According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are prop...
详细信息
In this paper, the subject of discussion is the uncertainties of Ant Colony Algorithm(ACA). In order to find application and popularize the ACA, we try to find some disciplinarians which can eliminate the impact of un...
详细信息
In this paper, a hybrid algorithm named DPSO-SA is proposed to find near-to-optimal elimination orderings in Bayesian networks. DPSO-SA is a discrete particle swarm optimization method enhanced by simulated annealing....
详细信息
Rule-based reasoning (RBR) and case-based reasoning (CBR) are two complementary alternatives for building knowledge-based “intelligent” decision-support systems. RBR and CBR can be combined in three main ways: RBR f...
Rule-based reasoning (RBR) and case-based reasoning (CBR) are two complementary alternatives for building knowledge-based “intelligent” decision-support systems. RBR and CBR can be combined in three main ways: RBR first, CBR first, or some interleaving of the two. The N EST system, described in this paper, allows us to invoke both components separately and in arbitrary order. In addition to the traditional network of propositions and compositional rules, N EST also supports binary, nominal, and numeric attributes used for derivation of proposition weights, logical (no uncertainty) and default (no antecedent) rules, context expressions, integrity constraints, and cases. The inference mechanism allows use of both rule-based and case-based reasoning. Uncertainty processing (based on Hájek′s algebraic theory) allows interval weights to be interpreted as a union of hypothetical cases, and a novel set of combination functions inspired by neural networks has been added. The system is implemented in two versions: stand-alone and web-based client server. A user-friendly editor covering all mentioned features is included.
Federated policy systems are required to support the complexity and organizational heterogeneity of the modern marketplace. The Community-based Policy Management System (CBPMS) is such a distributed policy management ...
详细信息
Federated policy systems are required to support the complexity and organizational heterogeneity of the modern marketplace. The Community-based Policy Management System (CBPMS) is such a distributed policy management approach. It utilizes a tree-based capability authority model to partition and delegate federated capabilities. However CBPMS delegation chains have limitations such as: performance overheads due to distributed rule evaluation, threats from malformed or malicious federated principals and a lack of flexibility with respect to delegation chain reduction or capability authority re-partitioning. In this paper we introduce a trust management model for CBPMS that addresses all of these issues.. A brief security analysis is presented and a telecommunications service management use case described.
Data mining tools able to semantically interpret textual or linguistic data are acquiring a growing importance. Moreover, the development of large ontologies for general and specific domains provides new tools to incl...
详细信息
For the optimization problem about triangulation of Bayesian networks, a novel genetic algorithm, DHGA, is proposed in this paper. DHGA employs a heuristic-based mutation operation. Moreover, it uses population divers...
详细信息
ISBN:
(纸本)9781424476718
For the optimization problem about triangulation of Bayesian networks, a novel genetic algorithm, DHGA, is proposed in this paper. DHGA employs a heuristic-based mutation operation. Moreover, it uses population diversity to identify stagnation and convergence as well as to guide the search procedure. Experiments on representative benchmarks show that DHGA posses better performance and robustness than other swarm intelligence methods.
We propose a fast and simple application system of 3D model reconstruction. We acquire range images by using a combination of a regular camera and a depth sensor. The reconstruction of a 3D model consists of four key ...
详细信息
We propose a fast and simple application system of 3D model reconstruction. We acquire range images by using a combination of a regular camera and a depth sensor. The reconstruction of a 3D model consists of four key steps: (i) Initial alignment either feature tracking or the 4-points congruent sets algorithm is used to align surfaces captured at different frames. (ii)The iterative closest point (ICP) method is applied to further align the piecewise surfaces from the last step. (iii) The surfaces are merged into a whole 3D model by the volumetric method. (iv) In the refinement step, we fill holes and produce a complete 3D model that approximates the original model with robust repair of polygonal models. At last, we present the experimental results which show that the errors between our reconstructed model and the ground truth are less than 1%.
Business intelligence is a new methodology to maximize the benefits for healthcare organization Business intelligence provides an integrated view of data that can be used to monitor, key performance indicators, identi...
详细信息
Business intelligence is a new methodology to maximize the benefits for healthcare organization Business intelligence provides an integrated view of data that can be used to monitor, key performance indicators, identify hidden patterns in diagnosis and identify variations in cost factors. Intelligent techniques provide an effective computational methods and robust environment for business intelligence in the healthcare domain. From the technical point of view, healthcare based business intelligence systems, are complex to build, maintain and face the knowledge-acquisition difficulty. Efficiency of such systems is determined by the efficiency of the intelligent techniques and methodologies. This paper discusses AI based techniques and approaches which are used in such systems namely; expert systems, data mining and grid computing.
Subspace detection and processing is receiving more attention nowadays as a method to speed up search and reduce processing overload. Subspace Learning algorithms try to detect low dimensional subspaces in the data wh...
详细信息
暂无评论