Bridgestone had two patents in big data during Q1 2024. Bridgestone Corp filed a patent for a computer implemented predictive method using machine learning to develop composites for tire tread compounds. The method involves providing a dataset of existing composite recipes and dynamic properties, normalizing the data, pre-processing it with Data Mining, training an algorithm, and using it to predict the dynamic properties of a composite to be tested. GlobalData’s report on Bridgestone gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Bridgestone had no grants in big data as a theme in Q1 2024.
Recent Patents
Application: Predictive method based upon machine learning for the development of composites for tire tread compounds (Patent ID: US20240006033A1)
The patent filed by Bridgestone Corp. describes a computer-implemented predictive method using machine learning for developing composites for tire tread compounds. The method involves providing a raw data database of existing composite recipes and their dynamic properties, normalizing the data, pre-processing it through data mining to eliminate aberrant data and add fictitious ingredients, training an algorithm through automatic learning, and applying the algorithm to experimental data to predict the dynamic properties of the composite to be tested. The dynamic properties predicted include loss module and storage module of the composite.
The method further includes steps such as iterative normalization based on the most repeated recipe in the dataset to reduce variability, dividing dynamic properties by corresponding properties of reference composites for comparison, applying weight/penalty logic to impose physical constraints on the properties during training, and using data mining algorithms for pre-processing. The data mining algorithms remove anomalous data and may execute principal component analysis (PCA) to add new fictitious ingredients related to specific categories of actual ingredients. This method allows for efficient and accurate prediction of dynamic properties of composites for tire tread compounds, enhancing the development process in the tire manufacturing industry.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
