Journal of Intelligent & Fuzzy Systems - Volume 33, issue 5

Authors: Zhu, Linli | Pan, Yu | Farahani, Mohammad Reza | Gao, Wei

Article Type: Research Article

Abstract: In recent years, the ontology problem has gained attention in machine learning and it has many applications in various fields. Ontology similarity computation plays a critical role in practical implementations. In ontology learning setting, one learns a real-valued score function that assigns scores to ontology vertices. Then, the similarity between vertices is weighted in terms of the difference between their corresponding scores. The purpose of this paper is to report a new ontology learning algorithm for ontology similarity measuring and ontology mapping by means of magnitude preserving. The classes of ontology loss function are considered in regularization ontology framework, the …ontology function is supposed to be linear, and the gradient descent implement is presented for getting the optimal ontology function. The result data from our four simulation experiments imply that the new proposed ontology trick has high efficiency and accuracy in biology and plant science with regard to ontology similarity measure, and humanoid robotics and education science with regard to ontology mapping. Show more

Keywords: Ontology, similarity measure, ontology mapping, magnitude preserving

DOI: 10.3233/JIFS-169363

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3113-3122, 2017

Authors: Wu, Hualong | Gan, Jianzhou | Zhao, Bo | Gao, Wei

Article Type: Research Article

Abstract: Strong connections between the chemical characteristics of chemical compounds, materials and drugs and their topological structures have been proved by lots of previous research. For instance, they get the connections in melting point and boiling point. The chemical indices from these molecular topological structures turn out to be favorable for chemists, material and medical scientists, when they try to get the relevant chemical reactivity, biological activity and physical features. As a result, the shortage of the experiments can be covered and made up, if the conduct the study of the topological indices on the molecular structures. Meanwhile, the study can …also make contributions by providing the theoretical evidence in chemical, pharmaceutical and material engineering. On the basis of graph analysis and computation derivation, some degree and distance mixing indices of some classes of Harary graphs and coronene polycyclic aromatic hydrocarbons are determined in the paper. Therefore, the study lay a theoretical foundation for the material properties. Show more

Keywords: Intelligent computing, molecular structure, Harary graph, generalized degree distance, coronene polycyclic aromatic hydrocarbon

DOI: 10.3233/JIFS-169364

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3123-3135, 2017

Authors: Liu, Xiaoyong | Zhou, Zhili

Article Type: Research Article

Abstract: Reasonable structure of human resource is of great significance to development of an organization, so accurate prediction of human resource structure is a very important research problem. Adaptive Neuro-Fuzzy Inference System (abbreviated as ANFIS) is a high-efficiency learning model, and its distributed network structure has very effective result in establishing nonlinear model and constructing time series prediction model. However, classical ANFIS has some disadvantages, such as difficult determination of structure and large randomness of training parameter setting. This paper provides a hybrid prediction model of human resource structure by using the algorithm based on fusion of PSO with random weight, …RPSO, and ANFIS, named RPSO-ANFIS. The novel algorithm uses RPSO to train relevant parameters of ANFIS and determine network structure of ANFIS. Empirical results shows that, compared with GA-ANFIS and PSO-ANFIS, RPSO-ANFIS has advantages of rapid learning speed, high prediction accuracy and smaller relative mean error, which indicated RPSO-ANFIS has good practical application value in predicting the structure of human resource. Show more

Keywords: Adaptive neuro-fuzzy inference system, PSO, the structure of human resources, random weight, fuzzy logic

DOI: 10.3233/JIFS-169365

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3137-3143, 2017

Authors: Gong, Shu | Siddiqui, Muhammad Kamran | Luo, Yi | Gao, Wei

Article Type: Research Article

Abstract: In the setting of software definition network (SDN), whether there exists an available transmission plan between any two sites is equal to whether there exists a fractional factor after deleting certain vertices and edges in the corresponding graph. A graph G is called a fractional ID-(a , b , m )-deleted graph if after deleting any independent-set I , the remaining graph G  - I is a fractional (a , b , m )-deleted graph. A fractional (g , f )-factor F of a graph G is called a Hamiltonian fractional (g , f )-factor if F …includes a Hamiltonian cycle. Furthermore, we say that G has a ID-Hamiltonian fractional (g , f )-factor if after deleting any independent set of G the remaining graph of G includes a Hamiltonian fractional (g , f )-factor. In this paper, we first give a binding number condition for a graph to be a fractional ID-(a , b , m )-deleted graph, and then two sufficient conditions for graphs to have ID-Hamiltonian fractional (g , f )-factors are obtained. Show more

Keywords: Fractional factor, software definition network, fractional ID-(a, b, m)-deleted graph, binding number, ID-Hamiltonian fractional (g, f)-factor

DOI: 10.3233/JIFS-169366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3145-3152, 2017

Authors: Gao, Wei | Zhu, Linli | Guo, Yun | Wang, Kaiyun

Article Type: Research Article

Abstract: In order to represent the semantics and concepts better, the ontology, as an efficient model, has penetrated into all research areas of the computer science and information technology. In recent years, the ontology framework has also been applied to biology, chemistry, pharmaceutics, geography, and other fields, and it has attracted much attention from the researchers. Multi-dividing ontology algorithm is one of the popular learning approaches for ontology applications in which the vertex set and sample data are divided into several parts. In this paper, we introduce a new ontology optimization scheming by means of representer theorem and kernel function, and …the method is a kind of linear programming. Four experiments are designed for the application of ontology algorithms in different fields to test the effectiveness by comparing the implement data. Show more

Keywords: Ontology, similarity measure, ontology mapping, kernel function, linear programming

DOI: 10.3233/JIFS-169367

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3153-3163, 2017

Authors: Zhang, Yaping | Xu, Dan

Article Type: Research Article

Abstract: Multiresolution technique is one of the most efficient approaches to improve the rendering performance, but its design and implementation for massive meshes are still very difficult. This paper gives a solution to the construction and rendering of multiresolution representation for massive meshes. Our approach provides a dual hierarchy: a cluster hierarchy for coarse-grained selective refinement and a vertex hierarchy for progressive meshes contained in the cluster for fine-grained local refinement. In order to promote the speed of the construction and rendering of multiresolution representation for massive meshes, we implement parallel half edge collapse to build the vertex hierarchy in the …clusters and view-dependent refinement for vertex hierarchy in parallel with GPU. To prevent data transmission delay to stall the rendering, a separate CPU thread is used to prefetch clusters data into main memory. Our construction process is faster than a corresponding sequential implementation and the rendering results are of comparable quality. Show more

Keywords: Multiresolution representation, massive meshes, cluster hierarchy, vertex hierarchy, edge collapse, GPU

DOI: 10.3233/JIFS-169368

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3165-3172, 2017