18218603. EVALUATION METHOD AND INFORMATION PROCESSING APPARATUS simplified abstract (FUJITSU LIMITED)
Contents
- 1 EVALUATION METHOD AND INFORMATION PROCESSING APPARATUS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 EVALUATION METHOD AND INFORMATION PROCESSING APPARATUS - 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
EVALUATION METHOD AND INFORMATION PROCESSING APPARATUS
Organization Name
Inventor(s)
Natsuki Ishikawa of Yamato (JP)
Yoshihiro Okawa of Yokohama (JP)
EVALUATION METHOD AND INFORMATION PROCESSING APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18218603 titled 'EVALUATION METHOD AND INFORMATION PROCESSING APPARATUS
Simplified Explanation
The patent application describes a process where a computer obtains a third matrix by adjusting the position or scale of a target object in a two-dimensional matrix, then combines this with a two-dimensional first matrix to create three-dimensional second data. This data is then inputted into a machine learning model along with the type of day of week and time to predict the influence of the target object.
- Obtaining a third matrix by adjusting the position or scale of a target object in a two-dimensional matrix
- Creating three-dimensional second data by combining the third matrix with a two-dimensional first matrix
- Inputting the second data, type of day of week, and time into a machine learning model to predict the influence of the target object
Potential Applications
This technology could be applied in various industries such as retail, marketing, and urban planning to predict the impact of changes in physical spaces or objects.
Problems Solved
This technology helps in predicting the influence of changes in physical objects or spaces, allowing for better decision-making and planning based on data-driven insights.
Benefits
The technology provides a method to accurately predict the impact of changes, leading to more informed and efficient decision-making processes.
Potential Commercial Applications
"Predictive Influence Analysis Technology for Physical Spaces and Objects" could be used in retail store layout optimization, event planning, and real estate development for predicting the impact of changes in physical environments.
Possible Prior Art
One possible prior art could be a similar technology used in the field of spatial analysis or predictive modeling for urban development projects.
Unanswered Questions
How does this technology handle real-time data input for accurate predictions?
The patent application does not specify how real-time data input is managed for predicting the influence of the target object. This aspect could be crucial for applications requiring instant feedback and decision-making.
What are the limitations of the machine learning model in predicting the influence of the target object accurately?
The patent application does not discuss the potential limitations or challenges faced by the machine learning model in accurately predicting the influence of the target object. Understanding these limitations could provide insights into the reliability of the predictions generated by the technology.
Original Abstract Submitted
A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process, the process includes obtaining a third matrix by changing at least one of a position of a target object already installed or a scale of the target object in a two-dimensional second matrix, obtaining three-dimensional second data by superimposing a two-dimensional first matrix and the third matrix, the first matrix being provided for each facility already installed and indicating a position and a scale thereof, and predicting a degree of influence of the target object by inputting the second data, a type of day of week, and time to a machine learning model trained with three-dimensional first data, a type of day of week, and time as input, and with a degree of influence of the target object as output, the first data being obtained by superimposing the first matrix and the second matrix.
