Plan recognition,the inverse problem of plan synthesis,is important wherever a system is expected to produce a kind of cooperative or competitive *** plan recognizers,however,suffer the problem of acquisition and hand...
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Plan recognition,the inverse problem of plan synthesis,is important wherever a system is expected to produce a kind of cooperative or competitive *** plan recognizers,however,suffer the problem of acquisition and hand-coding a larger plan *** paper is aims to show that modern planning techniques can help build plan recognition systems without suffering such ***,we show that the planning graph,which is an important component of the classical planning system Graphplan,can be used as an implicit,dynamic planning library to represent actions,plans and *** also show that modern plan generating technology can be used to find valid plans in this *** this sense,this method can be regarded as a bridge that connects these two research *** and theoretical results also show that the method is efficient and scalable.
We study the problem of answering queries given a set of mappings between peer ontologies. In addition to the schema mapping between peer ontologies, there are axioms to give constraints to classes and properties. We ...
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In this paper, a genetic algorithm approach with a novel mutation operator based on perturbation and local search has been proposed to solve an advanced planning and scheduling (APS) model in manufacturing supply chai...
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The difficulties of modeling complex knowledge system lie in a large quantity of knowledge rules and the difficulty in organizing rules and grasping their mutual logical relationships. This article proposed a concept ...
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This paper presents a new interest local regions descriptors method based on Hilbert-Huang Transform. The neighborhood of the interest local region is decomposed adaptively into oscillatory components called intrinsic...
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ISBN:
(纸本)1901725340
This paper presents a new interest local regions descriptors method based on Hilbert-Huang Transform. The neighborhood of the interest local region is decomposed adaptively into oscillatory components called intrinsic mode functions (IMFs). Then the Hilbert transform is applied to each component and get the phase and amplitude information. The proposed descriptors samples the phase angles information and amalgamates them into 10 overlap squares with 8-bin orientation histograms. The experiments show that the proposed descriptors are better than SIFT and other standard descriptors. Essentially, the Hilbert-Huang Transform based descriptors can belong to the class of phase-based descriptors. So it can provides a better way to overcome the illumination changes. Additionally, the Hilbert-Huang transform is a new tool for analyzing signals and the proposed descriptors is a new attempt to the Hilbert-Huang transform.
Description Logics are formalisms for representing knowledge of various domains in a structured and formally well-understood way. Typically, DLs are limited to dealing with precise and well defined concepts. In this p...
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ISBN:
(纸本)9781601320254
Description Logics are formalisms for representing knowledge of various domains in a structured and formally well-understood way. Typically, DLs are limited to dealing with precise and well defined concepts. In this paper we first present a fuzzy extension of ALC and define its syntax and semantics. Then we devote to taking advantage of the expressive power and reasoning capabilities of fuzzy ALC by encoding flexible planning problems within the framework of fuzzy ALC. Both theory and experimental results have shown that our method is sound and efficient.
At present, qualitative spatial reasoning has become the hot issues in many research fields. The most popular models of spatial topological relations are Region Connection Calculus (RCC) and 9-intersection model. Howe...
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The existing 3D direction models approximate spatial objects either as a point or as a minimal bounding block, which decrease the descriptive capability and precision. Considering the influence of object's shape, ...
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It is inadequate considering only one aspect of spatial information in practical problems, where several aspects are usually involved together. Reasoning with multi-aspect spatial information has become the focus of q...
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Fuzzy neural network combines the learning capacity of artificial neural networks with the interpretability of the fuzzy systems. A novel structure learning algorithm for fuzzy neural networks (SLNN) is presented in t...
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Fuzzy neural network combines the learning capacity of artificial neural networks with the interpretability of the fuzzy systems. A novel structure learning algorithm for fuzzy neural networks (SLNN) is presented in this paper. The neurons of SLNN are created and adapted as online learning proceeds. The learning rule of SLNN is based on Hebb as well as soft competitive learning. The soft competitive learning cannot only let SLNN be able to learn from new data but also prevent it from losing the knowledge that has been learned earlier. To obtain a concise fuzzy rule, a pruning algorithm is adopted in SLNN, which does not disobey the basic design philosophy of fuzzy system. Simulations are performed on the primary benchmarks: circle-in-the-square, two spirals apart, UCI machine learning archive's synthetic control chart time series, and KDDCUP'99 data set. Compared with fuzzy ARTMAP, BP and hierarchical neuro-fuzzy quadtree (HNFQ), the fuzzy neural network achieves higher performance.
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