In this paper, we propose an incremental method of Granular Networks (GN) to construct conceptual and computational platform of Granular Computing (GrC). The essence of this network is to describe the associations bet...In this paper, we propose an incremental method of Granular Networks (GN) to construct conceptual and computational platform of Granular Computing (GrC). The essence of this network is to describe the associations between information granules including fuzzy sets formed both in the input and output spaces. The context within which such relationships are being formed is established by the system developer. Here information granules are built using Context-driven Fuzzy Clustering (CFC). This clustering develops clusters by preserving the homogeneity of the clustered patterns associated with the input and output space. The experimental results on well-known software module of Medical Imaging System (MIS) revealed that the incremental granular network showed a good performance in comparison to other previous literature.展开更多
Utilizing granular computing to enhance artificial neural network architecture, a newtype of network emerges—thegranular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The a...Utilizing granular computing to enhance artificial neural network architecture, a newtype of network emerges—thegranular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The ability toprocess both numerical and granular data, leading to improved interpretability. This paper proposes a novel designmethod for constructing GNNs, drawing inspiration from existing interval-valued neural networks built uponNNNs. However, unlike the proposed algorithm in this work, which employs interval values or triangular fuzzynumbers for connections, existing methods rely on a pre-defined numerical network. This new method utilizesa uniform distribution of information granularity to granulate connections with unknown parameters, resultingin independent GNN structures. To quantify the granularity output of the network, the product of two commonperformance indices is adopted: The coverage of numerical data and the specificity of information granules.Optimizing this combined performance index helps determine the optimal parameters for the network. Finally,the paper presents the complete model construction and validates its feasibility through experiments on datasetsfrom the UCIMachine Learning Repository. The results demonstrate the proposed algorithm’s effectiveness andpromising performance.展开更多
The effects of packing configurations on the phase transition of straight granular chute flow with two bottlenecks axe studied. The granular flow shows a dilute- to-dense flow transition when the channel width is vari...The effects of packing configurations on the phase transition of straight granular chute flow with two bottlenecks axe studied. The granular flow shows a dilute- to-dense flow transition when the channel width is varied, accompanied with a peculiar bistable phenomenon. The bistable phenomenon is induced by the initial packing config- uration of particles. When the packing is dense, the initial flux is small and will induce a dense flow. When the packing is loose, the initial flux is large and will induce a di- lute flow. The fabric network of granulax packing is analyzed from a complex network perspective. The degree distribution shows quantitatively different characteristics for the configurations. A two-dimensional （2D） packing clustering coefficient is defined to better quantify the fabric network.展开更多
In the internet protocol（IP） over multi-granular optical switch network （IP/MG-OXC）, the network node is a typical multilayer switch comprising several layers, the IP packet switching （PXC） layer, wavelength swi...In the internet protocol（IP） over multi-granular optical switch network （IP/MG-OXC）, the network node is a typical multilayer switch comprising several layers, the IP packet switching （PXC） layer, wavelength switching （WXC） layer and fiber switching （FXC） layer. This network is capable of both IP layer grooming and wavelength grooming in a hierarchical manner. Resource provisioning in the multi-granular network paradigm is called hierarchical grooming problem. An integer linear programming （ILP） model is proposed to formulate the problem. An iterative heuristic approach is developed for solving the problem in large networks. Case study shows that IP/MG-OXC network is much more extendible and can significantly save the overall network cost as compared with IP over wavelength division multiplexing network.展开更多
文摘In this paper, we propose an incremental method of Granular Networks (GN) to construct conceptual and computational platform of Granular Computing (GrC). The essence of this network is to describe the associations between information granules including fuzzy sets formed both in the input and output spaces. The context within which such relationships are being formed is established by the system developer. Here information granules are built using Context-driven Fuzzy Clustering (CFC). This clustering develops clusters by preserving the homogeneity of the clustered patterns associated with the input and output space. The experimental results on well-known software module of Medical Imaging System (MIS) revealed that the incremental granular network showed a good performance in comparison to other previous literature.
基金the National Key R&D Program of China under Grant 2018YFB1700104.
文摘Utilizing granular computing to enhance artificial neural network architecture, a newtype of network emerges—thegranular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The ability toprocess both numerical and granular data, leading to improved interpretability. This paper proposes a novel designmethod for constructing GNNs, drawing inspiration from existing interval-valued neural networks built uponNNNs. However, unlike the proposed algorithm in this work, which employs interval values or triangular fuzzynumbers for connections, existing methods rely on a pre-defined numerical network. This new method utilizesa uniform distribution of information granularity to granulate connections with unknown parameters, resultingin independent GNN structures. To quantify the granularity output of the network, the product of two commonperformance indices is adopted: The coverage of numerical data and the specificity of information granules.Optimizing this combined performance index helps determine the optimal parameters for the network. Finally,the paper presents the complete model construction and validates its feasibility through experiments on datasetsfrom the UCIMachine Learning Repository. The results demonstrate the proposed algorithm’s effectiveness andpromising performance.
基金Project supported by the National Natural Science Foundation of China(Nos.11034010 and 71171185)
文摘The effects of packing configurations on the phase transition of straight granular chute flow with two bottlenecks axe studied. The granular flow shows a dilute- to-dense flow transition when the channel width is varied, accompanied with a peculiar bistable phenomenon. The bistable phenomenon is induced by the initial packing config- uration of particles. When the packing is dense, the initial flux is small and will induce a dense flow. When the packing is loose, the initial flux is large and will induce a di- lute flow. The fabric network of granulax packing is analyzed from a complex network perspective. The degree distribution shows quantitatively different characteristics for the configurations. A two-dimensional （2D） packing clustering coefficient is defined to better quantify the fabric network.
基金Sponsored by Agency for Singapore Technology and Advance Research(RGM01/16)
文摘In the internet protocol（IP） over multi-granular optical switch network （IP/MG-OXC）, the network node is a typical multilayer switch comprising several layers, the IP packet switching （PXC） layer, wavelength switching （WXC） layer and fiber switching （FXC） layer. This network is capable of both IP layer grooming and wavelength grooming in a hierarchical manner. Resource provisioning in the multi-granular network paradigm is called hierarchical grooming problem. An integer linear programming （ILP） model is proposed to formulate the problem. An iterative heuristic approach is developed for solving the problem in large networks. Case study shows that IP/MG-OXC network is much more extendible and can significantly save the overall network cost as compared with IP over wavelength division multiplexing network.
