Generalized Ordered Propositions Fusion Based on Belief Entropy

A set of ordered propositions describe the different intensities of a characteristic of an object, the intensities increase or decrease gradually. A basic support function is a set of truth-values of ordered propositions, it includes the determinate part and indeterminate part. The indeterminate part of a basic support function indicates uncertainty about all ordered propositions. In this paper, we propose generalized ordered propositions by extending the basic support function for power set of ordered propositions. We also present the entropy which is a measure of uncertainty of a basic support function based on belief entropy. The fusion method of generalized ordered proposition also be presented. The generalized ordered propositions will be degenerated as the classical ordered propositions in that when the truth-values of non-single subsets of ordered propositions are zero. Some numerical examples are used to illustrate the efficiency of generalized ordered propositions and their fusion.

[1]  Jérémy Robert,et al.  Minimum Cycle Time Analysis of Ethernet-Based Real-Time Protocols , 2014, Int. J. Comput. Commun. Control.

[2]  Sankaran Mahadevan,et al.  Reliability analysis with linguistic data: An evidential network approach , 2017, Reliab. Eng. Syst. Saf..

[3]  Sankaran Mahadevan,et al.  Relative contributions of aleatory and epistemic uncertainty sources in time series prediction , 2016 .

[4]  Hanqing Zheng,et al.  Evidence conflict measure based on OWA operator in open world , 2017, PloS one.

[5]  Xinyang Deng,et al.  A Novel Network Security Risk Assessment Approach by Combining Subjective and Objective Weights under Uncertainty , 2018 .

[6]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[7]  Yafei Song,et al.  Credibility decay model in temporal evidence combination , 2015, Inf. Process. Lett..

[8]  Bogdana Stanojević,et al.  On the ratio of fuzzy numbers – exact membership function computation and applications to decision making , 2015 .

[9]  Edmundas Kazimieras Zavadskas,et al.  Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection , 2016, Int. J. Comput. Commun. Control.

[10]  Yong Deng,et al.  Failure mode and effects analysis based on D numbers and TOPSIS , 2016, Qual. Reliab. Eng. Int..

[11]  Qi Zhang,et al.  Measure the structure similarity of nodes in complex networks based on relative entropy , 2018 .

[12]  Yong Deng,et al.  Dependent Evidence Combination Based on Shearman Coefficient and Pearson Coefficient , 2018, IEEE Access.

[13]  Yong Deng,et al.  Evaluation method based on fuzzy relations between Dempster–Shafer belief structure , 2018, Int. J. Intell. Syst..

[14]  Ronald R. Yager,et al.  Soft likelihood functions in combining evidence , 2017, Inf. Fusion.

[15]  Fuyuan Xiao,et al.  A Novel Evidence Theory and Fuzzy Preference Approach-Based Multi-Sensor Data Fusion Technique for Fault Diagnosis , 2017, Sensors.

[16]  Kerstin Thurow,et al.  A Context-Aware mHealth System for Online Physiological Monitoring in Remote Healthcare , 2015, Int. J. Comput. Commun. Control.

[17]  Edmundas Kazimieras Zavadskas,et al.  A Novel Approach for Evaluation of Projects Using an Interval-Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects , 2018, Symmetry.

[18]  Dayou Liu,et al.  Ordered proposition fusion based on consistency and uncertainty measurements , 2016, Science China Information Sciences.

[19]  Ronald R. Yager,et al.  On Viewing Fuzzy Measures as Fuzzy Subsets , 2016, IEEE Transactions on Fuzzy Systems.

[20]  Joaquín Abellán,et al.  Analyzing properties of Deng entropy in the theory of evidence , 2017 .

[21]  Christian Tahon,et al.  Integration of Traffic Management and Traveller Information Systems: Basic Principles and Case Study in Intermodal Transport System Management , 2008, Int. J. Comput. Commun. Control.

[22]  Reza Farzipoor Saen,et al.  A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context , 2015, Comput. Oper. Res..

[23]  Chun-Hsiang Chuang,et al.  Exploring resting-state EEG complexity before migraine attacks , 2018, Cephalalgia : an international journal of headache.

[24]  Sankaran Mahadevan,et al.  Resilience-based network design under uncertainty , 2018, Reliab. Eng. Syst. Saf..

[25]  Yong Deng,et al.  Generating Z‐number based on OWA weights using maximum entropy , 2018, Int. J. Intell. Syst..

