MiningMath

MiningMath

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One of the unavoidable steps for the next generation of Data Science and Artificial Intelligence technologies applied to mining

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Estimated reading: 1 minute 813 views

During some steps, such as Data Validation, the main question should be about the runtime and the progress bar. It is worth mention that this is a rough guess, since math programming isn’t something very predictable. The pre-processing steps, in which the algorithm eliminates the useless material, might keep it stuck in the initial percentage (2%, 4%, etc) for a while, but after that, the optimization can get faster.

MiningMath can virtually handle any model size. It has successfully run models from clients beyond 10M blocks without reblocking, which might take a few hours to finish. The runtime is directly proportional to the number of blocks, destinations, periods, constraints in use, and variables imported. Therefore, the combination of multiple aspects, are directly related to the complexity of the deposit.

Try to check if there is any “floating blocks” without any connection with the model topography. These regions might affect the optimization, thus, eliminate them so that MiningMath can work well.

Figure 1: Floating blocks.
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