Journal of Advanced Computational Intelligence and Intelligent Informatics最新文献_第4页

Adaptive Identification Method for Vehicle Driving Model Capable of Driving with Large Acceleration Changes and Steering 具有大加速度变化和转向能力的车辆驾驶模型的自适应识别方法

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0609

Soichiro Matsumoto, M. Saito

{"title":"Adaptive Identification Method for Vehicle Driving Model Capable of Driving with Large Acceleration Changes and Steering","authors":"Soichiro Matsumoto, M. Saito","doi":"10.20965/jaciii.2023.p0609","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0609","url":null,"abstract":"In the future, considering the expansion of the autonomous driving society, autonomous driving systems that can drive safely and quickly will be required for the purpose of saving lives and transporting goods even on rough road such as snowy, icy, and unpaved roads. In such unknown environments, technologies that combine model-based control and artificial intelligence (AI) are attracting attention for the purpose of ensuring operational stability and reliability. The second author has proposed a vehicle driving model that is robust to road geometry and ever-changing environmental disturbances. This model is based on a two-wheel model, and expresses the error in the position of the center of gravity of the vehicle by the front wheel steering angle deviation, and adaptively estimates this deviation. However, this model has large modeling errors when driving at high velocity on slippery roads. In this study, we extend this model proposed in previous study, and propose a new vehicle driving model that can handle situations such as driving with large acceleration changes and steering on bad roads such as snowy and wet roads. Then, we demonstrate the usefulness of the proposed method in a simulation using vehicle motion analysis software.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"46 1","pages":"609-615"},"PeriodicalIF":0.7,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80829556","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

Eccentric Connectivity Index of Nanosheets and Nanotube of SiO2 二氧化硅纳米片和纳米管的偏心连通性指数

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0649

A. B. Greeni, S. Jancy

引用次数: 0

Embedding Complete Bipartite Graphs into Wheel Related Graphs 将完全二部图嵌入车轮相关图

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0645

A. B. Greeni, P. L. Joshwa

引用次数: 1

A Sufficient Condition on Polynomial Inequalities and its Application to Interval Time-Varying Delay Systems 多项式不等式的一个充分条件及其在区间时变时滞系统中的应用

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0683

Meng Liu, Yong He, Lin Jiang

引用次数: 0

Local Metric Dimension of Certain Classes of Circulant Networks 一类循环网络的局部度量维数

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0554

J. Cynthia, M. Ramya, S. Prabhu

引用次数: 0

Application of Convolutional Neural Network to Gripping Comfort Evaluation Using Gripping Posture Image 卷积神经网络在夹持姿态图像夹持舒适性评价中的应用

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0655

Kazuki Hokari, Makoto Ikarashi, J. A. Pramudita, Kazuya Okada, Masato Ito, Yuji Tanabe

{"title":"Application of Convolutional Neural Network to Gripping Comfort Evaluation Using Gripping Posture Image","authors":"Kazuki Hokari, Makoto Ikarashi, J. A. Pramudita, Kazuya Okada, Masato Ito, Yuji Tanabe","doi":"10.20965/jaciii.2023.p0655","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0655","url":null,"abstract":"Gripping comfort evaluation was crucial for designing a product with good gripping comfort. In this study, a novel evaluation method using gripping posture image was constructed based on convolutional neural network (CNN). Human subject experiment was conducted to acquire gripping comfort scores and gripping posture images while gripping seven objects with simple shape and eleven manufactured products. The scores and the images were used as training set and validation set for CNN. Classification problem was employed to classify gripping posture images as comfort or discomfort. As a result, accuracies were 91.4% for simple shape objects and 76.2% for manufactured products. Regression problem was utilized to predict gripping comfort scores from gripping posture images while gripping cylindrical object. Gripping posture images of radial and dorsal sides in direction of hand were used to investigate effect of direction of hand on prediction accuracy. Consequently, mean absolute errors (MAE) of gripping comfort scores were 0.132 for radial side and 0.157 for dorsal side in direction of hand. In both problems, the results indicated that these evaluation methods were useful to evaluate gripping comfort. The evaluation methods help designers to evaluate products and enhance gripping comfort.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"75 1","pages":"655-663"},"PeriodicalIF":0.7,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80899081","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