[26]  Chunhe Xie,et al.  Failure mode and effects analysis based on a novel fuzzy evidential method , 2017, Appl. Soft Comput..

[27]  Xinyang Deng,et al.  Analyzing the monotonicity of belief interval based uncertainty measures in belief function theory , 2017, Int. J. Intell. Syst..

[28]  Lotfi A. Zadeh,et al.  A Note on Z-numbers , 2011, Inf. Sci..

[29]  Ronald R. Yager Uncertainty modeling using fuzzy measures , 2016, Knowl. Based Syst..

[30]  Fuyuan Xiao,et al.  A Hybrid Fuzzy Soft Sets Decision Making Method in Medical Diagnosis , 2018, IEEE Access.

[31]  Sankaran Mahadevan,et al.  Role of calibration, validation, and relevance in multi-level uncertainty integration , 2016, Reliab. Eng. Syst. Saf..

[32]  Fuyuan Xiao,et al.  An Improved Method for Combining Conflicting Evidences Based on the Similarity Measure and Belief Function Entropy , 2018, Int. J. Fuzzy Syst..

[33]  Fuyuan Xiao,et al.  A novel multi-criteria decision making method for assessing health-care waste treatment technologies based on D numbers , 2018, Eng. Appl. Artif. Intell..

[34]  Xinyang Deng,et al.  D-AHP method with different credibility of information , 2017, Soft Computing.

[35]  Farnaz Sabahi,et al.  A novel generalized belief structure comprising unprecisiated uncertainty applied to aphasia diagnosis , 2016, J. Biomed. Informatics.

[36]  Xiang Zhu,et al.  Trajectory Tracking Control for Seafloor Tracked Vehicle By Adaptive Neural-Fuzzy Inference System Algorithm , 2018, Int. J. Comput. Commun. Control.

[37]  Fei Liu,et al.  Consensus Problem of Second-order Dynamic Agents with Heterogeneous Input and Communication Delays , 2010, Int. J. Comput. Commun. Control.

[38]  An Zhang,et al.  Combination method of conflict evidences based on evidence similarity , 2010 .

[39]  Yong Deng,et al.  Measuring transferring similarity via local information , 2018 .

[40]  Omidvar Mohsen,et al.  An extended VIKOR method based on entropy measure for the failure modes risk assessment – A case study of the geothermal power plant (GPP) , 2017 .

[41]  Yong Deng,et al.  A hybrid intelligent model for assessment of critical success factors in high-risk emergency system , 2018, Journal of Ambient Intelligence and Humanized Computing.

[42]  Hua Zhang,et al.  A concurrent reliability optimization procedure in the earlier design phases of complex engineering systems under epistemic uncertainties , 2016 .

[43]  Yong Deng,et al.  A New MADA Methodology Based on D Numbers , 2018, Int. J. Fuzzy Syst..

[44]  Yi Peng,et al.  A Similarity Measure-based Optimization Model for Group Decision Making with Multiplicative and Fuzzy Preference Relations , 2016, Int. J. Comput. Commun. Control.

[45]  Edmundas Kazimieras Zavadskas,et al.  A Hybrid MCDM Technique for Risk Management in Construction Projects , 2018, Symmetry.

[46]  Yong Deng,et al.  Dependence assessment in human reliability analysis based on evidence credibility decay model and IOWA operator , 2018 .

[47]  Haiqing Li,et al.  Multidisciplinary reliability design optimization using an enhanced saddlepoint approximation in the framework of sequential optimization and reliability analysis , 2016 .

[48]  Yong Deng,et al.  An enhanced fuzzy evidential DEMATEL method with its application to identify critical success factors , 2018, Soft Computing.

[49]  Xinyang Deng,et al.  A Modified Method for Evaluating Sustainable Transport Solutions Based on AHP and Dempster–Shafer Evidence Theory , 2018 .

[50]  Yong Deng,et al.  A novel method for forecasting time series based on fuzzy logic and visibility graph , 2017, Advances in Data Analysis and Classification.

[51]  Zehong Cao,et al.  Shared Nearest-Neighbor Quantum Game-Based Attribute Reduction With Hierarchical Coevolutionary Spark and Its Application in Consistent Segmentation of Neonatal Cerebral Cortical Surfaces , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[52]  Liu Da A CONVEX EVIDENCE THEORY MODEL , 2000 .

