Browsing by Subject "Artificial neural networks"
Now showing items 1-13 of 13
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A Study on Evaporative Cooling for data centers & Artificial Neural Network Modeling
(2015-12-07)This study mainly aims at exploring how, one of the best “Green” solutions for IT equipment cooling aka Evaporative Cooling, can be optimized for better future deployment. Also, this study focuses on ways to deploy Artificial ... -
A TWO STAGE EVENT BASED DATA DRIVEN CONTROLLER FOR IMPROVED GRASPING OF AN ARTIFICIAL HAND
(2019-07-09)The human hand is one of the greatest (if not the greatest) tool known to mankind for grasping objects. So much so, that researchers have been investigating the development of artificial biomimetic hands in an effort to ... -
APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR EVAPORATIVE COOLING IN DATA CENTRES
(2017-01-17)A data center is a facility that may be used to house telecommunication or storage devices. Because of the 24/7 required operation of a data center, large segments of a data center are geared towards evacuating heat generated ... -
Assessing the impact of Principal Component Analysis on accurately predicting melanoma diagnosis applied on different classification models
(2019-11-26)With huge amounts of data at our disposal in the medical field, mathematical models are built to diagnose diseases. This study focuses on melanoma because it’s the type of skin cancer that accounts for most deaths, up to ... -
Comprehensive neural network forecasting system for ground level ozone in multiple regions
(2015-12-07)A comprehensive neural network daily maximum 8 hour-ozone forecasting model was developed based on five years of data (2010-2014) collected from 50 monitoring sites from the Dallas Fort Worth, Houston-Galveston-Brazoria, ... -
COMPUTATIONAL FLUID DYNAMICS SIMULATION-BASED ARTIFICIAL NEURAL NETWORK MODELLING FOR DATA CENTER COOLING PREDICTION
(2018-05-22)Continuous provision of quality supply air to data center’s IT pod room is key parameter in assuring effective data center operation without any down time. Due to number of possible operating conditions and non-linear ... -
CONTROL STRATEGIES FOR AIR-SIDE ECONOMIZATION, DIRECT AND INDIRECT EVAPORATIVE COOLING AND ARTIFICIAL NEURAL NETWORKS APPLICATIONS FOR ENERGY EFFICIENT DATA CENTERS
(2016-05-12)The skyrocketing growth in data centers, facilities that house information technology (IT) equipment for storage, management and distribution of data while striving for 24/7/365 operation with 100% up-time, has accounted ... -
DEVELOPMENT AND APPLICATIONS OF A MULTI-FUNCTIONAL POSITRON BEAM FOR SPECTROSCOPIES OF SURFACES AND INTERFACES
(2019-09-03)This dissertation describes the construction of a multi-functional positron beam and the methods employed for the analysis of digitized data produced by electron time-of-flight and gamma spectrometers. The positron beam ... -
Improving Probabilistic Quantitative Precipitation Forecasting Using Machine Learning and Statistical Postprocessing Methods
(2021-12-09)The objective of this research is to address the limitations inherent in conventional statistical postprocessing schemes to generate probabilistic quantitative precipitation forecasts (PQPFs) and improve postprocessed ... -
IMPROVING REGIONAL HYDROLOGY FORECASTING FOR THE NORTH CENTRAL TEXAS REGION UTILIZING CONDITIONAL ENSEMBLE STREAMFLOW AND HYDROMETEOROLOGICAL CONDITION PREDICTIONS WITH ARTIFICIAL NEURAL NETWORK MODELING
(2017-05-10)The predictive skill of hydrologic variables such as streamflow and soil moisture, in North Central Texas, has improved substantially in the recent decades. However, substantial model-data biases are still present during ... -
Learning Representations Using Reinforcement Learning
(2019-05-09)The framework of reinforcement learning is a powerful suite of algorithms that can learn generalized solutions to complex decision making problems. However, the applications of reinforcement learning algorithms to traditional ... -
Neural Network Modeling and Control of Data Center
(2015-12-09)Data Center has become a definitive element of Modern IT infrastructure. With the development of high performance computing architectures and equipment, data centers consume large amount of electricity. Due to low ... -
On the Development and Integration of Pneumatic Extrusion Module and a Methodology to Identify Process Parameters for Additive Manufacturing using Machine Learning
(2018-05-09)Commonly used additive manufacturing platforms have a single extrusion module based on Fused Filament Fabrication (FFF) and their processing software generates G-Codes for this FFF module using defined process parameters. ...