Results 1 to 10 of about 67,501 (205)
Detection of Cause-Effect Relations Based on Information Granulation and Transfer Entropy [PDF]
Entropy, 2022 Causality inference is a process to infer Cause-Effect relations between variables in, typically, complex systems, and it is commonly used for root cause analysis in large-scale process industries.
Xiangxiang Zhang, Wenkai Hu, Fan Yang
doaj +2 more sources
Cloud Model-Based Adaptive Time-Series Information Granulation Algorithm and Its Similarity Measurement [PDF]
EntropyTo efficiently reduce the dimensionality of time series and enhance the efficiency of subsequent data-mining tasks, this study introduces cloud model theory to propose a novel information granulation method and its corresponding similarity measurement ...
Hailan Chen +3 more
doaj +2 more sources
Fuzzy granulation-based wind speed prediction with multi-objective optimization [PDF]
Scientific ReportsAccurate wind power forecasting is essential for enhancing the integration of renewable energy sources, thereby supporting global decarbonization initiatives.
Chi Zhang, Jianzhou Wang, Zhiwu Li
doaj +2 more sources
Optimal Granulation Selection Method Based on Multi-granulation Rough Intuitionistic Hesitant Fuzzy Sets [PDF]
Jisuanji kexue, 2021 In order to obtain the optimal granulations after reduction from the intuitionistic hesitant fuzzy decision information system with multiple attributes,this paper deals with the uncertain information in this system from the perspective of multi-gra ...
XUE Zhan-ao, SUN Bing-xin, HOU Hao-dong, JING Meng-meng
doaj +1 more source
Algorithms, 2022 Granular Computing is a powerful information processing paradigm, particularly useful for the synthesis of pattern recognition systems in structured domains (e.g., graphs or sequences). According to this paradigm, granules of information play the pivotal
Alessio Martino +2 more
doaj +1 more source
Two-Phase Information Granulation Combined with Interval Type-2 FRCM and Mixed Metrics [PDF]
Jisuanji gongcheng, 2021 To address the unevenly distributed complex data with crossed clusters, this paper proposes a two-phase information granulation algorithm based on the trusted granularity criterion, which combines Interval Type-2 Fuzzy C-Means(IT2FCM) clustering and ...
SHAO Lijie, MA Fumin
doaj +1 more source
A Granular Computing Based Classification Method From Algebraic Granule Structure
IEEE Access, 2021 Classification, as one of the main task of machine learning, corresponds to the core work of granular computing, namely granulation. Most of granular computing models and related classification methods are uniquely classifying by granule features, but ...
Linshu Chen +4 more
doaj +1 more source
Support Vector Machine and Granular Computing Based Time Series Volatility Prediction
Journal of Robotics, 2022 With the development of information technology, a large amount of time-series data is generated and stored in the field of economic management, and the potential and valuable knowledge and information in the data can be mined to support management and ...
Yuan Yang, Xu Ma
doaj +1 more source
Information CALS-model of Granulation Processes of Multicomponent Materials
Chemical Engineering Transactions, 2022 Energy-saving processes for granulating multicomponent materials are widely used in industry. To develop these processes, an information CALS-model was created at 6 levels of the hierarchy. At the top level, a grouping is carried out according to 8 types
Dmitriy Makarenkov +4 more
doaj +1 more source
Complex & Intelligent Systems, 2022 For incomplete datasets with mixed numerical and symbolic features, feature selection based on neighborhood multi-granulation rough sets (NMRS) is developing rapidly.
Meng Yuan +3 more
doaj +1 more source