Multi-chain Economic Model

In economics, a model is a mathematical framework illustrating complex economic processes. Most economic models rest on a number of assumptions that are not entirely realistic with limited data sets. Modelling process has two steps: creating a model and then checking the model for accuracy, called diagnostics. Creating and diagnosing a model is frequently an iterative process over extensive data sets. This presentation will focus on techniques of data sciences, blockchains and machine learning for creating and testing economic models from real life data sets. In this presentation, multiple blockchains are used for economic activities and transactions in complex economic processes representing various distributed ledgers which can be combined into or viewed as one complex distributed ledger. Deep learning or any other machine learning techniques can be used for creating a model for each process in a blockchain or for multiple processes combining multiple blockchains or for all the processes combined. There will be discussions about machine learning model (CALSTATDN) for complex economic models, combining techniques of calculus, statistics and data normalizations.