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  • Open Access


    Artificial Fish Swarm Optimization with Deep Learning Enabled Opinion Mining Approach

    Saud S. Alotaibi1, Eatedal Alabdulkreem2, Sami Althahabi3, Manar Ahmed Hamza4,*, Mohammed Rizwanullah4, Abu Sarwar Zamani4, Abdelwahed Motwakel4, Radwa Marzouk5

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 737-751, 2023, DOI:10.32604/csse.2023.030170

    Abstract Sentiment analysis or opinion mining (OM) concepts become familiar due to advances in networking technologies and social media. Recently, massive amount of text has been generated over Internet daily which makes the pattern recognition and decision making process difficult. Since OM find useful in business sectors to improve the quality of the product as well as services, machine learning (ML) and deep learning (DL) models can be considered into account. Besides, the hyperparameters involved in the DL models necessitate proper adjustment process to boost the classification process. Therefore, in this paper, a new Artificial Fish… More >

  • Open Access


    Optimal Logistics Activities Based Deep Learning Enabled Traffic Flow Prediction Model

    Basim Aljabhan1, Mahmoud Ragab2,3,4,*, Sultanah M. Alshammari4,5, Abdullah S. Al-Malaise Al-Ghamdi4,6,7

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5269-5282, 2022, DOI:10.32604/cmc.2022.030694

    Abstract Traffic flow prediction becomes an essential process for intelligent transportation systems (ITS). Though traffic sensor devices are manually controllable, traffic flow data with distinct length, uneven sampling, and missing data finds challenging for effective exploitation. The traffic data has been considerably increased in recent times which cannot be handled by traditional mathematical models. The recent developments of statistic and deep learning (DL) models pave a way for the effectual design of traffic flow prediction (TFP) models. In this view, this study designs optimal attention-based deep learning with statistical analysis for TFP (OADLSA-TFP) model. The presented… More >

  • Open Access


    Development of an Artificial Fish Swarm Algorithm Based on a Wireless Sensor Networks in a Hydrodynamic Background

    Sheng Bai, Feng Bao*, Fengzhi Zhao, Miaomiao Liu

    FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.5, pp. 935-946, 2020, DOI:10.32604/fdmp.2020.010113

    Abstract The main objective of the present study is the development of a new algorithm that can adapt to complex and changeable environments. An artificial fish swarm algorithm is developed which relies on a wireless sensor network (WSN) in a hydrodynamic background. The nodes of this algorithm are viscous fluids and artificial fish, while related ‘events’ are directly connected to the food available in the related virtual environment. The results show that the total processing time of the data by the source node is 6.661 ms, of which the processing time of crosstalk data is 3.789… More >

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