Jing-Hua Zhao^1,†, Da-Lin Zeng^2,*, Ting-Wei Zhou^1,‡, Ze-Chao Zhu^1,§

Computer Systems Science and Engineering, Vol.35, No.3, pp. 151-172, 2020, DOI:10.32604/csse.2020.35.151

Abstract Given the government subsidies for new energy vehicles, this study is conducted to study the closed-loop supply chain comprising individual manufacturers, individual retailers and individual third-party recyclers. In this paper, combine the reality of new energy vehicles with the relevant research of game theory, and establish an no government subsidy model (Model N), a government subsidized consumer model (Model C), a government subsidized manufacturer model (Model M), a government subsidized third party recycler model (Model T), and a government subsidized retailer model (Model R) for quantitative research. Then, numerical examples are used to simulate the More >

Vitaliy Mezhuyev^1,*, Yurii Gunchenko², Sergey Shvorov³, Dmitry Chyrchenko³

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 121-132, 2020, DOI:10.31209/2019.100000133

Abstract The widespread distribution of precision farming systems necessitates improvements in the methods for the control of unmanned harvesting equipment (UHE). While unmanned aerial vehicles (UAVs) provide an effective solution to this problem, there are many challenges in the implementation of technology. This paper considers the problem of identifying optimal routes of UHE movement as a multicriteria evaluation problem, which can be solved by a nonlinear scheme of compromises. The proposed method uses machine learning algorithms and statistical processing of the spectral characteristics obtained from UAV digital images. Developed method minimizes the resources needed for a More >

Fei Li^{1, *}, Jiayan Zhang¹, Edward Szczerbicki², Jiaqi Song¹, Ruxiang Li ¹, Renhong Diao¹

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 653-681, 2020, DOI:10.32604/cmc.2020.011264 - 23 July 2020

Abstract The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated the intrusion detection system based on the in-vehicle system. We combined two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the detection of intrusive behavior. In order to More >

Guanghui Yu¹, Honghui Fan¹, Hongyan Zhou¹, Tao Wu¹, Hongjin Zhu^{1, *}

Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501 - 15 July 2020

Abstract When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy More >

Pengshou Xie¹, Guoqiang Ma^{1, *}, Tao Feng¹, Yan Yan^{1, 2}, Xueming Han¹

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1127-1137, 2020, DOI:10.32604/cmc.2020.09695 - 10 June 2020

Abstract Undoubtedly, uncooperative or malicious nodes threaten the safety of Internet of Vehicles (IoV) by destroying routing or data. To this end, some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication, data, energy, etc., to detect and evaluate vehicle nodes. However, it is difficult to effectively assess the trust level of a vehicle node only by message forwarding, data consistency, and energy sufficiency. In order to resolve these problems, a novel mechanism and a new trust calculating model is proposed in this… More >

Wenxi Han^{1, 2}, Mingzhi Cheng^{3, *}, Min Lei^{1, 2}, Hanwen Xu², Yu Yang^{1, 2}, Lei Qian⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1025-1038, 2020, DOI:10.32604/cmc.2020.09815 - 10 June 2020

Abstract In recent years, with the continuous advancement of the intelligent process of the Internet of Vehicles (IoV), the problem of privacy leakage in IoV has become increasingly prominent. The research on the privacy protection of the IoV has become the focus of the society. This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms, proposes a privacy protection system structure based on untrusted data collection server, and designs a vehicle location acquisition algorithm based on a local differential privacy and game model. The algorithm first meshes the road… More >

Muhammad Waqas^{1, 2}, Shanshan Tu^{1, 3, *}, Sadaqat Ur Rehman¹, Zahid Halim², Sajid Anwar², Ghulam Abbas², Ziaul Haq Abbas⁴, Obaid Ur Rehman⁵

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821 - 20 May 2020

Abstract Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes More >

Siyang Piao¹, Huajiang Ouyang^{1, 2}, Yahui Zhang^{1, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 571-591, 2020, DOI:10.32604/cmes.2020.08789 - 01 February 2020

Abstract A beam approximation method for dynamic analysis of launch vehicles modelled as stiffened cylindrical shells is proposed. Firstly, an initial beam model of the stiffened cylindrical shell is established based on the cross-sectional area equivalence principle that represents the shell skin and its longitudinal ribs as a beam with annular cross-section, and the circumferential ribs as lumped masses at the nodes of the beam elements. Then, a fine finite element model (FE model) of the stiffened cylindrical shell is constructed and a modal analysis is carried out. Finally, the initial beam model is improved through… More >

Xiang Cao^1,2,3, Haichun Yu^1,3, Hongbing Sun^1,3

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 25-34, 2019, DOI:10.31209/2018.100000038

Abstract For cooperative hunting by a multi-AUV (multiple autonomous underwater vehicles) team, not only basic problems such as path planning and collision avoidance should be considered but also task assignments in a dynamic way. In this paper, an integrated algorithm is proposed by combining the self-organizing map (SOM) neural network and the Glasius Bio-Inspired Neural Network (GBNN) approach to improve the efficiency of multi-AUV cooperative hunting. With this integrated algorithm, the SOM neural network is adopted for dynamic allocation, while the GBNN is employed for path planning. It deals with various situations for single/multiple target(s) hunting More >

Jian Wang¹, Tao Zhang^1,*, Bonan Jin¹, Shaoen Wu²

Journal of Cyber Security, Vol.1, No.1, pp. 1-10, 2019, DOI:10.32604/jcs.2019.05818

Abstract This paper presents a novel SINS/IUSBL integration navigation strategy for underwater vehicles. Based on the principle of inverted USBL (IUSBL), a SINS/IUSBL integration navigation system is established, where the USBL device and the SINS are both rigidly mounted onboard the underwater vehicle, and fully developed in-house, the integration navigation system will be able to provide the absolute position of the underwater vehicle with a transponder deployed at a known position beforehand. Furthermore, the state error equation and the measurement equation of SINS/IUSBL integration navigation system are derived, the difference between the position calculated by SINS More >