Resource Demand Projection Model Using Pseudofactors
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Solution Overview
Problem
Existing resource forecasting techniques struggle to adapt to changing circumstances and manage data from multiple sources, often discarding outlier data, which can lead to difficulties in solving resource allocation problems effectively.
Innovation Solution
A computer-implemented method that identifies factors associated with tasks and resources, generates a model to project resource demand, and adjusts the model using pseudofactors to account for variances between projections and historical data, allowing for adaptation to changing circumstances and improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If known techniques focus on conforming data and discarding nonconforming or outlier data, then data consistency is improved, but adaptability to changing circumstances deteriorates
Solution Approach 1:
The patent converts outlier data, which was traditionally discarded as harmful or nonconforming, into a beneficial resource for detecting changing circumstances. The system identifies outlier scenarios and generates pseudofactors from them, transforming previously useless data into valuable inputs that improve model adaptability and resource demand projection accuracy.
2Device complexity
If a model uses only first factors directly corresponding to task and resource, then model simplicity is improved, but prediction accuracy deteriorates
Solution Approach 1:
The patent introduces pseudofactors as intermediary elements that bridge the gap between first factors (directly corresponding to task and resource) and actual resource demand. These pseudofactors, generated from outlier scenarios, serve as mediators that capture indirect relationships and changing circumstances, thereby improving prediction accuracy without substantially increasing model complexity.
3Adaptability or versatility
If a model is frequently adjusted to adapt to changing circumstances, then adaptability is improved, but processing load increases
Solution Approach 1:
The patent performs preliminary action by pre-identifying outlier scenarios and generating pseudofactors in advance, before they are needed for resource demand projection. This preliminary processing allows the model to be pre-adapted to changing circumstances, reducing the need for frequent adjustments and lowering processing load during actual resource allocation tasks.
Data Source
AI summary
Examples of the disclosure project resource demand. In some examples, a first factor that corresponds to a task and/or a resource is identified. The first factor is associated with one or more scenarios. A model associated with the scenarios is generated. The model includes the first factor. The model is used to generate a projection associated with an expected resource demand for a first scenario. The projection is compared with historical data associated with an actual resource demand for the first scenario to determine a variance between the projection and the historical data. Based on the variance, a second factor that does not directly correspond to the task and/or the resource is generated. The second factor is configured to increase an accuracy of the model. Aspects of the disclosure enable the model to be generated, maintained, and/or updated in a calculated and systematic manner for increased performance.