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  • Open Access

    ARTICLE

    Bio-Inspired Numerical Analysis of COVID-19 with Fuzzy Parameters

    F. M. Allehiany1, Fazal Dayan2,3,*, F. F. Al-Harbi4, Nesreen Althobaiti5, Nauman Ahmed2, Muhammad Rafiq6, Ali Raza7, Mawahib Elamin8

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3213-3229, 2022, DOI:10.32604/cmc.2022.025811 - 29 March 2022

    Abstract Fuzziness or uncertainties arise due to insufficient knowledge, experimental errors, operating conditions and parameters that provide inaccurate information. The concepts of susceptible, infectious and recovered are uncertain due to the different degrees in susceptibility, infectivity and recovery among the individuals of the population. The differences can arise, when the population groups under the consideration having distinct habits, customs and different age groups have different degrees of resistance, etc. More realistic models are needed which consider these different degrees of susceptibility infectivity and recovery of the individuals. In this paper, a Susceptible, Infected and Recovered (SIR) More >

  • Open Access

    ARTICLE

    Bio-Inspired Computational Methods for the Polio Virus Epidemic Model

    Fatimah Abdulrahman Alrawajeh1, F. M. Allehiany2, Ali Raza3,*, Shaimaa A. M. Abdelmohsen4, Tahir Nawaz Cheema5, Muhammad Rafiq6, Muhammad Mohsin7

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2357-2374, 2022, DOI:10.32604/cmc.2022.024604 - 29 March 2022

    Abstract In 2021, most of the developing countries are fighting polio, and parents are concerned with the disabling of their children. Poliovirus transmits from person to person, which can infect the spinal cord, and paralyzes the parts of the body within a matter of hours. According to the World Health Organization (WHO), 18 million currently healthy people could have been paralyzed by the virus during 1988–2020. Almost all countries but Pakistan, Afghanistan, and a few more have been declared polio-free. The mathematical modeling of poliovirus is studied in the population by categorizing it as susceptible individuals… More >

  • Open Access

    ARTICLE

    Crashworthiness Design and Multi-Objective Optimization for Bio-Inspired Hierarchical Thin-Walled Structures

    Shaoqiang Xu1, Weiwei Li1,*, Lin Li2, Tao Li1, Chicheng Ma1

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 929-947, 2022, DOI:10.32604/cmes.2022.018964 - 14 March 2022

    Abstract Thin-walled structures have been used in many fields due to their superior mechanical properties. In this paper, two types of hierarchical multi-cell tubes, inspired by the self-similarity of Pinus sylvestris, are proposed to enhance structural energy absorption performance. The finite element models of the hierarchical structures are established to validate the crashworthiness performance under axial dynamic load. The theoretical model of the mean crushing force is also derived based on the simplified super folded element theory. The finite element results demonstrate that the energy absorption characteristics and deformation mode of the bionic hierarchical thin-walled tubes More >

  • Open Access

    ARTICLE

    Locomotion of Bioinspired Underwater Snake Robots Using Metaheuristic Algorithm

    Souad Larabi-Marie-Sainte1, Taiseer Abdalla Elfadil Eisa2, Fahd N. Al-Wesabi3,4, Amani Abdulrahman Albraikan5, Manar Ahmed Hamza6,*, Abdelwahed Motwakel6, Ishfaq Yaseen6, Mesfer Al Duhayyim7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1293-1308, 2022, DOI:10.32604/cmc.2022.024585 - 24 February 2022

    Abstract Snake Robots (SR) have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments, a characteristic not found in other kinds of robots (like wheeled or legged robots). Underwater Snake Robots (USR) establish a bioinspired solution in the domain of underwater robotics. It is a key challenge to increase the motion efficiency in underwater robots, with respect to forwarding speed, by enhancing the locomotion method. At the same time, energy efficiency is also considered as a crucial issue for long-term automation of the systems. In this aspect,… More >

  • Open Access

    ARTICLE

    An Improved Sparrow Search Algorithm for Node Localization in WSN

    R. Thenmozhi1, Abdul Wahid Nasir2, Vijaya Krishna Sonthi3, T. Avudaiappan4, Seifedine Kadry5, Kuntha Pin6, Yunyoung Nam7,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2037-2051, 2022, DOI:10.32604/cmc.2022.022203 - 03 November 2021

