Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 69 for “"Artificial Neural Networks (ANN)"”.
-
Modeling red pine tree mortality: An artificial neural network approach
… and yield simulation. Multi-layer feed-forward artificial neural networks (ANN) are adopted to achieve the goal. The premise of ANN modeling approach is the ability of such networks to approximate any measurable or continuous function to any desired degree of accuracy, given enough complexity …
-
SNP auto-calling using artificial neural networks
In recent years feedforward artificial neural networks (ANN) and their training algorithms have become an effective methodology for the construction of nonlinear systems that solve the statistical problem of classification. The ability of ANNs to solve this problem is highly germane to making …
-
A Neural Network Receiver for EM-MWD Communication
… <p>This thesis investigates the application of artificial neural networks (ANN) as communication receivers in EM-MWD baseband digital communication systems. The performances of various ANN architectures and training algorithms are studied and compared with conventional correlation receivers via …
-
Porosity distribution prediction using artificial neural networks
… Virginia was selected to conduct this study.;Artificial Neural Networks (ANN) is one of the latest technologies available to the petroleum industry. The objective of this study was to predict reliable porosity values from geophysical log data. In this study, porosity predictions were compared …
-
Application of Neural Network Techniques to Downscale Precipitation
… such as precipitation. This study utilized Artificial Neural Networks (ANN) and Hybrid Support Vector Regression (HSVR) methods to predict precipitation at a finer grid, based on the data from a coarse grid. Precipitation data for three stations (Dhaka, Comilla and Mymesnsingh in Bangladesh) …
-
ANALYZING AND PREDICTING ARMY COMBAT FITNESS TEST PERFORMANCE: A STATISTICAL AND MACHINE LEARNING APPROACH
… Trees (CART), Random Forests (RF), and Artificial Neural Networks (ANN)—to predict ACFT outcomes using raw ACFT scores alongside demographic and body composition data. The analysis evaluates two feature subsets. One subset combines detailed ACFT event scores and body composition data, …
-
Developing neural network applications using LabVIEW
Artificial Neural Networks (ANN) have gained tremendous popularity over the last few decades. They are considered as substitutes for classical techniques which have been followed for many years. Many neural network architectures and training algorithms have been developed so far. Different aspects …
-
Seasonality of circulation in southern Africa using the Kohonen self-organising map
… climatology. The SOM is one of many types of artificial neural networks (ANN) and is capable of unsupervised learning or non-linear classification. Components of the SOM are introduced and an application is then illustrated using observed daily sea level pressure (SLP) from the Australian …
-
Neural architectures for database query processing, syntax analysis, knowledge representation, and inference
<p>Artificial neural networks (ANN), due to their inherent parallelism, potential for fault tolerance, and adaptation through learning, offer an attractive computational paradigm for a variety of applications in computer science and engineering, artificial intelligence, robotics, and cognitive …
-
Uncertainty and sensitivity analysis for long-running computer codes : a critical review
… the use of polynomial Response Surfaces (RS), Artificial Neural Networks (ANN), and Kriging/Gaussian Processes (GP) for metamodeling. Moreover, two methods are discussed for estimating the uncertainty introduced by the metamodel. The first of these methods is based on a bootstrap sampling …
-
Transforming Architectural Practice Through Computational Design and Machine Learning: A Decision-Support Framework for Energy and Daylight Optimization
… climatic conditions. Among the tested models, Artificial Neural Networks (ANN) proved the most effective, excelling in identifying critical design features and uncovering hidden influences among variables such as material properties and glazing systems. The findings demonstrate that machine …
-
An Interactive Learning Framework for Understanding Infrastructure Health Monitoring and Leveraging Machine Learning for Safety Improvement
… crash occurrence and severity patterns. As road networks continue to deteriorate and traffic complexity increases, ensuring roadway safety increasingly depends on integrating advanced predictive modeling capabilities with real-time infrastructure health monitoring systems that can detect …
-
Modelling and simulation of surface roughness obtain from micro milling by using artificial neural network
… In this study by using regression model and Artificial Neural Networks (ANN) which are widely used for both modeling and optimizing the performance of the manufacturing technologies. Optimum machining parameters are of great concern in manufacturing environments, where economy of machining …
-
Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs
… tools like traditional statistical models or Artificial Neural Networks (ANN) are often more applicable.
-
Dynamic load forecasting for commercial power network
… and polynomial based methods as well as artificial neural networks (ANN) approach have been adapted in the load forecasting from 2006 to 2012. The results attained are validated with the real data obtained from the Tenaga Nasional Berhad (TNB) which represents the monthly load electric …
-
Spatial Downscaling and Forecasting of Atmospheric Variables over Complex Terrain Using Machine Learning
… one month lead. This study utilized ML models, Artificial Neural Networks (ANN), Random Forests (RF), and Convolutional Neural Networks (CNN), CNN-based encoder decoder to enhance the spatial resolution of atmospheric variables. The results of downscaling models were intercompared and evaluated …
-
Comparison of Random Forests, Support Vector Machine and Artificial Neural Network Methods for Agriculture Land Cover Classification
… Forests (RF), Support Vector Machines (SVM) and Artificial Neural Networks (ANN) can be applied in land cover classification. However, putting a machine learning categorization system in place is not easy, especially in the field of agricultural land classifications. Very limited research can be …
-
Design and Development of Intelligent Navigation Control Systems for Autonomous Robots that Uses Neural Networks and Fuzzy Logic Techniques and Fpga For Its Implementation
… three robot navigation controllers namely: PID, Artificial Neural Networks (ANN), and Fuzzy Logic (FL), that are used to control the same autonomous mobile robot platform navigating a real unknown indoor environment that contains simple geometric-shaped static objects to reach a goal in an …
-
Internet negotiation patterns and an appraisal of data mining from a managerial perspective : a case study approach
… negotiations: Tree Rule Induction (TRI), Artificial Neural Networks (ANN) and Logistic Regression Analysis (IRA). The results showed that the numbers of offers sent, especially during the early and middle negotiation stages, are positively related to reaching agreements, while sending …
-
Intelligent techniques for dynamic and transient analysis of multi stage desalination plant
… plants. The technique is developed using artificial neural networks (ANN) approach for the purpose of prediction, analysis, modelling, and control of MSF desalination plant. The applicability of the method to predict an approximation of the transient operating conditions as well as the …
Page 1 of 4