Weekly Demand Forecast LSTM Diagram

Weekly Demand Forecast LSTM

This neural network diagram shows a small sequence model for weekly demand forecasting. The input block collects twelve weeks of sales history alongside price and promotion context. An LSTM layer processes the ordered observations so the forecast can reflect recent trends and repeating patterns. A dense layer transforms the LSTM representation before the final block estimates next-week units. The diagram gives planners and engineers a shared view of the model boundary: what history enters, where sequence learning happens, and what the model returns. It does not imply that the forecast is a purchase recommendation; inventory constraints, lead times, and service targets belong in a planning layer around the model.

유형 블록 다이어그램표준 Ogata / standard controls textbook convention엔진 schematex-blockdiagram업데이트됨 2026. 9. 24.

요청 내용

“Create a neural network diagram for weekly demand forecasting with 12 weeks of sales, price, and promotion inputs, a 64-unit LSTM, a 32-unit ReLU layer, and a next-week unit forecast.”

그렇다면Add a holiday-calendar input to the history block.Change the forecast to four weeks ahead.

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01History window

Include twelve recent weeks of demand context.

02Sequence model

Use an LSTM for ordered weekly inputs.

03Forecast horizon

State the next-week target clearly.

Use this model overview for a sequence forecast that combines past sales with commercial signals such as price and promotions.

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자주 묻는 질문

What is an LSTM?

A long short-term memory network is a recurrent neural-network layer designed to retain useful information across a sequence.

Why include promotions?

Promotions can change demand sharply, so including them helps the model separate promotion effects from baseline sales.

What is a forecast horizon?

It is the future period the model predicts, such as the next week or the next four weeks.