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  • Open Access

    ARTICLE

    Neutrosophic Mathematical Programming for Optimization of Multi-Objective Sustainable Biomass Supply Chain Network Design

    Mohammad Fallah*, Hamed Nozari

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 927-951, 2021, DOI:10.32604/cmes.2021.017511 - 08 October 2021

    Abstract In this paper, a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method. In this method, for each objective function of the problem, three functions of truth membership, non-determination and falsehood are considered. Neutrosophic programming method in this paper simultaneously seeks to optimize the total costs of the supply chain network, the amount of greenhouse gas emissions, the number of potential people hired and the time of product transfer along the supply chain network. To achieve the stated objective functions, strategic decisions such as locating potential facilities and tactical decisions More >

  • Open Access

    ARTICLE

    An Improved Method Based on TODIM and TOPSIS for Multi-Attribute Decision-Making with Multi-Valued Neutrosophic Sets

    Dongsheng Xu, Lijuan Peng*

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 907-926, 2021, DOI:10.32604/cmes.2021.016720 - 08 October 2021

    Abstract Due to the complexity of decision-making problems and the subjectivity of decision-makers in practical application, it is necessary to adopt different forms of information expression according to the actual situation of specific decision-making problems and choose the best method to solve them. Multi-valued neutrosophic set, as an extension of neutrosophic set, can more effectively and accurately describe incomplete, uncertain or inconsistent information. TODIM and TOPSIS methods are two commonly used multi-attribute decision-making methods, each of which has its advantages and disadvantages. This paper proposes a new method based on TODIM and TOPSIS to solve multi-attribute More >

  • Open Access

    ARTICLE

    Decision Making Algorithmic Approaches Based on Parameterization of Neutrosophic Set under Hypersoft Set Environment with Fuzzy, Intuitionistic Fuzzy and Neutrosophic Settings

    Atiqe Ur Rahman1,*, Muhammad Saeed1, Sultan S. Alodhaibi2, Hamiden Abd El-Wahed Khalifa3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 743-777, 2021, DOI:10.32604/cmes.2021.016736 - 22 July 2021

    Abstract Hypersoft set is an extension of soft set as it further partitions each attribute into its corresponding attribute-valued set. This structure is more flexible and useful as it addresses the limitation of soft set for dealing with the scenarios having disjoint attribute-valued sets corresponding to distinct attributes. The main purpose of this study is to make the existing literature regarding neutrosophic parameterized soft set in line with the need of multi-attribute approximate function. Firstly, we conceptualize the neutrosophic parameterized hypersoft sets under the settings of fuzzy set, intuitionistic fuzzy set and neutrosophic set along with More >

  • Open Access

    ARTICLE

    A Direct Data-Cluster Analysis Method Based on Neutrosophic Set Implication

    Sudan Jha1, Gyanendra Prasad Joshi2, Lewis Nkenyereya3, Dae Wan Kim4, *, Florentin Smarandache5

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1203-1220, 2020, DOI:10.32604/cmc.2020.011618 - 20 August 2020

    Abstract Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University More >

  • Open Access

    ARTICLE

    PID Tuning Method Using Single-Valued Neutrosophic Cosine Measure and Genetic Algorithm

    Jun Ye

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 15-23, 2019, DOI:10.31209/2018.100000067

    Abstract Because existing proportional-integral-derivative (PID) tuning method using similarity measures of single-valued neutrosophic sets (SVNSs) and an increasing step algorithm shows its complexity and inconvenience, this paper proposes a PID tuning method using a cosine similarity measure of SVNSs and genetic algorithm (GA) to improve the existing PID tuning method. In the tuning process, the step response characteristic values (rising time, settling time, overshoot ratio, undershoot ratio, peak time, and steady-state error) of the control system are converted into the single-valued neutrosophic set (SVNS) by the neutrosophic membership functions (Neutrosophication). Then the values of three appropriate More >

  • Open Access

    ARTICLE

    Fault Diagnoses of Hydraulic Turbine Using the Dimension Root Similarity Measure of Single-valued Neutrosophic Sets

    Jun Ye

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 1-8, 2018, DOI:10.1080/10798587.2016.1261955

    Abstract This paper proposes a dimension root distance and its similarity measure of single-valued neutrosophic sets (SVNSs), and then develops the fault diagnosis method of hydraulic turbine by using the dimension root similarity measure of SVNSs. By the similarity measures between the fault diagnosis patterns and a testing sample with single-valued neutrosophic information and the relation indices, we can determine the main fault type and the ranking order of various vibration faults for predicting some possible fault trend. Then, the comparison of the fault diagnoses of hydraulic turbine based of the proposed dimension root similarity measure More >

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