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  • Open Access


    Quantum Fuzzy Regression Model for Uncertain Environment

    Tiansu Chen1,2, Shi bin Zhang1,2, Qirun Wang3, Yan Chang1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2759-2773, 2023, DOI:10.32604/cmc.2023.033284

    Abstract In the era of big data, traditional regression models cannot deal with uncertain big data efficiently and accurately. In order to make up for this deficiency, this paper proposes a quantum fuzzy regression model, which uses fuzzy theory to describe the uncertainty in big data sets and uses quantum computing to exponentially improve the efficiency of data set preprocessing and parameter estimation. In this paper, data envelopment analysis (DEA) is used to calculate the degree of importance of each data point. Meanwhile, Harrow, Hassidim and Lloyd (HHL) algorithm and quantum swap circuits are used to improve the efficiency of high-dimensional… More >

  • Open Access


    Mathematical Modeling and Evaluation of Reliability Parameters Based on Survival Possibilities under Uncertain Environment

    Alhanouf Alburaikan1, Hamiden Abd El-Wahed Khalifa1,2, Pavan Kumar3,*, Seyedali Mirjalili4,6, Ibrahim Mekawy5

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1943-1956, 2023, DOI:10.32604/cmes.2022.021815

    Abstract In this article, mathematical modeling for the evaluation of reliability is studied using two methods. One of the methods, is developed based on possibility theory. The performance of the reliability of the system is of prime concern. In view of this, the outcomes for the failure are required to evaluate with utmost care. In possibility theory, the reliability information data determined from decision-making experts are subjective. The same method is also related to the survival possibilities as against the survival probabilities. The other method is the one that is developed using the concept of approximation of closed interval including the… More >

  • Open Access


    Network Analysis for Projects with High Risk Levels in Uncertain Environments

    Mohamed Abdel-Basset1, Asmaa Atef1, Mohamed Abouhawwash2,3, Yunyoung Nam4,*, Nabil M. AbdelAziz1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1281-1296, 2022, DOI:10.32604/cmc.2022.018947

    Abstract The critical path method is one of the oldest and most important techniques used for planning and scheduling projects. The main objective of project management science is to determine the critical path through a network representation of projects. The critical path through a network can be determined by many algorithms and is useful for managing, monitoring, and controlling the time and cost of an entire project. The essential problem in this case is that activity durations are uncertain; time presents considerable uncertainty because the time of an activity is not always easily or accurately estimated. This issue increases the need… More >

  • Open Access


    Using genetic algorithms to find a globally optimal solution in uncertain environments with multiple sources of additive and multiplicative noise

    Takéhiko Nakama1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.4, pp. 233-242, 2009, DOI:10.3970/icces.2009.009.233

    Abstract Random noise perturbs objective functions in a variety of practical optimization problems, and genetic algorithms (GAs) have been widely proposed as an effective optimization tool for dealing with noisy objective functions. In this paper, we investigate GAs applied to objective functions that are perturbed by multiple sources of additive and multiplicative noise that each take on finitely many values. We reveal the convergence properties of GAs by constructing and analyzing a Markov chain that explicitly models the evolution of the algorithms in noisy environments. Our analysis shows that this Markov chain is indecomposable; it has only one positive recurrent communication… More >

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