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Splitting and updating hybrid knowledge bases
2011
Theory and Practice of Logic Programming
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We introduce splitting sequences and splitting theorem for hybrid knowledge bases, use them to define a modular update semantics, investigate its basic properties, and illustrate its use on a realistic ...
Many applications that use hybrid knowledge bases in dynamic scenarios require both DL axioms and rules to be updated. ...
Proposition 14 (Layers of an Updatable Dynamic Hybrid Knowledge Base are Basic) Let U be an update-enabling splitting sequence for a dynamic hybrid knowledge base K and X ∈ M. ...
doi:10.1017/s1471068411000317
fatcat:s7sps267aff6fjxhjntmv5qeuy
Using a hybrid rule-based approach in developing an intelligent tutoring system with knowledge acquisition and update capabilities
2004
Expert systems with applications
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Another important component of the ITS, for both its development and maintenance, is its knowledge management unit, which provides knowledge acquisition and knowledge update capabilities to the system, ...
The pedagogical knowledge is distributed in a number of neurule bases within the user modelling and the pedagogical unit. ...
The rule update module (RUM) implements those algorithms and interacts with RCM and the corresponding knowledge base and source knowledge to achieve knowledge update. ...
doi:10.1016/j.eswa.2003.10.007
fatcat:6mzopf7fxbcqfff6sipaeuwfrq
Collaborative Adaptive Filters for Online Knowledge Extraction and Information Fusion
[chapter]
2008
Signal Processing Techniques for Knowledge Extraction and Information Fusion
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Implementations of the proposed hybrid filter in both the real R and complex C domains are analysed and the potential of such a scheme for tracking signal nonlinearity in both domains is highlighted. ...
We show that it is possible to use the fusion of the outputs of adaptive filters to produce a single collaborative hybrid filter and that by tracking the dynamics of the mixing parameter of this filter ...
Kazuyuki Aihara and Dr Yoshito Hirata from the Institute of Industrial Science, University of Tokyo, Japan for providing the wind data sets. ...
doi:10.1007/978-0-387-74367-7_1
fatcat:pyhbwt2pmvawhgmwn47nihyt4a
Boosted Hybrid Recurrent Neural Classifier for Text Document Classification on the Reuters News Text Corpus
2012
International Journal of Machine Learning and Computing
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In particular, a neuroscience based hybrid neural classifier fully integrated with a novel boosting algorithm is examined for its potential in text document classification in a non-stationary environment ...
The novel boosting algorithm termed NeuroBoost is an Adaboost-like algorithm that computes and integrates boosted weights into neural network weights, using back-propagation approach. ...
[8] , [14] and [15] provide motivation in the direction of knowledge based architectures. ...
doi:10.7763/ijmlc.2012.v2.195
fatcat:pwsaaqtsuzakxahnswxutqk5cq
Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook
2020
Energies
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Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to environmental pollution and fuel savings. ...
The presented review targets two main headlines: (a) offline EMSs wherein global optimization-based EMSs and rule-based EMSs are presented; and (b) online EMSs, under which instantaneous optimization-based ...
[101] proposed an energy management strategy for a power-split hybrid electric vehicle, integrating rule-based EMS and ECMS to optimize the fuel economy. ...
doi:10.3390/en13133352
fatcat:gqcaecppvzhybcabwvjzn2gtau
Splitting Technique Initialization in Local PCA
2006
Journal of Computer Science
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The initialization using this proposed splitting technique not only splits and reproduces the mean vector but also the orientation of components in the subspace domain. ...
This study explores a technique that can be easily integrated in the local PCA design and is efficient even when the given statistical distribution is unknown. ...
principal curves based on a mixture model. ...
doi:10.3844/jcssp.2006.53.58
fatcat:uwi6wlwvwzhxpixib3vwk35u7a
Topological Transduction for Hybrid Few-shot Learning
2022
Proceedings of the ACM Web Conference 2022
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from both labeled and unlabeled data to enrich the knowledge about the task-specific data distribution and multi-space relationships. ...
Digging informative knowledge and analyzing contents from the internet is a challenging task as web data may contain new concepts that are lack of sufficient labeled data as well as could be multimodal ...
The TopoNet-H ‡ deletes the GNN-based node and edge updating mechanism, and replaces it with the non-parameterised Label Propagation [19] strategy. ...
doi:10.1145/3485447.3512033
fatcat:o4jes64ec5hhfhoffrxx57j5fa
Hybrid meta-heuristic methods for the multi-resource leveling problem with activity splitting
2012
Automation in Construction
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The PSO algorithms are based on different update mechanisms for the particles' velocities and positions. ...
