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  • Open Access

    ARTICLE

    Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm

    Ayman Khallel Al-Ani1,*, Shams Ul Arfeen Laghari2, Hariprasath Manoharan3, Shitharth Selvarajan4, Mueen Uddin5

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2261-2279, 2023, DOI:10.32604/cmc.2023.038534

    Abstract In this paper, the application of transportation systems in real-time traffic conditions is evaluated with data handling representations. The proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the system. Compared to the existing approach, the design model in the proposed method is made by dividing the computing areas into several cluster regions, thereby reducing the complex monitoring system where control errors are minimized. Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate… More >

  • Open Access

    PROCEEDINGS

    Efficient and Robust Temperature Field Simulation of Long-Distance Crude Oil Pipeline Based on Bayesian Neural Network and PDE

    Weixin Jiang1,*, Qing Yuan2, Zongze Li3, Junhua Gong3, Bo Yu4

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.08861

    Abstract The hydraulic and thermal simulation of crude oil pipeline transportation is greatly significant for the safe transportation and accurate regulation of pipelines. With reasonable basic parameters, the solution of the traditional partial differential equation (PDE) for the axial soil temperature field on the pipeline can obtain accurate simulation results, yet it brings about a low calculation efficiency problem. In order to overcome the low-efficiency problem, an efficient and robust hybrid solution model for soil temperature field coupling with Bayesian neural network and PDE is proposed, which considers the dynamic changes of boundary conditions. Four models, including the proposed hybrid model,… More >

  • Open Access

    ARTICLE

    EFFECT OF TEMPERATURE ON WATER TRANSPORTATION IN NANOCHANNEL

    Yongbin Zhang*

    Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-4, 2017, DOI:10.5098/hmt.9.16

    Abstract The flow factor approach model was used to study the effect of temperature on water transportation in a nano slit pore flow driven by the pressure. The influences of the temperature on the density and viscosity of water and on the water-wall interaction were considered. The results show that enhancing the temperature of water significantly improves water transportation in nanochannel, especially when the channel height is so low that the water non-continuum effect is significant. The mechanism of this temperature effect is that the temperature increase not only appreciably reduces the water viscosity but also considerably alleviates the water non-continuum… More >

  • Open Access

    ARTICLE

    Effect of Freeze-Thaw Cycles on Chloride Transportation in Concrete: Prediction Model and Experiment

    Yongdong Yan*, Youdong Si, Chunhua Lu, Keke Wu

    Structural Durability & Health Monitoring, Vol.17, No.3, pp. 225-238, 2023, DOI:10.32604/sdhm.2022.022629

    Abstract This research aims to investigate the effect of frost damage on chloride transportation mechanism in ordinary and fiber concrete with both theoretical and experimental methods. The proposed theoretical model takes into account the varying damage levels caused by concrete cover depth and freeze-thaw cycles, which are the two primary parameters affecting the expression of the chloride diffusion coefficient. In the experiment, three types of concrete were prepared: ordinary Portland concrete (OPC), polypropylene fiber concrete (PFC), and steel fiber concrete (SFC). These were then immersed in NaCl solution for 120 days after undergoing 10, 25, and 50 freeze-thaw cycles. The damage… More >

  • Open Access

    ARTICLE

    Research on Parking Path Planing Based on A-Star Algorithm

    Zhiliang Deng, Dong Wang*

    Journal of New Media, Vol.5, No.1, pp. 55-64, 2023, DOI:10.32604/jnm.2023.040252

    Abstract The issue of finding available parking spaces and mitigating congestion during parking is a persistent challenge for numerous car owners in urban areas. In this paper, we propose a novel method based on the A-star algorithm to calculate the optimal parking path to address this issue. We integrate a road impedance function into the conventional A-star algorithm to compute path duration and adopt a fusion function composed of path length and duration as the weight matrix for the A-star algorithm to achieve optimal path planning. Furthermore, we conduct simulations using parking lot modeling to validate the effectiveness of our approach,… More >

  • Open Access

    ARTICLE

    Non-Cooperative Game of Coordinated Scheduling of Parallel Machine Production and Transportation in Shared Manufacturing

