Management of Humanitarian Projects in Conflict Zones Based on Complementary Neural Networks
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- Complementary neural network, Humanitarian Projects, Conflict Zones
The model of complementary neural networks for managing project portfolios of Humanitarian Projects in Conflict Zones under uncertainty (observability, unverified information and imperfection of loss estimation methods) is considered. The principles and methods of forming a portfolio of projects of loss Humanitarian Projects in Conflict Zones are defined. The properties of neural networks to parallel processing of information, self-organization, training, generalization, etc. are determined. The general model of the neural network, its elements and training techniques are given. The concepts of complementary neural network and complementarity classes are introduced. The concept of complementary neural network architecture is defined. Within the complementary networks, an algebra with a medium is introduced, which is determined by elements of the artificial neural network and a signature that forms classes of operations of the complementarity of the neural networks concerning portfolio management of loss Humanitarian Projects in Conflict Zones.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Sergey Bushuyev AU - Igbal Babayev AU - Jahid Babayev AU - Boris Kozyr PY - 2019/12 DA - 2019/12 TI - Management of Humanitarian Projects in Conflict Zones Based on Complementary Neural Networks BT - Proceedings of the 5th IPMA SENET Project Management Conference (SENET 2019) PB - Atlantis Press SP - 64 EP - 67 SN - 2352-5428 UR - https://doi.org/10.2991/senet-19.2019.11 DO - https://doi.org/10.2991/senet-19.2019.11 ID - Bushuyev2019/12 ER -