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  • Open Access

    ARTICLE

    Deep Neural Network Architecture Search via Decomposition-Based Multi-Objective Stochastic Fractal Search

    Hongshang Xu1, Bei Dong1,2,*, Xiaochang Liu1, Xiaojun Wu1,2

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 185-202, 2023, DOI:10.32604/iasc.2023.041177 - 05 February 2024

    Abstract Deep neural networks often outperform classical machine learning algorithms in solving real-world problems. However, designing better networks usually requires domain expertise and consumes significant time and computing resources. Moreover, when the task changes, the original network architecture becomes outdated and requires redesigning. Thus, Neural Architecture Search (NAS) has gained attention as an effective approach to automatically generate optimal network architectures. Most NAS methods mainly focus on achieving high performance while ignoring architectural complexity. A myriad of research has revealed that network performance and structural complexity are often positively correlated. Nevertheless, complex network structures will bring… More >

  • Open Access

    ARTICLE

    Forecasting Energy Consumption Using a Novel Hybrid Dipper Throated Optimization and Stochastic Fractal Search Algorithm

    Doaa Sami Khafaga1, El-Sayed M. El-kenawy2, Amel Ali Alhussan1,*, Marwa M. Eid3

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2117-2132, 2023, DOI:10.32604/iasc.2023.038811 - 21 June 2023

    Abstract The accurate prediction of energy consumption has effective role in decision making and risk management for individuals and governments. Meanwhile, the accurate prediction can be realized using the recent advances in machine learning and predictive models. This research proposes a novel approach for energy consumption forecasting based on a new optimization algorithm and a new forecasting model consisting of a set of long short-term memory (LSTM) units. The proposed optimization algorithm is used to optimize the parameters of the LSTM-based model to boost its forecasting accuracy. This optimization algorithm is based on the recently emerged… More >

  • Open Access

    ARTICLE

    Hybrid Sine Cosine and Stochastic Fractal Search for Hemoglobin Estimation

    Marwa M. Eid1,*, Fawaz Alassery2, Abdelhameed Ibrahim3, Bandar Abdullah Aloyaydi4, Hesham Arafat Ali1,3, Shady Y. El-Mashad5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2467-2482, 2022, DOI:10.32604/cmc.2022.025220 - 29 March 2022

    Abstract The sample's hemoglobin and glucose levels can be determined by obtaining a blood sample from the human body using a needle and analyzing it. Hemoglobin (HGB) is a critical component of the human body because it transports oxygen from the lungs to the body's tissues and returns carbon dioxide from the tissues to the lungs. Calculating the HGB level is a critical step in any blood analysis job. The HGB levels often indicate whether a person is anemic or polycythemia vera. Constructing ensemble models by combining two or more base machine learning (ML) models can… More >

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