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Keyword: Neural networkHardware Acceleration on Cloud Services: The use of Restricted Boltzmann Machines on Handwritten Digits Recognition
Cloud computing allows users and enterprises to process their data in high performance servers, thus reducing the need for advanced hardware at the client side. Although local processing is viable in many cases, collecting data from multiple clients and processing them in a server gives the best possible performance in terms of processing rate. In…
Read MoreAnalysis of Wireless Traffic Data through Machine Learning
The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data…
Read MoreMedical imbalanced data classification
In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine…
Read MoreEvaluation of Three Evaporation Estimation Techniques In A Semi-Arid Region (Omar El Mukhtar Reservoir Sluge, Libya- As a case Study)
In many semi-arid countries in the world like Libya, drinking water supply is dependent on reservoirs water storage. Since the evaporation rate is very high in semi-arid countries, estimates and forecasts of reservoir evaporation rate can be useful in the management of major water source. Many researchers have been investigating the suitability of estimates evaporation…
Read MoreRecent Trends in ELM and MLELM: A review
Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer feed forward neural networks. Compared with the existing neural network learning algorithm it solves the slow training speed and over-fitting problems. It has been used in different fields and applications such as biomedical engineering, computer vision, remote sensing, chemical process…
Read MoreAdaptive Intelligent Systems applied to two-wheeled robot and the effect of different terrains on performance
This work discuss two different intelligent controllers: Online Neuro Fuzzy Controller (ONFC) and Proportional-Integral-Derivative Neural Network (PID-NN). They were applied to maintain the equilibrium and to control the position of a two-wheeled robot prototype. Experiments were carried out to investigate the equilibrium control and movement of the two-wheeled robot first on flat terrain, then in…
Read MoreAn Application of ANN Model with Bayesian Regularization Learning Algorithm for Computing the Operating Frequency of C-Shaped Patch Antennas
In this paper, an application of artificial neural network (ANN) using bayesian regularization (BR) learning algorithm based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped patch antennas (CPAs) in UHF band. Firstly, the operating frequencies of 144 CPAs having varied dimensions and electrical parameters were simulated by the XFDTD…
Read MoreFuzzy-logical Control Models of Nonlinear Dynamic Objects
The article considers the task of developing a fuzzy-logical PID-type controller for a nonlinear dynamic system. A feature of the structure is presented, which consists in simplifying its controller by decomposition. In the simplest version, three fuzzy controllers are used with one input and one output and separate rule bases. Parameters of fuzzy controllers are…
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