    Peng Liu1,*, Ke Xu1,2, Hua Gong1,2

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 239-258, 2023, DOI:10.32604/cmc.2023.038232

    Abstract Given the challenges of manufacturing resource sharing and competition in the modern manufacturing industry, the coordinated scheduling problem of parallel machine production and transportation is investigated. The problem takes into account the coordination of production and transportation before production as well as the disparities in machine spatial position and performance. A non-cooperative game model is established, considering the competition and self-interest behavior of jobs from different customers for machine resources. The job from different customers is mapped to the players in the game model, the corresponding optional processing machine and location are mapped to the strategy set, and the makespan… More >

  • Open Access

    ARTICLE

    Parameter Tuned Deep Learning Based Traffic Critical Prediction Model on Remote Sensing Imaging

    Sarkar Hasan Ahmed1, Adel Al-Zebari2, Rizgar R. Zebari3, Subhi R. M. Zeebaree4,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3993-4008, 2023, DOI:10.32604/cmc.2023.037464

    Abstract Remote sensing (RS) presents laser scanning measurements, aerial photos, and high-resolution satellite images, which are utilized for extracting a range of traffic-related and road-related features. RS has a weakness, such as traffic fluctuations on small time scales that could distort the accuracy of predicted road and traffic features. This article introduces an Optimal Deep Learning for Traffic Critical Prediction Model on High-Resolution Remote Sensing Images (ODLTCP-HRRSI) to resolve these issues. The presented ODLTCP-HRRSI technique majorly aims to forecast the critical traffic in smart cities. To attain this, the presented ODLTCP-HRRSI model performs two major processes. At the initial stage, the… More >

  • Open Access

    ARTICLE

    Coordinated Scheduling of Two-Agent Production and Transportation Based on Non-Cooperative Game

    Ke Xu1,2, Peng Liu1,*, Hua Gong1,2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3279-3294, 2023, DOI:10.32604/iasc.2023.036007

    Abstract A two-agent production and transportation coordinated scheduling problem in a single-machine environment is suggested to compete for one machine from different downstream production links or various consumers. The jobs of two agents compete for the processing position on a machine, and after the processed, they compete for the transport position on a transport vehicle to be transported to two agents. The two agents have different objective functions. The objective function of the first agent is the sum of the makespan and the total transportation time, whereas the objective function of the second agent is the sum of the total completion… More >

  • Open Access

    ARTICLE

    Multiple Extreme Learning Machines Based Arrival Time Prediction for Public Bus Transport

    J. Jalaney1,*, R. S. Ganesh2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2819-2834, 2023, DOI:10.32604/iasc.2023.034844

    Abstract Due to fast-growing urbanization, the traffic management system becomes a crucial problem owing to the rapid growth in the number of vehicles The research proposes an Intelligent public transportation system where information regarding all the buses connecting in a city will be gathered, processed and accurate bus arrival time prediction will be presented to the user. Various linear and time-varying parameters such as distance, waiting time at stops, red signal duration at a traffic signal, traffic density, turning density, rush hours, weather conditions, number of passengers on the bus, type of day, road type, average vehicle speed limit, current vehicle… More >

  • Open Access

    ARTICLE

    Modeling of Hydrogen Blending on the Leakage and Diffusion of Urban Buried Hydrogen-Enriched Natural Gas Pipeline

    Yue Su1, Jingfa Li2,*, Bo Yu2, Yanlin Zhao1, Dongxu Han2, Dongliang Sun2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1315-1337, 2023, DOI:10.32604/cmes.2023.026035

    Abstract With the introduction of various carbon reduction policies around the world, hydrogen energy, as a kind of clean energy with zero carbon emission, has attracted much attention. The safe and economical transportation of hydrogen is of great significance to the development of hydrogen energy industries. Utilizing natural gas pipelines to transport hydrogen is considered to be an efficient and economical way. However, hydrogen has a higher risk of leakage due to its strong diffusion capacity and lower explosive limit than conventional natural gas. Therefore, it is of great significance to study the leakage and diffusion law of hydrogen-enriched natural gas… More > Graphic Abstract

    Modeling of Hydrogen Blending on the Leakage and Diffusion of Urban Buried Hydrogen-Enriched Natural Gas Pipeline

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