[53]  Abraham Kandel,et al.  Axiomatic Theory of Complex Fuzzy Logic and Complex Fuzzy Classes , 2011, Int. J. Comput. Commun. Control.

[54]  Tetsuya Murai,et al.  Multiple-attribute decision making under uncertainty: the evidential reasoning approach revisited , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[55]  Yong Deng,et al.  Evidential Supplier Selection Based on DEMATEL and Game Theory , 2018, Int. J. Fuzzy Syst..

[56]  Nikhil R. Pal,et al.  Weighted Fuzzy Dempster–Shafer Framework for Multimodal Information Integration , 2018, IEEE Transactions on Fuzzy Systems.

[57]  Florin Gheorghe Filip,et al.  Fuzzy Logic Is Not Fuzzy: World-renowned Computer Scientist Lotfi A. Zadeh , 2017, Int. J. Comput. Commun. Control.

[58]  Xiaojing Song,et al.  The optimal design of industrial alarm systems based on evidence theory , 2016 .

[59]  Miguel A. Martínez-del-Amor,et al.  P-Lingua 2.0: A software framework for cell-like P systems , 2009, Int. J. Comput. Commun. Control.

[60]  Wei Deng,et al.  Evidential Model Validation under Epistemic Uncertainty , 2018 .

[61]  Yong Deng,et al.  Toward uncertainty of weighted networks: An entropy-based model , 2018, Physica A: Statistical Mechanics and its Applications.

[62]  Bingyi Kang,et al.  Stable strategies analysis based on the utility of Z-number in the evolutionary games , 2018, Appl. Math. Comput..

[63]  Jurgita Antucheviciene,et al.  A Hybrid Model Based on Fuzzy AHP and Fuzzy WASPAS for Construction Site Selection , 2015, Int. J. Comput. Commun. Control.

[64]  Weiping Ding,et al.  A Layered-Coevolution-Based Attribute-Boosted Reduction Using Adaptive Quantum-Behavior PSO and Its Consistent Segmentation for Neonates Brain Tissue , 2018, IEEE Transactions on Fuzzy Systems.

[65]  Zehong Cao,et al.  Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation , 2018, IEEE Transactions on Fuzzy Systems.

[66]  Yong Deng,et al.  Identification of influential nodes in network of networks , 2015, ArXiv.

[67]  Fuyuan Xiao,et al.  An Intelligent Complex Event Processing with Numbers under Fuzzy Environment , 2016 .

[68]  Xiaoyan Su,et al.  Research on fault diagnosis methods for the reactor coolant system of nuclear power plant based on D-S evidence theory , 2018 .

[69]  Liguo Fei,et al.  A new vector valued similarity measure for intuitionistic fuzzy sets based on OWA operators , 2019 .

[70]  Weiping Ding,et al.  Deep Neuro-Cognitive Co-Evolution for Fuzzy Attribute Reduction by Quantum Leaping PSO With Nearest-Neighbor Memeplexes , 2019, IEEE Transactions on Cybernetics.

[71]  Yu Luo,et al.  Determining Basic Probability Assignment Based on the Improved Similarity Measures of Generalized Fuzzy Numbers , 2015, Int. J. Comput. Commun. Control.

[72]  Chun-Hsiang Chuang,et al.  Forehead EEG in Support of Future Feasible Personal Healthcare Solutions: Sleep Management, Headache Prevention, and Depression Treatment , 2017, IEEE Access.

[73]  Yong Deng,et al.  Identifying influential nodes in complex networks: A node information dimension approach. , 2018, Chaos.

[74]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[75]  Yong Hu,et al.  A DEMATEL-based completion method for incomplete pairwise comparison matrix in AHP , 2016, Ann. Oper. Res..

[76]  Fuyuan Xiao,et al.  Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy , 2019, Inf. Fusion.

[77]  Jian-Bo Yang,et al.  A group evidential reasoning approach based on expert reliability , 2015, Eur. J. Oper. Res..

[78]  Chao Fu,et al.  Weighted cautious conjunctive rule for belief functions combination , 2015, Inf. Sci..

[79]  Sankaran Mahadevan,et al.  A Game Theoretic Approach to Network Reliability Assessment , 2017, IEEE Transactions on Reliability.

[80]  Wen Jiang,et al.  An Uncertainty Measure for Interval-valued Evidences , 2017, Int. J. Comput. Commun. Control.