Nec corporation (20240160970). OPTIMIZATION SYSTEM, OPTIMIZATION METHOD, AND RECORDING MEDIUM simplified abstract
Contents
- 1 OPTIMIZATION SYSTEM, OPTIMIZATION METHOD, AND RECORDING MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 OPTIMIZATION SYSTEM, OPTIMIZATION METHOD, AND RECORDING MEDIUM - 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
OPTIMIZATION SYSTEM, OPTIMIZATION METHOD, AND RECORDING MEDIUM
Organization Name
Inventor(s)
OPTIMIZATION SYSTEM, OPTIMIZATION METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240160970 titled 'OPTIMIZATION SYSTEM, OPTIMIZATION METHOD, AND RECORDING MEDIUM
Simplified Explanation
The optimization system described in the abstract includes various units to acquire, amplify, calculate weights, and output decision-making information from a plurality of experts. Here is a simplified explanation of the abstract:
- Acquisition unit gathers loss data from decision-making by multiple experts.
- Amplification unit enhances experts' information with different timings.
- Weight calculation unit computes decision-making weights based on amplified data.
- Output unit displays decision-making weights of each expert.
Potential Applications
This technology could be applied in various fields such as finance, healthcare, and sports analytics to optimize decision-making processes.
Problems Solved
This system helps in improving the accuracy and efficiency of decision-making by combining and weighting inputs from multiple experts.
Benefits
The system provides a structured approach to decision-making, leading to better outcomes and reducing the impact of individual biases.
Potential Commercial Applications
"Optimization System for Expert Decision-Making" could be utilized in consulting firms, investment companies, and research institutions to enhance their decision-making processes.
Possible Prior Art
One possible prior art could be the use of machine learning algorithms to optimize decision-making based on expert inputs.
What are the potential limitations of this technology in real-world applications?
In real-world applications, the system may face challenges in handling a large volume of data from multiple experts and ensuring the accuracy of weight calculations.
How scalable is this technology for different industries and decision-making scenarios?
The scalability of this technology depends on the complexity of decision-making scenarios and the adaptability of the system to different industries' requirements. Further research and testing would be needed to assess its scalability across various domains.
Original Abstract Submitted
the optimization system includes an acquisition unit, an amplification unit, a weight calculation unit, and an output unit. the acquisition unit acquires a loss caused as a result of decision-making by a plurality of experts in repetition of decision-making in which the plurality of experts are weighted and combined. the amplification unit amplifies each of the plurality of experts into a plurality of experts having different timings for initializing the information on the weight. the weight calculation unit calculates the weight of decision-making of each of the plurality of experts based on the weight of decision-making calculated using the loss for each of the experts amplified. the output unit outputs a weight of the decision-making of each of the plurality of experts.
