منابع مشابه
Monitoring of Regional Low-Flow Frequency Using Artificial Neural Networks
Ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment Canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (ANNs) are introduced to obtain improved regional low-flow estimates at ungauged sites. A multilayer perceptron (MLP) network is used to identify the funct...
متن کاملSimultaneous Monitoring of Multivariate-Attribute Process Mean and Variability Using Artificial Neural Networks
In some statistical process control applications, the quality of the product is characterized by thecombination of both correlated variable and attributes quality characteristics. In this paper, we propose anovel control scheme based on the combination of two multi-layer perceptron neural networks forsimultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attribu...
متن کاملsimultaneous monitoring of multivariate-attribute process mean and variability using artificial neural networks
in some statistical process control applications, the quality of the product is characterized by thecombination of both correlated variable and attributes quality characteristics. in this paper, we propose anovel control scheme based on the combination of two multi-layer perceptron neural networks forsimultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attribu...
متن کاملmonitoring of regional low-flow frequency using artificial neural networks
ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (anns) are introduced to obtain improved regional low-flow estimates at ungauged sites. a multilayer perceptron (mlp) network is used to identify the funct...
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 ...
ذخیره 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: Journal of Korean Institute of Intelligent Systems
سال: 2005
ISSN: 1976-9172
DOI: 10.5391/jkiis.2005.15.2.264