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  6. Support for development using machine learning.

Support for development using machine learning.

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last updated:Sep 17, 2024

ネオリウム・テクノロジー
ネオリウム・テクノロジー
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Achieve optimization of the development process and improvement of analysis accuracy using big data (time series, images)!

The benefits of introducing machine learning into the development process are numerous. By optimizing the design and development processes, efficiency is improved, and defects can be prevented through enhanced predictive accuracy. Furthermore, it reduces the number of prototypes, cutting costs, and allows for process adaptability with real-time feedback. It also achieves a reduction in defective products, strengthens quality control, improves production efficiency through automation, and accelerates simulations. Additionally, by collaborating with digital twins, it enables the optimization of the entire manufacturing process.

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Support for development using machine learning.

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  • Related Link - https://youtu.be/PHVdB6BC6sM

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basic information

At Neorium Technology, we provide technical support to incorporate machine learning into our customers' development processes. Customers may have various challenges such as "how can the big data collected from experimental validation be utilized in machine learning?" and "what do we need to start machine learning?" In this information, we offer engineering services related to nonlinear control target modeling using deep learning and the construction of image recognition systems. The catalog and videos provide simple examples of using Transformers, which are also famous for ChatGPT, as well as examples of image recognition.

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Applications/Examples of results

Development of an image recognition system using deep learning - Developed a system that learns from traffic-related videos using deep learning to distinguish between vehicles, humans, and other objects. Development of a time series prediction model using deep learning - Developed a multi-input multi-output nonlinear dynamic model using deep learning (LSTM model). Hyperparameter optimization of neural networks using machine learning - Applied Bayesian optimization to determine the hyperparameters of neural networks (such as the number of hidden layers and the number of neurons in hidden layers). In addition, we incorporate machine learning into the development of predictive maintenance algorithms for equipment and support for the development of control target models to meet our customers' needs.

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ネオリウム・テクノロジー

ネオリウム・テクノロジー

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Neorium Technology responds to the diverse needs of customers involved in model-based development, consistently providing high-quality technology. In particular, we have a wealth of experience in professional services (model development, contracting, consulting, technical seminars) and product services (sales of control design support software and technical support) in the fields of control, optimization, machine learning, and system modeling. If you have any issues with model-based development, please feel free to consult us. Additionally, in collaboration with our partners, we also offer support services for ADAS simulation testing in the automotive sector. Examples include road surface creation, creation of OpenDRIVE and OpenSCENARIO data, and automation through MILS/HILS.

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