Neural networks for topology optimization
نویسندگان
چکیده
منابع مشابه
Neural networks for topology optimization
In this research, we propose a deep learning based approach for speeding up the topology optimization methods. The problem we seek to solve is the layout problem. The main novelty of this work is to state the problem as an image segmentation task. We leverage the power of deep learning methods as the efficient pixel-wise image labeling technique to perform the topology optimization. We introduc...
متن کاملClassification Approach for Reliability-based Topology Optimization using Probabilistic Neural Networks
Optimization algorithms traditionally have been solved using a deterministic approach where a design solution was obtained for specific force and boundary conditions. However, performing probabilistic analysis prior to the early stage of fabrication is critical to reduce cost, improve product quality, and provide a better understanding of failure mechanisms and sensitivity to process variation....
متن کاملOptimization and Neural Networks
Artificial Neural Networks are a supervised machine learning technique with a number of drawbacks. The drawbacks fall into the categories of topology selection, optimization and manual tuning. These drawbacks can be partially overcome in a recently proposed technique that reformulates the problem as a convex optimization
متن کاملrodbar dam slope stability analysis using neural networks
در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
Fusion of Topology Preserving Neural Networks
In this paper ensembles of self organizing NNs through fusion are introduced. In these ensembles not the output signals of the base learners are combined, but their architectures are properly merged. Merging algorithms for fusion and boosting-fusion-based ensembles of SOMs, GSOMs and NG networks are presented and positively evaluated on benchmarks from the UCI database.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Russian Journal of Numerical Analysis and Mathematical Modelling
سال: 2019
ISSN: 0927-6467,1569-3988
DOI: 10.1515/rnam-2019-0018