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Advanced Computational Methods for Knowledge Engineering
Tien, Van Do [Do, Van Tien (Távközlés), szerk.] Hálózati Rendszerek és Szolgáltatások Tanszék (BME / VIK)
;
Hoai, An Le Thi [szerk.]
;
Ngoc, Thanh Nguyen [szerk.]
Angol nyelvű Konferenciakötet (Könyv) Tudományos
Megjelent: Springer Netherlands, Budapest, Magyarország, 428 p.
2014
Konferencia:
Advanced Computational Methods for Knowledge Engineering 2014-05-08 [Budapest, Magyarország]
Sorozatok:
Advances in Intelligent Systems and Computing 2194-5357 2194-5365, 282
Azonosítók
MTMT: 2698771
DOI:
10.1007/978-3-319-06569-4
ISBN:
9783319065687
Fejezetek
Ádám Horváth. Usability of Deterministic and Stochastic Petri Nets in the Wood Industry: A Case Study. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 119-127
Tran Thi Xuan et al. A New Approach for Buffering Space in Scheduling Unknown Service Time Jobs in a Computational Cluster with Awareness of Performance and Energy Consumption. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 129-139
Imre Kelényi et al. Supporting Energy-Efficient Mobile Application Development with Model-Driven Code Generation. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 143-156
Nguyen Thanh Binh. Policy by Policy Analytical Approach to Develop GAINS-City Data Marts Based on Regional Federated Data Warehousing Framework. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 243-253
Pödör Zoltán et al. Application of Sigmoid Models for Growth Investigations of Forest Trees. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 353-364
Marcell Fehér et al. GPS tracklog compression by heading-based filtering. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 367-376
Vinh Thong Ta et al. Formal Security Verification of Transport Protocols for Wireless Sensor Networks. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 389-403
Levendovszky János et al. How to apply Large deviation theory to routing in WSNs. (2014) Megjelent: Advanced Computational Methods for Knowledge Engineering pp. 405-414
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2025-05-21 23:42
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