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Advanced Implications of Fuzzy Logic Evolutionary Computation

Submission Deadline: 10 July 2023 (closed)

Guest Editors

Prof. Waqas Nazeer, Government College University, Pakistan.
Prof. Ebenezer Bonyah, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Ghana.
Prof. Merve Ilkhan Kara, Düzce University, Turkey.


Logical thinking is a way of handling variables which enables the interpretation of several potential conditional probabilities throughout an independent condition. Inductive reasoning provides an effort to resolve difficulties using an unstructured, imperfect range of facts and procedures which enables the production of a variety of exact judgments. The majority of conflicting schedules are complicated knapsack problems. Because of this, many techniques concentrate on optimising in accordance with a specific factor. Integrating multiple definitions generates new issues and system generates. In this research, they provide a proportional strategy to the alternative work timetabling problem predicated on the fusion of inductive inference and optimization computation. Utilising both the responsive and understanding encoding features of optimization computation, the proposed methodology. There is significant focus in incorporating these two methodologies for multi-objective management. The goal is to reduce the aggregate project duration (effort), the aggregate burden of the machineries, and the demand of the equipment that is most heavily populated.


Latest surveys are indeed the conceptual and practical advancements in boolean controller and genetic algorithms theories. They examine the history and key turning points of inductive inference (in the broad sense), along with the more recent growth of computational intelligence, while offering a perspective of implementations, ranging through the most theoretical towards the most realistic. It is generally acknowledged as proposed algorithm, parametric interpretation, cognitive technology, and simulated annealing are the key elements of soft data processing. These key dimensions are complementing rather than antagonistic and have many points of convergence. Simulations that integrate the received notification and take advantage of its greatest qualities can indeed be created. Variety of applications from the strictly simulated result, those that introduce additional concepts in conceptual arithmetic or reasoning, to pragmatic industrial applications like automation and industrialization, computer sciences, nuclear or clinical architecture, desire forecasting, knowledge discovery, etc.


When using incremental factors that have an effect, the additional source of information is predominantly a consequence of the computation total number of iterations in addition to the evaluating stored procedure complexities. The temporal sophistication of the approach can also be influenced by the different algorithmic operations along with the challenge that must be addressed. The additional source of information of approximating iterative methods is often quadratic, though. Therefore, while considering strategies in this area, the time complexity is unimportant. Since the fundamental formulation of a linguistic variable, other similar conceptions of the idea were put forth, examined, as well as utilised. Despite the possibility that the prior major components may now be replaced by everyone, mathematical modelling somehow doesn't include this category.

Fuzzy logic evolutionary computation components: theoretical and practical consequences is the theme of the article collection we are inviting submissions and article proposals for.


Research papers that consider the following questions and themes are welcomed:
1.Technologies for particle swarm optimization using fuzzy logic and soft computing.
2.Adaptive optimization and fuzzy level of expertise acquisition.
3.Economic implications of fusing machine learning, evolutionary algorithms, and optimization computation.
4.A fusion strategy incorporating neural networks, simulated annealing, and probabilistic reasoning.
5.Modelling and management of integrated applications using clever soft calculations.
6.State of the art innovations in key component of computational intelligence.
7.Intelligent computing for prediction of time series.
8.Evolutionary programming with adaptable mutation and crossing probability utilising clustering.
9.Innovative technologies for designing imprecise security controls.
10.Employing genetic, neuronal, and ambiguous technologies together in machine learning.
11.Benefits of metaheuristic optimization methods in multiobjective problems.

Published Papers

  • Open Access


    The Entity Relationship Extraction Method Using Improved RoBERTa and Multi-Task Learning

    Chaoyu Fan
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1719-1738, 2023, DOI:10.32604/cmc.2023.041395
    (This article belongs to this Special Issue: Advanced Implications of Fuzzy Logic Evolutionary Computation)
    Abstract There is a growing amount of data uploaded to the internet every day and it is important to understand the volume of those data to find a better scheme to process them. However, the volume of internet data is beyond the processing capabilities of the current internet infrastructure. Therefore, engineering works using technology to organize and analyze information and extract useful information are interesting in both industry and academia. The goal of this paper is to explore the entity relationship based on deep learning, introduce semantic knowledge by using the prepared language model, develop an advanced entity relationship information extraction… More >

  • Open Access


    A Nonstandard Computational Investigation of SEIR Model with Fuzzy Transmission, Recovery and Death Rates

    Ahmed H. Msmali, Fazal Dayan, Muhammad Rafiq, Nauman Ahmed, Abdullah Ali H. Ahmadini, Hassan A. Hamali
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2251-2269, 2023, DOI:10.32604/cmc.2023.040266
    (This article belongs to this Special Issue: Advanced Implications of Fuzzy Logic Evolutionary Computation)
    Abstract In this article, a Susceptible-Exposed-Infectious-Recovered (SEIR) epidemic model is considered. The equilibrium analysis and reproduction number are studied. The conventional models have made assumptions of homogeneity in disease transmission that contradict the actual reality. However, it is crucial to consider the heterogeneity of the transmission rate when modeling disease dynamics. Describing the heterogeneity of disease transmission mathematically can be achieved by incorporating fuzzy theory. A numerical scheme nonstandard, finite difference (NSFD) approach is developed for the studied model and the results of numerical simulations are presented. Simulations of the constructed scheme are presented. The positivity, convergence and consistency of the… More >

  • Open Access


    Digital Image Encryption Algorithm Based on Double Chaotic Map and LSTM

    Luoyin Feng, Jize Du, Chong Fu
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1645-1662, 2023, DOI:10.32604/cmc.2023.042630
    (This article belongs to this Special Issue: Advanced Implications of Fuzzy Logic Evolutionary Computation)
    Abstract In the era of network communication, digital image encryption (DIE) technology is critical to ensure the security of image data. However, there has been limited research on combining deep learning neural networks with chaotic mapping for the encryption of digital images. So, this paper addresses this gap by studying the generation of pseudo-random sequences (PRS) chaotic signals using dual logistic chaotic maps. These signals are then predicted using long and short-term memory (LSTM) networks, resulting in the reconstruction of a new chaotic signal. During the research process, it was discovered that there are numerous training parameters associated with the LSTM… More >

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