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Research Article

BEST PAPER 2021

Big Data Analytics and Artificial Intelligence Techniques for Complex Systems


Submission Deadline: 30 May 2021 (closed)

Abstract

This article has no abstract.

Keywords

Potential topics include but are not limited to the following:
• Complex system modeling in the cloud/edge/IoT environment
• Knowledge-based collaboration in complex systems
• Decision-making collaboration over big data for complex systems
• Computational intelligence and Mathematical Modelling in big data-driven complex systems
• Collaborative machine learning models for complex systems
• IoT and Big Data Analytic Optimization and Machine Learning
• Collaborative recommendation methods over big data for complex systems
• Security, privacy, and trust issues in a big data-driven complex system
• Modelling and analysis of complex systems
• Optimization and control of complex systems
• Evolutionary analysis of complex systems
• Data-driven modeling and simulation of complex systems
• Machine learning techniques in model and simulation of complex systems
  • Research Article

    BEST PAPER 2021

    Multi-Level Knowledge Engineering Approach for Mapping Implicit Aspects to Explicit Aspects

    Jibran Mir1, Azhar Mahmood2,*, Shaheen Khatoon3 CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3491-3509, 2022, DOI:10.32604/cmc.2022.019952
    Abstract Aspect's extraction is a critical task in aspect-based sentiment analysis, including explicit and implicit aspects identification. While extensive research has identified explicit aspects, little effort has been put forward on implicit aspects extraction due to the complexity of the problem. Moreover, existing research on implicit aspect identification is widely carried out on product reviews targeting specific aspects while neglecting sentences’ dependency problems. Therefore, in this paper, a multi-level knowledge engineering approach for identifying implicit movie aspects is proposed. The proposed method first identifies explicit aspects using a variant of BiLSTM and CRF (Bidirectional Long Short Memory-Conditional Random Field), which serve… More >

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  • Research Article

    BEST PAPER 2021

    Utilization of Machine Learning Methods in Modeling Specific Heat Capacity of Nanofluids

    Mamdouh El Haj Assad1, Ibrahim Mahariq2, Raymond Ghandour2, Mohammad Alhuyi Nazari3, Thabet Abdeljawad4,5,6,* CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 361-374, 2022, DOI:10.32604/cmc.2022.019048
    Abstract Nanofluids are extensively applied in various heat transfer mediums for improving their heat transfer characteristics and hence their performance. Specific heat capacity of nanofluids, as one of the thermophysical properties, performs principal role in heat transfer of thermal mediums utilizing nanofluids. In this regard, different studies have been carried out to investigate the influential factors on nanofluids specific heat. Moreover, several regression models based on correlations or artificial intelligence have been developed for forecasting this property of nanofluids. In the current review paper, influential parameters on the specific heat capacity of nanofluids are introduced. Afterwards, the proposed models for their… More >

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  • Research Article

    BEST PAPER 2021

    Modeling CO2 Emission of Middle Eastern Countries Using Intelligent Methods

    Mamdouh El Haj Assad1, Ibrahim Mahariq2,*, Zaher Al Barakeh2, Mahmoud Khasawneh2, Mohammad Ali Amooie3 CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3767-3781, 2021, DOI:10.32604/cmc.2021.018872
    Abstract CO2 emission is considerably dependent on energy consumption and on share of energy sources as well as on the extent of economic activities. Consequently, these factors must be considered for CO2 emission prediction for seven middle eastern countries including Iran, Kuwait, United Arab Emirates, Turkey, Saudi Arabia, Iraq and Qatar. In order to propose a predictive model, a Multilayer Perceptron Artificial Neural Network (MLP ANN) is applied. Three transfer functions including logsig, tansig and radial basis functions are utilized in the hidden layer of the network. Moreover, various numbers of neurons are applied in the structure of the models. It… More >

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  • Research Article

    BEST PAPER 2021

    Automatic PV Grid Fault Detection System with IoT and LabVIEW as Data Logger

    Rohit Samkria1, Mohammed Abd-Elnaby2, Rajesh Singh3, Anita Gehlot3, Mamoon Rashid4,*, Moustafa H. Aly5, Walid El-Shafai6 CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1709-1723, 2021, DOI:10.32604/cmc.2021.018525
    Abstract Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum power. In the LabVIEW environment,… More >

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  • Research Article

    BEST PAPER 2021

    Advanced Community Identification Model for Social Networks

    Farhan Amin1, Jin-Ghoo Choi2, Gyu Sang Choi2,* CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1687-1707, 2021, DOI:10.32604/cmc.2021.017870
    Abstract Community detection in social networks is a hard problem because of the size, and the need of a deep understanding of network structure and functions. While several methods with significant effort in this direction have been devised, an outstanding open problem is the unknown number of communities, it is generally believed that the role of influential nodes that are surrounded by neighbors is very important. In addition, the similarity among nodes inside the same cluster is greater than among nodes from other clusters. Lately, the global and local methods of community detection have been getting more attention. Therefore, in this… More >

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