Method and system for machine failure prediction

A system for machine failure prediction, the system comprising:

• a first processor and a memory communicably coupled thereto,
• wherein the first memory is configured to store data to be executed by the first processor,
• wherein the first processor is configured to
• identify a plurality of basic memory depth values based on a machine failure history;
• ascertain a set of weight values for at least one of the plurality of basic memory depth values according to a pre-stored table which is stored in a memory and includes a plurality of mappings wherein each mapping relates a basic memory depth value to one set of weight values;
• and
• predict a future failure using a Back Propagation Through Time (BPTT) trained Recurrent Neural Network (RNN) based on the ascertained weight values for the at least one of the plurality of basic memory depth values,
• wherein a first set of weight values related to a first basic memory depth value in the pre-stored table is ascertained based on a second set of weight values related to a second basic memory depth value, wherein the second basic memory depth value is less than the first basic memory depth value by a predetermined value.