Special lssues

Optimization Algorithm for Intelligent Computing Application

Submission Deadline: 31 December 2022 (closed)

Guest Editors

Dr. Marwa M. Eid, Delta University for Science and Technology, Egypt.
Dr. Nima Khodadadi, Florida International University, USA.
Dr. Sunil Kumar, University of Petroleum and Energy Studies, India.
Dr. Mostafa Abotaleb, South Ural State University, Russia.

Summary

Intelligent computing data analysis is required for speedy and accurate diagnosis. To reduce human intervention and time, innovative computing-based solutions are essential. Methods based on artificial intelligence are commonly utilized to assess and mine information from biological data. Several machine learning-based tools are available for developing robust and intelligent automated systems.

This special issue covers various topics concerning Intelligent computing and its applications. We welcome the new research ideas and developments in Intelligent computing relevant to Optimization for Artificial Intelligence applications, including foundation, systems, smart applications, and other research contributions.


Keywords

Intelligent Automation
Soft Computing
Artificial intelligence applications
Computer-based algorithms
Swarm Intelligence
Evolutionary Algorithms
Computer vision
Natural language processing (NLP)
Deep learning
Machine Learning
Transfer Learning

Published Papers


  • Open Access

    ARTICLE

    Genetic Algorithm Combined with the K-Means Algorithm: A Hybrid Technique for Unsupervised Feature Selection

    Hachemi Bennaceur, Meznah Almutairy, Norah Alhussain
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2687-2706, 2023, DOI:10.32604/iasc.2023.038723
    (This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)
    Abstract The dimensionality of data is increasing very rapidly, which creates challenges for most of the current mining and learning algorithms, such as large memory requirements and high computational costs. The literature includes much research on feature selection for supervised learning. However, feature selection for unsupervised learning has only recently been studied. Finding the subset of features in unsupervised learning that enhances the performance is challenging since the clusters are indeterminate. This work proposes a hybrid technique for unsupervised feature selection called GAk-MEANS, which combines the genetic algorithm (GA) approach with the classical k-Means algorithm. In… More >

  • Open Access

    ARTICLE

    Advanced Guided Whale Optimization Algorithm for Feature Selection in BlazePose Action Recognition

    Motasem S. Alsawadi, El-Sayed M. El-kenawy, Miguel Rio
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2767-2782, 2023, DOI:10.32604/iasc.2023.039440
    (This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)
    Abstract The BlazePose, which models human body skeletons as spatiotemporal graphs, has achieved fantastic performance in skeleton-based action identification. Skeleton extraction from photos for mobile devices has been made possible by the BlazePose system. A Spatial-Temporal Graph Convolutional Network (STGCN) can then forecast the actions. The Spatial-Temporal Graph Convolutional Network (STGCN) can be improved by simply replacing the skeleton input data with a different set of joints that provide more information about the activity of interest. On the other hand, existing approaches require the user to manually set the graph’s topology and then fix it across… More >

  • Open Access

    ARTICLE

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

    Doaa Sami Khafaga, El-Sayed M. El-kenawy, Amel Ali Alhussan, Marwa M. Eid
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2117-2132, 2023, DOI:10.32604/iasc.2023.038811
    (This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)
    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

    PF-YOLOv4-Tiny: Towards Infrared Target Detection on Embedded Platform

    Wenbo Li, Qi Wang, Shang Gao
    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 921-938, 2023, DOI:10.32604/iasc.2023.038257
    (This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)
    Abstract Infrared target detection models are more required than ever before to be deployed on embedded platforms, which requires models with less memory consumption and better real-time performance while considering accuracy. To address the above challenges, we propose a modified You Only Look Once (YOLO) algorithm PF-YOLOv4-Tiny. The algorithm incorporates spatial pyramidal pooling (SPP) and squeeze-and-excitation (SE) visual attention modules to enhance the target localization capability. The PANet-based-feature pyramid networks (P-FPN) are proposed to transfer semantic information and location information simultaneously to ameliorate detection accuracy. To lighten the network, the standard convolutions other than the backbone More >

  • Open Access

    ARTICLE

    Fluid Flow and Mixed Heat Transfer in a Horizontal Channel with an Open Cavity and Wavy Wall

    Tohid Adibi, Shams Forruque Ahmed, Omid Adibi, Hassan Athari, Irfan Anjum Badruddin, Syed Javed
    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 147-163, 2023, DOI:10.32604/iasc.2023.035392
    (This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)
    Abstract Heat exchangers are utilized extensively in different industries and technologies. Consequently, optimizing heat exchangers has been a major concern among researchers. Although various studies have been conducted to improve the heat transfer rate, the use of a wavy wall in the presence of different types of heat transfer mechanisms has not been investigated. This study thus investigates the mixed heat transmission behavior of fluid in a horizontal channel with a cavity and a hot, wavy wall. The fluid flow in the channel is considered laminar, and the governing equations including continuity, momentum, and energy are… More >

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