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63 results about "Case Search" patented technology

The activity of looking for individuals with a shared characteristic such as a disease.

Intelligent urban construction examining and approving method based on case-based reasoning technology

The invention discloses an intelligent urban construction examining and approving method based on a case-based reasoning technology. The intelligent urban construction examining and approving method based on the case-based reasoning technology comprises the following steps of constructing an examining and approving case library; inputting new examining and approving case and model parameter information; submitting jogs to a Hadoop cluster to search KNN (k-nearest neighbor algorithm) Map Reduce cases; statistically analyzing a searching result on the basis of a 'weighted integral model'; evaluating and correcting the cases; and performing distributed full-text searching on examining and approving data. The intelligent urban construction examining and approving method has the advantages that by the method, the circumstance of manual examination and approval application at present can be changed, the work efficiency is improved, the basis on examining and approving is increased, and an examining and approving process is intelligent. Distributed searching can be carried out by using a Hadoop frame and a MapReduce frame through a cloud computing center, and a distributed case searching model based on the case-based reasoning technology is established. The 'weighted integral model' is creatively raised to statistically analyzing searched similar cases, and a guidance which is beneficial to new examining and approving cases is obtained.
Owner:ZHEJIANG UNIV CITY COLLEGE

Post-rolling cooling long-termed self-learning method based on case-based reasoning

The invention relates to a post-rolling cooling long-termed self-learning method based on case-based reasoning, which belongs to the technical field of rolling. The method comprises the steps: Step 1: case construction; Step 2: case searching; Step 3: case reuse; and Step 4: case correction. The post-rolling cooling long-termed self-learning method based on case-based reasoning has the advantages that: based on a large amount of on-site production data, the method makes decisions for a long-termed self-learning coefficient in a control cooling mathematic model through case construction, case searching, case reuse, case correction and other case-based reasoning technologies beginning with how to effectively utilize empirical knowledge. For rolled steel specifications, the method can effectively prevent heads from a super-cooling phenomenon, and simultaneously can significantly improve the set precision of sheet and strip head final-cooling temperature models. The post-rolling cooling long-termed self-learning method based on case-based reasoning can make post-rolling cooling models possess the self-adaptive capability of changing with working conditions, and can significantly improve the head setting precision of the models.
Owner:NORTHEASTERN UNIV

Traffic accident responsibility determination system based on machine learning

InactiveCN108389392AReduce the time for manual on-site measurement and evidence collectionShorten the timeDetection of traffic movementCharacter and pattern recognitionImaging processingDistance analysis
The present invention discloses a traffic accident responsibility determination system based on machine learning, and relates to the technical field of traffic accident responsibility determination. The system comprises a traffic information interaction center, an image processing system and an accident responsibility analysis system. The traffic information interaction center comprises an image character receiving module and a determination result sending module; the image processing system comprises an image loading module, a color extraction module, a contour extraction module, a Gaussian Blur module and a distance analysis module; and the accident responsibility analysis system comprises a feature case search module and a comparison computing module. The traffic accident responsibilitydetermination system based on machine learning allow a reporter to replace the traffic police to perform photograph and evidence collection of a scene of a traffic accident and pass back informationin real time for responsibility analysis and determination so as to effectively reduce the time of scene measurement evidence collection, analysis and determination, is high in efficiency and accuratein determination, reduce human subjective factors, can recover the traffic as soon as possible and can avoid traffic congestion.
Owner:GUANGDONG RONGQE INTELLIGENT TECH CO LTD

Similar medical case search device, similar medical case search method, and similar medical case search program

Provided are a similar medical case search device, a similar medical case search method, and a similar medical case search program, with which it is possible to perform a search which is focused on the respective feature amounts of multiple regions of interest. A similar medical case search server (17) is equipped with a feature amount calculation unit (62), an individual similarity calculation unit (65), and a similar medical case search unit (67). The feature amount calculation unit (62) obtains a feature amount for each of multiple regions of interest (ROI). Each region of interest (ROI) contains one or more different object lesions (OL) and is specified in inspection data (21) containing one or more inspection images (19), and is specified so as to contain an object lesion (OL), which is a lesion existing in an inspection image (19). The individual similarity calculation unit (65) calculates an individual degree of similarity for each region of interest (ROI) by comparing the feature amount for each region of interest (ROI) and the feature amount for a medical case lesion (CL), which is a lesion in a medical case image (22) and registered in a medical case. The similar medical case search unit (67) searches for similar medical cases on the basis of the multiple individual degrees of similarity that have been calculated.
Owner:FUJIFILM CORP
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