Next to this, the above mathematical evaluation has been made in the assumption of a single server with a single resource that sends its notifications directly to the sink or gateway of the sensor network.
This will be supported by a mathematical evaluation and an empirical comparison to existing protocols on bit error rate (BER) graphs.
In this subsection, we will show this potential gain of conditional observation through a mathematical evaluation.
The fuzzy logic enables to transform these ambiguous expressions into numeric values for further mathematical evaluation.
Recently wide applications of neural networks are reported in geophysical scientific papers, mostly lack the consideration of their mathematical evaluation and performance.
Many approaches so far included the digital method using the single sensor data with the mathematical evaluation, and those were believed to be the best to define the ground phenomena, so first we would like to know what is the synoptic view of the Earth surface from various aspects.
The next section discusses our implementation on constrained devices, followed by section 6 presenting a detailed experimental and mathematical evaluation.
For a mathematical evaluation of the underlying assumptions of model selection criteria and their considerations, see [22], [23], [24].
Hence, we advocate the use of mathematical evaluation techniques for ad hoc routing algorithms because they are time efficient, accurate, unbiased, consistent, and scalable.
The above mathematical evaluation reveals that a mechanism such as Conditional Observe is extremely useful for resources that change very frequently.
