The Experts below are selected from a list of 1815 Experts worldwide ranked by ideXlab platform

Florentin Smarandache - One of the best experts on this subject based on the ideXlab platform.

Xiaohong Chen - One of the best experts on this subject based on the ideXlab platform.

  • Multi-valued Neutrosophic Sets and Power Aggregation Operators with Their Applications in Multi-criteria Group Decision-making Problems
    2019
    Co-Authors: Juanjuan Peng, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    In recent years, hesitant fuzzy Sets (HFSs) and Neutrosophic Sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued Neutrosophic Sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy membership and falsity-membership degree have a set of crisp values between zero and one, respectively. Then theoperations of multi-valued Neutrosophic numbers (MVNNs) based on Einstein operations are defined, and a comparison method for MVNNs is developed depending on the related research of HFSs and Atanassov’s intuitionistic fuzzy Sets (IFSs). Furthermore, the multi-valued Neutrosophic power weighted average (MVNPWA) operator and the multi-valued Neutrosophic power weighted geometric (MVNPWG) operator are proposed and the desirable properties of two operators are also discussed. Finally, an approach for solving MCGDM problems is explored by applying the power aggregation operators, and an example is provided to illustrate the application of the proposed method, together with a comparison analysis

  • multi criteria decision making method based on a cross entropy with interval Neutrosophic Sets
    International Journal of Systems Science, 2016
    Co-Authors: Zhangpeng Tian, Hongyu Zhang, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    In this paper, two optimisation models are established to determine the criterion weights in multi-criteria decision-making situations where knowledge regarding the weight information is incomplete and the criterion values are interval Neutrosophic numbers. The proposed approach combines interval Neutrosophic Sets and TOPSIS, and the closeness coefficients are expressed as interval numbers. Furthermore, the relative likelihood-based comparison relations are constructed to determine the ranking of alternatives. A fuzzy cross-entropy approach is proposed to calculate the discrimination measure between alternatives and the absolute ideal solutions, after a transformation operator has been developed to convert interval Neutrosophic numbers into simplified Neutrosophic numbers. Finally, an illustrative example is provided, and a comparative analysis is conducted between the approach developed in this paper and other existing methods, to verify the feasibility and effectiveness of the proposed approach.

  • simplified Neutrosophic Sets and their applications in multi criteria group decision making problems
    International Journal of Systems Science, 2016
    Co-Authors: Juanjuan Peng, Hongyu Zhang, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    As a variation of fuzzy Sets and intuitionistic fuzzy Sets, Neutrosophic Sets have been developed to represent uncertain, imprecise, incomplete and inconsistent information that exists in the real world. Simplified Neutrosophic Sets SNSs have been proposed for the main purpose of addressing issues with a set of specific numbers. However, there are certain problems regarding the existing operations of SNSs, as well as their aggregation operators and the comparison methods. Therefore, this paper defines the novel operations of simplified Neutrosophic numbers SNNs and develops a comparison method based on the related research of intuitionistic fuzzy numbers. On the basis of these operations and the comparison method, some SNN aggregation operators are proposed. Additionally, an approach for multi-criteria group decision-making MCGDM problems is explored by applying these aggregation operators. Finally, an example to illustrate the applicability of the proposed method is provided and a comparison with some other methods is made.

  • an outranking approach for multi criteria decision making problems with interval valued Neutrosophic Sets
    Neural Computing and Applications, 2016
    Co-Authors: Hongyu Zhang, Jianqiang Wang, Xiaohong Chen
    Abstract:

    In this paper, a novel outranking approach for multi-criteria decision-making (MCDM) problems is proposed to address situations where there is a set of numbers in the real unit interval and not just a specific number with a Neutrosophic set. Firstly, the operations of interval Neutrosophic Sets and their related properties are introduced. Then some outranking relations for interval Neutrosophic numbers (INNs) are defined based on ELECTRE IV, and the properties of the outranking relations are further discussed in detail. Additionally, based on the outranking relations of INNs, a ranking approach is developed in order to solve MCDM problems. Finally, two practical examples are provided to illustrate the practicality and effectiveness of the proposed approach. Moreover, a comparison analysis based on the same examples is also conducted.

