Path loss prediction in urban environment using learning machines and dimensionality reduction techniques
نویسندگان
چکیده
منابع مشابه
Path loss prediction in urban environment using learning machines and dimensionality reduction techniques
Path loss prediction is a crucial task for the planning of networks inmodern mobile communication systems. Learning machine-based models seem to be a valid alternative to empirical and deterministic methods for predicting the propagation path loss.As learningmachine performance depends on the number of input features, a good way to get a more reliable model can be to use techniques for reducing...
متن کاملLearning omnidirectional path following using dimensionality reduction
We consider the task of omnidirectional path following for a quadruped robot: moving a four-legged robot along any arbitrary path while turning in any arbitrary manner. Learning a controller capable of such motion requires learning the parameters of a very high-dimensional policy class, which requires a prohibitively large amount of data to be collected on the real robot. Although learning such...
متن کاملDrug-target interaction prediction using ensemble learning and dimensionality reduction.
Experimental prediction of drug-target interactions is expensive, time-consuming and tedious. Fortunately, computational methods help narrow down the search space for interaction candidates to be further examined via wet-lab techniques. Nowadays, the number of attributes/features for drugs and targets, as well as the amount of their interactions, are increasing, making these computational metho...
متن کامل2D Dimensionality Reduction Methods without Loss
In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (...
متن کاملImage Reduction Using Assorted Dimensionality Reduction Techniques
Dimensionality reduction is the mapping of data from a high dimensional space to a lower dimension space such that the result obtained by analyzing the reduced dataset is a good approximation to the result obtained by analyzing the original data set. There are several dimensionality reduction approaches which include Random Projections, Principal Component Analysis, the Variance approach, LSA-T...
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: Computational Management Science
سال: 2010
ISSN: 1619-697X,1619-6988
DOI: 10.1007/s10287-010-0121-8