17955053. SYSTEMS AND METHODS FOR GENERATING A FORECAST OF A TIMESERIES simplified abstract (Panasonic Intellectual Property Management Co., Ltd.)
Contents
- 1 SYSTEMS AND METHODS FOR GENERATING A FORECAST OF A TIMESERIES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEMS AND METHODS FOR GENERATING A FORECAST OF A TIMESERIES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEMS AND METHODS FOR GENERATING A FORECAST OF A TIMESERIES
Organization Name
Panasonic Intellectual Property Management Co., Ltd.
Inventor(s)
Debdeep Paul of Singapore (SG)
Chandra Suwandi Wijaya of Singapore (SG)
Yizhou Huang of Singapore (SG)
Khai Jun Kek of Singapore (SG)
SYSTEMS AND METHODS FOR GENERATING A FORECAST OF A TIMESERIES - A simplified explanation of the abstract
This abstract first appeared for US patent application 17955053 titled 'SYSTEMS AND METHODS FOR GENERATING A FORECAST OF A TIMESERIES
Simplified Explanation
The method disclosed in the patent application involves generating a forecast of a timeseries by using a set of features, generating forecast results based on an ensemble of prediction models, optimizing the forecast results, probabilistically combining the outputs of optimization modules, and outputting a final forecast based on the combination of the forecast results.
- Receiving a set of features comprising data and timeseries
- Generating forecast results based on an ensemble of prediction models
- Optimizing the forecast results associated with a respective forecast module
- Probabilistically combining the outputs of the optimization modules
- Outputting a final forecast based on the combination of at least two forecast results
Potential Applications
This technology can be applied in various fields such as finance, weather forecasting, sales prediction, and resource planning.
Problems Solved
This technology helps in generating accurate forecasts by combining the outputs of multiple prediction models and optimizing the forecast results.
Benefits
The benefits of this technology include improved forecast accuracy, better decision-making based on reliable predictions, and increased efficiency in forecasting processes.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of advanced forecasting software for businesses in various industries.
Possible Prior Art
One possible prior art for this technology could be the use of ensemble methods in machine learning for improving prediction accuracy.
Unanswered Questions
How does this technology compare to traditional forecasting methods?
This article does not provide a direct comparison between this technology and traditional forecasting methods.
What is the computational complexity of implementing this method?
The article does not address the computational complexity of implementing this method.
Original Abstract Submitted
According to an embodiment, a method for generating a forecast of a timeseries is disclosed. The method comprises receiving a set of features comprising data and timeseries to be used by each of a plurality of prediction models for generating the forecast. Further, the method comprises generating using the set of features, a plurality of forecast results based on an ensemble of the plurality of prediction models. Furthermore, the method comprises optimizing the plurality of forecast results associated with a respective forecast module. Additionally, the method comprises probabilistically combining the outputs of the plurality of optimization modules. Moreover, the method comprises outputting a final forecast based on the combination of the at least two forecast results.
