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The use of network techniques was very useful to depict animal exchanges between herds and to evaluate their level of relationship due to animal exchanges.
This implies the use of network techniques for the analysis of time-stamped data.
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But Pašagić [16] has also introduced some possible uses of network techniques in transport.
The use of neural network techniques to predict trends relating to air pollutants is regarded as a reliable and cost-effective method for the task of prediction.
This chapter presents the use of network analysis techniques in a fully worked example.
This tradeoff is one of the reasons for restricting the use of network MIMO techniques to a limited number of cells or areas of the system.
The posed optimization problem is solved approximately with use of network-flow techniques.
We were able to study the feasibility of using neural network techniques in generating reliable power models.
This chapter focuses on the design and implementation of fuzzy neural networks that use neural network techniques to realize fuzzy rule-based systems under different fuzzy inference models.
However, due to the use of Network Address Translation (NAT) techniques at the mesh gateway, existing connections exploiting stateful protocols, such as TCP, are terminated when the backhaul link is switched.
In addition, the hybrid networks automatically derive the fuzzy rules (knowledge base) of the problem domain using neural network techniques and hence avoid the pitfalls of traditional fuzzy systems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com