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Search Results (15)
  • Open Access


    Improved Prediction of Metamaterial Antenna Bandwidth Using Adaptive Optimization of LSTM

    Doaa Sami Khafaga1, Amel Ali Alhussan1,*, El-Sayed M. El-kenawy2,3, Abdelhameed Ibrahim4, Said H. Abd Elkhalik3, Shady Y. El-Mashad5, Abdelaziz A. Abdelhamid6,7

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 865-881, 2022, DOI:10.32604/cmc.2022.028550

    Abstract The design of an antenna requires a careful selection of its parameters to retain the desired performance. However, this task is time-consuming when the traditional approaches are employed, which represents a significant challenge. On the other hand, machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended performance. In this paper, we propose a novel approach for accurately predicting the bandwidth of metamaterial antenna. The proposed approach is based on employing the recently emerged guided whale… More >

  • Open Access


    COVID-19 Severity Prediction Using Enhanced Whale with Salp Swarm Feature Classification

    Nebojsa Budimirovic1, E. Prabhu2, Milos Antonijevic1, Miodrag Zivkovic1, Nebojsa Bacanin1,*, Ivana Strumberger1, K. Venkatachalam3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1685-1698, 2022, DOI:10.32604/cmc.2022.023418

    Abstract Computerized tomography (CT) scans and X-rays play an important role in the diagnosis of COVID-19 and pneumonia. On the basis of the image analysis results of chest CT and X-rays, the severity of lung infection is monitored using a tool. Many researchers have done in diagnosis of lung infection in an accurate and efficient takes lot of time and inefficient. To overcome these issues, our proposed study implements four cascaded stages. First, for pre-processing, a mean filter is used. Second, texture feature extraction uses principal component analysis (PCA). Third, a modified whale optimization algorithm is used (MWOA) for a feature… More >

  • Open Access


    A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System

    Omar Almomani*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113

    Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one… More >

  • Open Access


    A Study of Unmanned Path Planning Based on a Double-Twin RBM-BP Deep Neural Network

    Xuan Chen1,*, Zhiping Wan1, Jiatong Wang2

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1531-1548, 2020, DOI:10.32604/iasc.2020.011723

    Abstract Addressing the shortcomings of unmanned path planning, such as significant error and low precision, a path-planning algorithm based on the whale optimization algorithm (WOA)-optimized double-blinking restricted Boltzmann machine-back propagation (RBM-BP) deep neural network model is proposed. The model consists mainly of two twin RBMs and one BP neural network. One twin RBM is used for feature extraction of the unmanned path location, and the other RBM is used for the path similarity calculation. The model uses the WOA algorithm to optimize parameters, which reduces the number of training sessions, shortens the training time, and reduces the training errors of the… More >

  • Open Access


    Few-Shot Learning with Generative Adversarial Networks Based on WOA13 Data

    Xin Li1,2, Yanchun Liang1,2, Minghao Zhao1,2, Chong Wang1,2,3, Yu Jiang1,2,*

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1073-1085, 2019, DOI:10.32604/cmc.2019.05929

    Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the ocean data. We use GAN… More >

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