Thoros Scoring Algorithm

At the core of Thoros.AI lies the Thoros Scoring Algorithm (TSA), in charge of aggregating and synthesizing the on/off-chain and sentiment data described above. Our algorithm employs a sophisticated methodology to evaluate blockchain projects by combining all the above information into a scoring system. The scoring system itself uses machine learning techniques to continually refine its accuracy by learning from historical data trends and outcomes. However, the true innovation of the TSA lies in its dynamic weighting system. Unlike static models, Thoros adapts the weights of different metrics based on evolving market conditions, the project life cycle stage and the context of the project being analyzed.

For example, during a market downturn, financial stability metrics such as burn rate might be weighted more heavily. In contrast, during a technological innovation cycle, metrics related to smart contract upgrades and developer activity might receive a higher emphasis.

Thus the TSA algorithm, by continually refining its metrics to adapt to the current conditions through dynamic weighting, is able to provide the most up-to-date insight about a given blockchain project, guiding investors to navigate the crypto market, choosing the blockchain where to deploy your strategic project or or evaluating the trendiest NFTs.