  • cross entropy and prioritized aggregation operator with simplified Neutrosophic Sets and their application in multi criteria decision making problems
    International Journal of Fuzzy Systems, 2016
    Co-Authors: Jianqiang Wang, Juanjuan Peng, Xiaohong Chen
    Abstract:

    Simplified Neutrosophic Sets (SNSs) can effectively solve the uncertainty problems, especially those involving the indeterminate and inconsistent information. Considering the advantages of SNSs, a new approach for multi-criteria decision-making (MCDM) problems is developed under the simplified Neutrosophic environment. First, the prioritized weighted average operator and prioritized weighted geometric operator for simplified Neutrosophic numbers (SNNs) are defined, and the related theorems are also proved. Then two novel effective cross-entropy measures for SNSs are proposed, and their properties are proved as well. Furthermore, based on the proposed prioritized aggregation operators and cross-entropy measures, the ranking methods for SNSs are established in order to solve MCDM problems. Finally, a practical MCDM example for coping with supplier selection of an automotive company is used to demonstrate the effectiveness of the developed methods. Moreover, the same example-based comparison analysis of between the proposed methods and other existing methods is carried out.

Jianqiang Wang - One of the best experts on this subject based on the ideXlab platform.

  • Multi-valued Neutrosophic Sets and Power Aggregation Operators with Their Applications in Multi-criteria Group Decision-making Problems
    2019
    Co-Authors: Juanjuan Peng, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    In recent years, hesitant fuzzy Sets (HFSs) and Neutrosophic Sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued Neutrosophic Sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy membership and falsity-membership degree have a set of crisp values between zero and one, respectively. Then theoperations of multi-valued Neutrosophic numbers (MVNNs) based on Einstein operations are defined, and a comparison method for MVNNs is developed depending on the related research of HFSs and Atanassov’s intuitionistic fuzzy Sets (IFSs). Furthermore, the multi-valued Neutrosophic power weighted average (MVNPWA) operator and the multi-valued Neutrosophic power weighted geometric (MVNPWG) operator are proposed and the desirable properties of two operators are also discussed. Finally, an approach for solving MCGDM problems is explored by applying the power aggregation operators, and an example is provided to illustrate the application of the proposed method, together with a comparison analysis

  • probability multi valued Neutrosophic Sets and its application in multi criteria group decision making problems
    Neural Computing and Applications, 2018
    Co-Authors: Honggang Peng, Hongyu Zhang, Jianqiang Wang
    Abstract:

    This paper introduces probability multi-valued Neutrosophic Sets (PMVNSs) based on multi-valued Neutrosophic Sets and probability distribution. PMVNS can serve as a reliable tool to depict uncertain, incomplete, inconsistent and hesitant decision-making information and reflect the distribution characteristics of all provided evaluation values. This paper focuses on developing an innovative method to address multi-criteria group decision-making (MCGDM) problems in which the weight information is completely unknown and the evaluation values taking the form of probability multi-valued Neutrosophic numbers (PMVNNs). First, the definition of PMVNSs is described. Second, an extended convex combination operation of PMVNNs is defined, and the probability multi-valued Neutrosophic number weighted average operator is proposed. Moreover, two cross-entropy measures for PMVNNs are presented, and a novel qualitative flexible multiple criteria method (QUALIFLEX) is developed. Subsequently, an innovative MCGDM approach is established by incorporating the proposed aggregation operator and the developed QUALIFLEX method. Finally, an illustrative example concerning logistics outsourcing is provided to demonstrate the proposed method, and its feasibility and validity are further verified by comparison with other existing methods.

  • probability multi valued Neutrosophic Sets and its application in multi criteria group decision making problems
    viXra, 2017
    Co-Authors: Honggang Peng, Hongyu Zhang, Jianqiang Wang
    Abstract:

    This paper introduces probability multi-valued Neutrosophic Sets (PMVNSs) based on multi-valued Neutrosophic Sets and probability distribution. PMVNS can serve as a reliable tool to depict uncertain, incomplete, inconsistent and hesitant decision-making information and reflect the distribution characteristics of all provided evaluation values.

  • solving solar wind power station location problem using an extended weighted aggregated sum product assessment waspas technique with interval Neutrosophic Sets
    Symmetry, 2017
    Co-Authors: Ruxin Nie, Jianqiang Wang, Hongyu Zhang
    Abstract:

