Terrain classification in SAR images using principal components analysis and neural networks

Terrain classification in SAR images using principal components analysis and neural networks

rodbar 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 ...

Classification of Polarimetric SAR Images Using Evolutionary RBF Neural Networks

This paper proposes an evolutionary RBF network classifier for polarimetric synthetic aperture radar ( SAR) images. The proposed feature extraction process utilizes the full covariance matrix, the gray level co-occurrence matrix (GLCM) based texture features, and the backscattering power (Span) combined with the H/α /A decomposition, which are projected onto a lower dimensional feature space us...

Classification of Multi-spectral, Multi-temporal and Multi-sensor Images Using Principal Components Analysis and Artificial Neural Networks: Beykoz Case

The thematic maps derived from remotely-sensed images are invaluable sources of information for various investigations since they provide spatial and temporal information about the nature of Earth surface materials and objects. The robustness of classification techniques used to produce these thematic maps can be crucial especially for complex classification problems. This study aims to determi...

Automated Classification of Stellar Spectra. II: Two-Dimensional Classification with Neural Networks and Principal Components Analysis

We investigate the application of neural networks to the automation of MK spectral classification. The data set for this project consists of a set of over 5000 optical (3800–5200Å) spectra obtained from objective prism plates from the Michigan Spectral Survey. These spectra, along with their two-dimensional MK classifications listed in the Michigan Henry Draper Catalogue, were used to develop s...