller. Asymptotic results are obtained with rigorous theoretical derivations provided by the Lyapunov-based stability analysis and LaSalle’s invariance theorem. Two groups of simulation results are provided to demonstrate the superior performance of the proposed controller.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121292386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of KNN prediction model in urban traffic flow prediction KNN预测模型在城市交通流预测中的应用
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731348
Yaxian Liu, Hua Yu, Hao Fang
{"title":"Application of KNN prediction model in urban traffic flow prediction","authors":"Yaxian Liu, Hua Yu, Hao Fang","doi":"10.1109/acait53529.2021.9731348","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731348","url":null,"abstract":"Traffic congestion is one of the most important problems of urban traffic. Real time prediction of urban traffic flow can provide data reference to congestion dredging and driving route planning. In order to realize real-time urban traffic flow prediction, an urban traffic flow prediction model based on K nearest neighbor (KNN) model is studied. The experimental results show that the average prediction time of the urban traffic flow prediction model based on KNN is 1.3s and the average prediction accuracy is 91.1%. It can effectively realize the real-time urban bayonet traffic flow prediction efficiently and accurately, and it is of great practical value for the traffic management department to prevent and dredge road congestion and for the driver to choose a smooth driving path.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126795978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Region-based Active Learning for Reducing Annotation Effort of ECG Waveform Segmentation 基于区域的主动学习方法减少心电波形分割的标注工作量
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731214
Qiao Xiao, Changyong Yang, Xiaoyan Zhu, Chaofeng Wang, Yaping Wan, Can Liu
{"title":"Region-based Active Learning for Reducing Annotation Effort of ECG Waveform Segmentation","authors":"Qiao Xiao, Changyong Yang, Xiaoyan Zhu, Chaofeng Wang, Yaping Wan, Can Liu","doi":"10.1109/acait53529.2021.9731214","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731214","url":null,"abstract":"Electrocardiogram (ECG) signals consists of various beat morphologies including P wave, QRS complex, and T wave. Waveform segmentation to identify those waves in ECG signals is critical to monitor heart health status and can be leveraged for automatic diagnosis of heart-related diseases. Instead of manually annotating those waves, this work studies an active learning (AL)-based ECG waveform segmentation method to reduce the annotation effort where a learning model is trained to automatically annotate ECG waves. To adapt AL for ECG waveform segmentation, we introduce a region-based AL method where multiple signal regions containing fewer consecutive signal samples within ECG frames are selected iteratively for human annotation instead of querying at the frame level. The performance of the proposed method is validated on the QT database, as it has a faster convergence rate and higher annotation accuracy compared to benchmark schemes which are based on random query and frame-level query strategies. In addition, the proposed method consumes 25% less annotation effort in average compared to the benchmark schemes.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127023982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The optimum fractional-order modeling and controlling for Ion-exchange Polymer-Metal Composite drive 离子交换聚合物-金属复合驱动的最佳分数阶建模与控制
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731202
Lanfeng Chen, Liying Cheng, Y. Lv, Xinshu Cui, Dingyu Xue
{"title":"The optimum fractional-order modeling and controlling for Ion-exchange Polymer-Metal Composite drive","authors":"Lanfeng Chen, Liying Cheng, Y. Lv, Xinshu Cui, Dingyu Xue","doi":"10.1109/acait53529.2021.9731202","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731202","url":null,"abstract":"In order to make exploratory research more meaningful, it was necessary to establish an accurate mathematical model for IPMC(Ion-exchange Polymer-Metal Composite) driver. In this paper, a method of obtaining the fractional-order model parameters (coefficients and order) by optimization of the objective function based on MATLAB fminsearch algorithm was proposed. Moreover, it was shown that the identified model by fminsearch algorithm with experimental data was fitted better comparing with higher accuracy vinagre algorithm in frequency domain. So, the stability of system was determined by more_sols function. The simulation results showed that the IPMC fractional-order mathematical model optimized by the fminsearch algorithm was accurate and stable, so it could be used to describe the IPMC driver accurately. Finally, optimum fractional-order controller was designed for IPMC fractional-order model. The feasibility and effectiveness of the controller were verified based on analysis of the simulation results.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115842327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on data analysis of English intelligent assistant teaching system based on BP neural network algorithm 基于BP神经网络算法的英语智能辅助教学系统数据分析研究
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731241
Yinghui Wang
{"title":"Research on data analysis of English intelligent assistant teaching system based on BP neural network algorithm","authors":"Yinghui Wang","doi":"10.1109/acait53529.2021.9731241","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731241","url":null,"abstract":"This study applies BP neural network to English teaching assistant system, confirms the parameters of BP neural network, then uses the students’ English test data of a university to train and test the system. The results show that the system can meet the error requirements when the parameters are fixed. Through the performance test of the test set data of the teaching aid system and comparison after the test, the results show that the error generated by the prediction results can meet the requirements of this kind of system.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Improved Teaching-Learning Optimization Algorithm based on Morlet Wavelet Variation 一种改进的基于Morlet小波变分的教学优化算法
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT) Pub Date : 2021-10-29 DOI: 10.1109/acait53529.2021.9731331
Haixuan He, Xiuxi Wei, Huajuan Huang
{"title":"An Improved Teaching-Learning Optimization Algorithm based on Morlet Wavelet Variation","authors":"Haixuan He, Xiuxi Wei, Huajuan Huang","doi":"10.1109/acait53529.2021.9731331","DOIUrl":"https://doi.org/10.1109/acait53529.2021.9731331","url":null,"abstract":"In order to overcome the weaknesses of the Teaching and Learning optimization (TLBO) algorithm in solving function optimization problems, such as easy to fall into local optimum, slow convergence at the later stage, and low solution accuracy, an improved algorithm with dynamic adaptive teaching factors and Morlet wavelet variation-based algorithms is proposed. Firstly, the improved algorithm introduces a nonlinear dynamic teaching factor to adjust the influence of teachers on students in the iterative optimization process. Secondly, in order to avoid algorithm trapped in local optimum, using Morlet wavelet to the implementation of global extreme value of each dimension in each generation wavelet disturbance, disturbance and the result was recognized as a certain probability is selected for the new position of the individual, make full use of the advantage of global extremum information guide populations to be near optimal solution quickly, by fine-tuning characteristics of wavelet functions help population out of local minima. The simulation results on 18 classical test functions show that the improved algorithm has better performance than TLBO, SLTLBO, CSA and BOA algorithms, and is suitable for solving function optimization problems. It is applied to engineering practice to solve PID parameter optimization and obtains good results.","PeriodicalId":173633,"journal":{"name":"2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128358301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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