Systems and methods for real-time data processing and for emergency planning

A modular neural network system for real-time processing of data, comprising:

• a plurality of graphical processors, executing stored programming codes stored in a non-transitory computer storage medium to process scenario data, wherein the programming codes are configured as:
• a first processing segment and a second processing segment, each of the first and the second processing segment comprising respective plurality of processing bulks, wherein:
• a first bulk of the first and the second processing segment is a front portion and a last bulk of the first and the second processing segment is a back portion,
• the first bulk has a shallower data processing block depth than subsequent processing bulks, such that processing block depth increases as a flow of the scenario data increases towards the back portion;
• each processing bulk of the first and the second processing segment comprises a plurality of processing blocks for processing certain micro tasks;
• each processing block having a different kernel size at a same level for capturing features with different data sizes in the scenario data;
• the kernels are selected from one of:
• a convolution kernel, a transpose convolution kernel;
• such that the first segment is responsible for learning special tasks, which the learning will be used in the second segment to reconstruct a volumetric input.