    As one of the promising renewable energy resources, solar-wind energy has increasingly become a regional engine in leading the economy and raising competitiveness. Selecting a solar-wind power station location can contribute to efficient utilization of resource and instruct long-term development of socio-economy. Since the selection procedure consists of several location alternatives and many influential criteria factors, the selection can be recognized as a multiple criteria decision-making (MCDM) problem. To better express multiple uncertainty information during the selection procedure, fuzzy set theory is introduced to manage that issue. Interval Neutrosophic Sets (INSs), which are characterized by truth-membership, indeterminacy-membership and falsity-membership functions in the interval numbers (INs) form, are feasible in modeling more uncertainty of reality. In this paper, a newly extended weighted aggregated sum product assessment (WASPAS) technique, which involves novel three procedures, is utilized to handle MCDM issues under INSs environment. Some modifications are conducted in the extended method comparing with the classical WASPAS method. The most obvious improvement of the extended method relies on that it can generate more realistic criteria weight information by an objective and subjective integrated criteria weight determination method. A case study concerning solar-wind power station location selection is implemented to demonstrate the applicability and rationality of the proposed method in practice. Its validity and feasibility are further verified by a sensitivity analysis and a comparative analysis. These analyses effectively reveal that the extended WASPAS technique can well match the reality and appropriately handle the solar-wind power station location selection problem.

  • multi criteria decision making method based on a cross entropy with interval Neutrosophic Sets
    International Journal of Systems Science, 2016
    Co-Authors: Zhangpeng Tian, Hongyu Zhang, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    In this paper, two optimisation models are established to determine the criterion weights in multi-criteria decision-making situations where knowledge regarding the weight information is incomplete and the criterion values are interval Neutrosophic numbers. The proposed approach combines interval Neutrosophic Sets and TOPSIS, and the closeness coefficients are expressed as interval numbers. Furthermore, the relative likelihood-based comparison relations are constructed to determine the ranking of alternatives. A fuzzy cross-entropy approach is proposed to calculate the discrimination measure between alternatives and the absolute ideal solutions, after a transformation operator has been developed to convert interval Neutrosophic numbers into simplified Neutrosophic numbers. Finally, an illustrative example is provided, and a comparative analysis is conducted between the approach developed in this paper and other existing methods, to verify the feasibility and effectiveness of the proposed approach.

Juanjuan Peng - One of the best experts on this subject based on the ideXlab platform.

  • Multi-Valued Neutrosophic Distance-Based QUALIFLEX Method for Treatment Selection
    2019
    Co-Authors: Juanjuan Peng, Chao Tian
    Abstract:

    Multi-valued Neutrosophic Sets (MVNSs) consider the truth-membership, indeterminacy-membership, and falsity-membership simultaneously, which can more accurately express the preference information of decision-makers

  • Multi-valued Neutrosophic Sets and Power Aggregation Operators with Their Applications in Multi-criteria Group Decision-making Problems
    2019
    Co-Authors: Juanjuan Peng, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    In recent years, hesitant fuzzy Sets (HFSs) and Neutrosophic Sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued Neutrosophic Sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy membership and falsity-membership degree have a set of crisp values between zero and one, respectively. Then theoperations of multi-valued Neutrosophic numbers (MVNNs) based on Einstein operations are defined, and a comparison method for MVNNs is developed depending on the related research of HFSs and Atanassov’s intuitionistic fuzzy Sets (IFSs). Furthermore, the multi-valued Neutrosophic power weighted average (MVNPWA) operator and the multi-valued Neutrosophic power weighted geometric (MVNPWG) operator are proposed and the desirable properties of two operators are also discussed. Finally, an approach for solving MCGDM problems is explored by applying the power aggregation operators, and an example is provided to illustrate the application of the proposed method, together with a comparison analysis

  • simplified Neutrosophic Sets and their applications in multi criteria group decision making problems
    International Journal of Systems Science, 2016
    Co-Authors: Juanjuan Peng, Hongyu Zhang, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    As a variation of fuzzy Sets and intuitionistic fuzzy Sets, Neutrosophic Sets have been developed to represent uncertain, imprecise, incomplete and inconsistent information that exists in the real world. Simplified Neutrosophic Sets SNSs have been proposed for the main purpose of addressing issues with a set of specific numbers. However, there are certain problems regarding the existing operations of SNSs, as well as their aggregation operators and the comparison methods. Therefore, this paper defines the novel operations of simplified Neutrosophic numbers SNNs and develops a comparison method based on the related research of intuitionistic fuzzy numbers. On the basis of these operations and the comparison method, some SNN aggregation operators are proposed. Additionally, an approach for multi-criteria group decision-making MCGDM problems is explored by applying these aggregation operators. Finally, an example to illustrate the applicability of the proposed method is provided and a comparison with some other methods is made.