Joint Path and Multi-Hop Communication Node Location Planning in Cluttered Environment 混沌环境下联合路径与多跳通信节点位置规划

IF 0.7

Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0664

Lihua Li, Zhihong Peng, Chengxin Wen, Peiqiao Shang, Jinqiang Cui

{"title":"Joint Path and Multi-Hop Communication Node Location Planning in Cluttered Environment","authors":"Lihua Li, Zhihong Peng, Chengxin Wen, Peiqiao Shang, Jinqiang Cui","doi":"10.20965/jaciii.2023.p0664","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0664","url":null,"abstract":"In the communication-constrained operating environment, a unmanned aerial vehicle (UAV) needs to plan a feasible path from the starting point to the endpoint while planning the node deployment location for multi-hop communication to establish an information pathway. In this study, a new algorithm was designed for joint path and multi-hop communication node location planning in cluttered environments based on rapidly-exploring random trees star (RRT*) algorithm. The maximum communication distance constraint between nodes was obtained based on the signal-free propagation model, whereas the communication node loss and path loss were established as joint optimization objectives. In bidirectional random tree growth, the structure of the trees was optimized according to the value of the loss function, and optimal path and node location planning were finally achieved through continuous growth and iteration. When tested in different complexity-barrier environments and compared to RRT*, Informed-RRT*, and IB-RRT* algorithms, the paths in the planning results of the new algorithm are close to those of the comparison algorithms; however, the number of nodes decreases significantly, which proves the effectiveness of the newly proposed algorithm.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"74 1","pages":"664-672"},"PeriodicalIF":0.7,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74079439","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

Rehabilitation Evaluation System for Lower-Limb Rehabilitation Robot 下肢康复机器人康复评估系统

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0691

Li Jiang, Juan Zhao, Feng Wang, Yujian Zhou, Wangyang Ge, Jinhua She

引用次数: 0

Offline Handwritten Chinese Character Using Convolutional Neural Network: State-of-the-Art Methods 使用卷积神经网络的离线手写汉字:最新的方法

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0567

Yingna Zhong, Kauthar Mohd Daud, Ain Najiha Binti Mohamad Nor, R. Ikuesan, Kohbalan Moorthy

{"title":"Offline Handwritten Chinese Character Using Convolutional Neural Network: State-of-the-Art Methods","authors":"Yingna Zhong, Kauthar Mohd Daud, Ain Najiha Binti Mohamad Nor, R. Ikuesan, Kohbalan Moorthy","doi":"10.20965/jaciii.2023.p0567","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0567","url":null,"abstract":"Given the presence of handwritten documents in human transactions, including email sorting, bank checks, and automating procedures, handwritten characters recognition (HCR) of documents has been invaluable to society. Handwritten Chinese characters (HCC) can be divided into offline and online categories. Online HCC recognition (HCCR) involves the trajectory movement of the pen tip for expressing linguistic content. In contrast, offline HCCR involves analyzing and categorizing the sample binary or grayscale images of characters. As recognition technology develops, academics’ interest in Chinese character recognition has continuously increased, as it significantly affects social and economic development. Recent development in this area is promising. However, the recognition accuracy of offline HCCR is still a sophisticated challenge owing to their complexity and variety of writing styles. With the advancement of deep learning, convolutional neural network (CNN)-based algorithms have demonstrated distinct benefits in offline HCCR and have achieved outstanding results. In this review, we aim to show the different HCCR methods for tackling the complexity and variability of offline HCC writing styles. This paper also reviews different activation functions used in offline HCCR and provides valuable assistance to new researchers in offline Chinese handwriting recognition by providing a succinct study of various methods for recognizing offline HCC.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"45 1","pages":"567-575"},"PeriodicalIF":0.7,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88527668","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

Exploring Model Structures to Reduce Data Requirements for Neural ODE Learning in Control Systems 探索模型结构以减少控制系统中神经ODE学习的数据需求

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Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI: 10.20965/jaciii.2023.p0537

Takanori Hashimoto, N. Matsui, N. Kamiura, T. Isokawa

引用次数: 0