{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11948111","patent":{"patent_number":"US-11948111","title":"Deep learning-based demand forecasting system","assignee":null,"inventors":[],"filing_date":"2021-10-25T00:00:00.000Z","publication_date":"2024-04-02T00:00:00.000Z","cpc_codes":["G06Q","G06N","G06N","G06N","G06N","G06Q","G06Q"],"num_claims":20,"abstract":"A method of training a neural network to approximate a forecasting error of a passenger-demand forecasting model that includes calculating, using the forecasting model, a historical passenger demand forecast for each key level in a set of key levels and for each departure date in a set of historical departures dates; applying a dropout model to the historical passenger demand forecasts to create a training sample; training, using the historical passenger demand forecasts and the training sample, the neural network, to approximate forecasting errors associated with the forecasting model; calculating, using the forecasting model, a future passenger demand forecast for each key level in the set of key levels and for each departure date in a set of future dates; and approximating, using the trained neural network, the forecasting error associated with the future passenger demand forecasts for the second set of departure dates."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Deep learning-based demand forecasting system","description":"A method of training a neural network to approximate a forecasting error of a passenger-demand forecasting model that includes calculating, using the forecasting model, a historical passenger demand f","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11948111","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11948111","citation_suggestion":"Patentable. \"Deep learning-based demand forecasting system\" (US-11948111). https://patentable.app/patents/US-11948111","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11948111","json":"https://patentable.app/api/llm-context/US-11948111","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T14:37:24.718Z"}