    Abstract Wireless sensor networks (WSN) comprise a set of numerous cheap sensors placed in the target region. A primary function of the WSN is to avail the location details of the event occurrences or the node. A major challenge in WSN is node localization which plays an important role in data gathering applications. Since GPS is expensive and inaccurate in indoor regions, effective node localization techniques are needed. The major intention of localization is for determining the place of node in short period with minimum computation. To achieve this, bio-inspired algorithms are used and node localization… More >

  • Open Access

    ARTICLE

    Extremal Coalitions for Influence Games Through Swarm Intelligence-Based Methods

    Fabián Riquelme1,*, Rodrigo Olivares1, Francisco Muñoz1, Xavier Molinero3, Maria Serna2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6305-6321, 2022, DOI:10.32604/cmc.2022.021804 - 11 October 2021

    Abstract An influence game is a simple game represented over an influence graph (i.e., a labeled, weighted graph) on which the influence spread phenomenon is exerted. Influence games allow applying different properties and parameters coming from cooperative game theory to the contexts of social network analysis, decision-systems, voting systems, and collective behavior. The exact calculation of several of these properties and parameters is computationally hard, even for a small number of players. Two examples of these parameters are the length and the width of a game. The length of a game is the size of its smaller… More >

  • Open Access

    ARTICLE

    Swarm-Based Extreme Learning Machine Models for Global Optimization

    Mustafa Abdul Salam1,*, Ahmad Taher Azar2, Rana Hussien2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6339-6363, 2022, DOI:10.32604/cmc.2022.020583 - 11 October 2021

    Abstract Extreme Learning Machine (ELM) is popular in batch learning, sequential learning, and progressive learning, due to its speed, easy integration, and generalization ability. While, Traditional ELM cannot train massive data rapidly and efficiently due to its memory residence, high time and space complexity. In ELM, the hidden layer typically necessitates a huge number of nodes. Furthermore, there is no certainty that the arrangement of weights and biases within the hidden layer is optimal. To solve this problem, the traditional ELM has been hybridized with swarm intelligence optimization techniques. This paper displays five proposed hybrid Algorithms… More >

  • Open Access

    ARTICLE

    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 - 22 March 2021

    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… More >

  • Open Access

    ARTICLE

    Nature-Inspired Level Set Segmentation Model for 3D-MRI Brain Tumor Detection

    Oday Ali Hassen1, Sarmad Omar Abter2, Ansam A. Abdulhussein3, Saad M. Darwish4,*, Yasmine M. Ibrahim4, Walaa Sheta5

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 961-981, 2021, DOI:10.32604/cmc.2021.014404 - 22 March 2021

    Abstract Medical image segmentation has consistently been a significant topic of research and a prominent goal, particularly in computer vision. Brain tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy preparation. To prevent or minimize manual segmentation error, automated tumor segmentation, and detection became the most demanding process for radiologists and physicians as the tumor often has complex structures. Many methods for detection and segmentation presently exist, but all lack high accuracy. This paper’s key contribution… More >

  • Open Access

    ARTICLE

    A Fuzzy-Based Bio-Inspired Neural Network Approach for Target Search by Multiple Autonomous Underwater Vehicles in Underwater Environments

    Aolin Sun, Xiang Cao*, Xu Xiao, Liwen Xu

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 551-564, 2021, DOI:10.32604/iasc.2021.01008 - 18 January 2021

    Abstract An essential issue in a target search is safe navigation while quickly finding targets. In order to improve the efficiency of a target search and the smoothness of AUV’s (Autonomous Underwater Vehicle) trajectory, a fuzzy-based bio-inspired neural network approach is proposed in this paper. A bio-inspired neural network is applied to a multi-AUV target search, which can effectively plan search paths. In the meantime, a fuzzy algorithm is introduced into the bio-inspired neural network to make the trajectory of AUV obstacle avoidance smoother. Unlike other algorithms that need repeated training in the parameters selection, the More >

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