  • cross entropy and prioritized aggregation operator with simplified Neutrosophic Sets and their application in multi criteria decision making problems
    International Journal of Fuzzy Systems, 2016
    Co-Authors: Jianqiang Wang, Juanjuan Peng, Xiaohong Chen
    Abstract:

    Simplified Neutrosophic Sets (SNSs) can effectively solve the uncertainty problems, especially those involving the indeterminate and inconsistent information. Considering the advantages of SNSs, a new approach for multi-criteria decision-making (MCDM) problems is developed under the simplified Neutrosophic environment. First, the prioritized weighted average operator and prioritized weighted geometric operator for simplified Neutrosophic numbers (SNNs) are defined, and the related theorems are also proved. Then two novel effective cross-entropy measures for SNSs are proposed, and their properties are proved as well. Furthermore, based on the proposed prioritized aggregation operators and cross-entropy measures, the ranking methods for SNSs are established in order to solve MCDM problems. Finally, a practical MCDM example for coping with supplier selection of an automotive company is used to demonstrate the effectiveness of the developed methods. Moreover, the same example-based comparison analysis of between the proposed methods and other existing methods is carried out.

  • multi valued Neutrosophic Sets and power aggregation operators with their applications in multi criteria group decision making problems
    viXra, 2015
    Co-Authors: Juanjuan Peng, Jianqiang Wang, Jing Wang, Xiaohong Chen
    Abstract:

    In recent years, hesitant fuzzy Sets (HFSs) and Neutrosophic Sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued Neutrosophic Sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy membership and falsity-membership degree have a set of crisp values between zero and one, espectively.

Aboul Ella Hassenian - One of the best experts on this subject based on the ideXlab platform.

  • ct liver tumor segmentation hybrid approach using Neutrosophic Sets fast fuzzy c means and adaptive watershed algorithm
    Artificial Intelligence in Medicine, 2019
    Co-Authors: Ahmed M Anter, Aboul Ella Hassenian
    Abstract:

    Liver tumor segmentation from computed tomography (CT) images is a critical and challenging task. Due to the fuzziness in the liver pixel range, the neighboring organs of the liver with the same intensity, high noise and large variance of tumors. The segmentation process is necessary for the detection, identification, and measurement of objects in CT images. We perform an extensive review of the CT liver segmentation literature. Furthermore, in this paper, an improved segmentation approach based on watershed algorithm, Neutrosophic Sets (NS), and fast fuzzy c-mean clustering algorithm (FFCM) for CT liver tumor segmentation is proposed. To increase the contrast of the liver CT images, the intensity values are adjusted and high frequencies are removed using histogram equalization and median filter approach. It is followed by transforming the CT image to NS domain, which is described using three subSets (percentage of truth T, the percentage of indeterminacy I, and percentage of falsity F). The obtained NS image is enhanced by adaptive threshold and morphological operators to focus on liver parenchyma. The enhanced NS image passed to a watershed algorithm for post-segmentation process and liver parenchyma is extracted using the connected component algorithm. Finally, the liver tumors are segmented from the segmented liver using fast fuzzy c-mean (FFCM). A quantitative analysis is carried out to evaluate segmentation results using six different indices. The results show that the overall accuracy offered by the employed Neutrosophic Sets is accurate, less time consuming, less sensitive to noise and performs better on non-uniform CT images.

  • computational intelligence optimization approach based on particle swarm optimizer and Neutrosophic set for abdominal ct liver tumor segmentation
    Journal of Computational Science, 2018
    Co-Authors: Ahmed M Anter, Aboul Ella Hassenian
    Abstract:

    Abstract In this paper, an improved segmentation approach for abdominal CT liver tumor based on Neutrosophic Sets (NS), particle swarm optimization (PSO), and fast fuzzy C-mean algorithm (FFCM) is proposed. To increase the contrast of the CT liver image, the intensity values and high frequencies of the original images were removed and adjusted firstly using median filter approach. It is followed by transforming the abdominal CT image to NS domain, which is described using three subSets namely; percentage of truth T, percentage of falsity F, and percentage of indeterminacy I. The entropy is used to evaluate indeterminacy in NS domain. Then, the NS image is passed to optimized FFCM using PSO to enhance, optimize clusters results and segment liver from abdominal CT. Then, these segmented livers passed to PSOFCM technique to cluster and segment tumors. The experimental results obtained based on the analysis of variance (ANOVA) technique, Jaccard Index and Dice Coefficient measures show that, the overall accuracy offered by Neutrosophic Sets is accurate, less time consuming and less sensitive to noise and performs well on non-uniform CT images.