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Bio-Inspired Computational Intelligence and Optimization Techniques for Real-World Engineering Applications

Submission Deadline: 15 June 2022 (closed)

Guest Editors

Dr. Sandeep Kautish, LBEF Campus (Asia Pacific University of Technology & Innovation, Malaysia), Nepal.
Dr. Ali Wagdy Mohamed, Cairo University, Egypt & The American University in Cairo, Egypt.
Dr. Ahmed J. Obaid, University of Kufa, Iraq.
Dr Deepmala Singh, LBEF Campus (Asia Pacific University of Technology & Innovation, Malaysia), Nepal.
Prof. Sheng Lung Peng, National Taipei University of Business, Taiwan.

Summary

Bio-inspired computational intelligence and optimization techniques are a set of novel problem-solving methodologies and approaches and have been attracted wider attention for their good performance. Exemplary examples of nature-inspired algorithms include fuzzy systems (FS), artificial neural networks (ANN), evolutionary computing (EC), and swarm intelligence (SI), and they have been proved as very effective and efficient for solving many real-world problems. These techniques are referred to as bio-inspired optimization (BIO) algorithms. BIO can be referred to as a collection of computational techniques in computer science, artificial intelligence, machine learning and some engineering disciplines which attempt to study, model, and analyze very complex real-world problems and/or phenomena.

 

This special issue will provide a systematic overview and state-of-the-art and contemporary researches in the field of computational intelligence and optimization methods and their application to various engineering applications. The primary task of this special issue is on some hybrid algorithms for solving the real-world complex constrained optimization problems from engineering domain for modeling of various benchmark design problems and hence present an efficient technique using bio-inspired optimization. In light of this, the aim of this special issue is to provide a unified platform for bringing forth and advancing the state-of-the-art in latest developments of nature-inspired algorithms, such as genetic algorithm, particle swarm optimization, ant colony optimization, migrating birds optimization, neural networks, gravitational search algorithm, and their applications.

Researchers are invited to submit innovative works on the theory and implementation of this family of techniques, in order to provide an up-to-date overview on the field.



Keywords

Evolutionary Computations
Evolutionary Strategies/Programming
Genetic Algorithms/Programming
Artificial Neural Network
Hybrid algorithms
Flower Pollination Algorithm
Cat Swarm Optimization Algorithm
Applications of the bio-inspired algorithms
Particle swarm optimization
Firefly algorithm
Fireworks algorithm
Bees algorithm
Evolutionary algorithms
Neural networks
Deep learning
Soft computing methods
Nature-inspired heuristics
Fuzzy optimization
Constrained optimization


Published Papers


  • Open Access

    ARTICLE

    Archery Algorithm: A Novel Stochastic Optimization Algorithm for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi, Mohammad Dehghani, Pavel Trojovský, Štěpán Hubálovský, Victor Leiva, Gaurav Dhiman
    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 399-416, 2022, DOI:10.32604/cmc.2022.024736
    (This article belongs to this Special Issue: Bio-Inspired Computational Intelligence and Optimization Techniques for Real-World Engineering Applications)
    Abstract Finding a suitable solution to an optimization problem designed in science is a major challenge. Therefore, these must be addressed utilizing proper approaches. Based on a random search space, optimization algorithms can find acceptable solutions to problems. Archery Algorithm (AA) is a new stochastic approach for addressing optimization problems that is discussed in this study. The fundamental idea of developing the suggested AA is to imitate the archer's shooting behavior toward the target panel. The proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the… More >

  • Open Access

    ARTICLE

    Fuzzy System Design Using Current Amplifier for 20 nm CMOS Technology

    Shruti Jain, Cherry Bhargava, Vijayakumar Varadarajan, Ketan Kotecha
    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1815-1829, 2022, DOI:10.32604/cmc.2022.024004
    (This article belongs to this Special Issue: Bio-Inspired Computational Intelligence and Optimization Techniques for Real-World Engineering Applications)
    Abstract In the recent decade, different researchers have performed hardware implementation for different applications covering various areas of experts. In this research paper, a novel analog design and implementation of different steps of fuzzy systems with current differencing buffered amplifier (CDBA) are proposed with a compact structure that can be used in many signal processing applications. The proposed circuits are capable of wide input current range, simple structure, and are highly linear. Different electrical parameters were compared for the proposed fuzzy system when using different membership functions. The novelty of this paper lies in the electronic implementation of different steps for… More >

  • Open Access

    ARTICLE

    Examination of Pine Wilt Epidemic Model through Efficient Algorithm

    Ali Raza, Emad E. Mahmoud, A. M. Al-Bugami, Dumitru Baleanu, Muhammad Rafiq, Muhammad Mohsin, Muneerah Al Nuwairan
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5293-5310, 2022, DOI:10.32604/cmc.2022.024535
    (This article belongs to this Special Issue: Bio-Inspired Computational Intelligence and Optimization Techniques for Real-World Engineering Applications)
    Abstract Pine wilt is a dramatic disease that kills infected trees within a few weeks to a few months. The cause is the pathogen Pinewood Nematode. Most plant-parasitic nematodes are attached to plant roots, but pinewood nematodes are found in the tops of trees. Nematodes kill the tree by feeding the cells around the resin ducts. The modeling of a pine wilt disease is based on six compartments, including three for plants (susceptible trees, exposed trees, and infected trees) and the other for the beetles (susceptible beetles, exposed beetles, and infected beetles). The deterministic modeling, along with subpopulations, is based on… More >

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