Based on the results of the computational experiments, we suggest one of the proposed heuristic procedures to be used for solving the multi-resource leveling problem with activity splitting. ...
Son and Skibniewski [18] developed a technique for resource leveling, based on a local optimizer procedure and a hybrid procedure, with the objective of minimizing the difference between the required resources ...
doi:10.1016/j.autcon.2012.04.017
fatcat:p6iahq7nurhftmoj5kcp5v7bme
Cluster-based Communication and Load Balancing for Simulations on Dynamically Adaptive Grids
2014
Procedia Computer Science
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a hybrid parallelization. ...
For data migration, the stack-based intra-cluster communication allows a very low memory footprint for data migration and the RLE leads to efficient updates of connectivity information. ...
Based on this knowledge, we can then store the meta information for shared edges with a run-length encoding in a list of tuples for the left and right communication stack. ...
doi:10.1016/j.procs.2014.05.209
fatcat:iguhbpp4rnhnddvefqtod57tfi
Learning Contextualized Knowledge Structures for Commonsense Reasoning
[article]
2021
arXiv
pre-print
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Given the task input context and an extracted KG subgraph, HGN is trained to generate embeddings for the subgraph's missing edges to form a "hybrid" graph, then reason over the hybrid graph while filtering ...
However, KG edge (fact) sparsity and noisy edge extraction/generation often hinder models from obtaining useful knowledge to reason over. ...
Acknowledgments -19-20271, and NSF SMA 18-29268 . ...
arXiv:2010.12873v3
fatcat:bg7lswqwgzcmhcsceuwgcx256m
A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle
2014
International Journal of Vehicular Technology
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This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. ...
Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and ...
Choudhary, Department of Humanities and Social Sciences, B.I.T.S. Pilani, for giving his valuable time to improve the quality of paper grammatically. ...
doi:10.1155/2014/160510
fatcat:q2fkcjgqp5fddllmnyppwydpgm
A Hybrid Approach: Dynamic Diagnostic Rules for Sensor Systems in Industry 4.0 Generated by Online Hyperparameter Tuned Random Forest
2020
Sci
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In this work, a hybrid component Fault Detection and Diagnosis (FDD) approach for industrial sensor systems is established and analyzed, to provide a hybrid schema that combines the advantages and eliminates ...
the drawbacks of both model-based and data-driven methods of diagnosis. ...
Funding: This research was funded by the DFG research grants LO748/11-1 and OB384/5-1.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/sci2040075
fatcat:kec7wdou5zelli7xvgat3tsuua
Li-ion Battery Aging Conscious Intelligent Energy Management Strategy for Hybrid Electric Buses
2019
Revista Perspectivas
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Therefore, a methodology for updating the energy management strategy along the bus lifetime is proposed, in order to improve the operation costs and extend the battery lifetime. ...
This methodology is based on a dynamic programming optimization, tuning the membership functions in a fuzzy logic control. ...
ACKNOWLEDGMENT This work was partially supported by the Gipuzkoa Provincial Council under Project On-Mobility (Regional Program Red Guipuzcoana de Ciencia, Technology and Innovation). ...
doi:10.47187/perspectivas.vol1iss2.pp38-45.2019
fatcat:ykbbyfbpejfg5c7irhenzdk63u
Attribute Weighting with Adaptive NBTree for Reducing False Positives in Intrusion Detection
[article]
2010
arXiv
pre-print
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Recently data mining algorithms are applied on network-based traffic data and host-based program behaviors to detect intrusions or misuse patterns, but there exist some issues in current intrusion detection ...
It is based on decision tree-based attribute weighting with adaptive na\"ive Bayesian tree, which not only reduce the false positives (FP) at acceptable level, but also scale up the detection rates (DR ...
Find the splitting attribute with highest information gain using the updated weights, w i in D. T = Create the root node and label with splitting attribute. 9. ...
arXiv:1005.0919v1
fatcat:z6jccc4qujairmfed6fybhjgcq
A Hybrid Approach: Dynamic Diagnostic Rules for Sensor Systems in Industry 4.0 Generated by Online Hyperparameter Tuned Random Forest
2020
Sci
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In this work, a hybrid component Fault Detection and Diagnosis (FDD) approach for industrial sensor systems is established and analyzed, to provide a hybrid schema that combines the advantages and eliminates ...
the drawbacks of both model-based and data-driven methods of diagnosis. ...
Funding: This research was funded by the DFG research grants LO748/11-1 and OB384/5-1.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/sci2040061
fatcat:kpwatw25fjdtbcjeo7r6gfqegi
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