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[DOC File]THE NEURAL-NETWORK ANALYSIS
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1. Introduction to neural networks. 1.1 What is a Neural Network? An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system.
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[DOC File]Michael Cash - University of Wisconsin–Madison
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Michael Cash. 12/19/03. ECE 539: Introduction to Artificial Neural Networks and Fuzzy Systems. Semester Project. Professor Y. H. Hu Background: The current status and past trends of waterfowl populations are annually studied to estimate abundance, location, and species composition of ducks and geese throughout the country.
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[DOC File]Ethical Considerations When Implementing Advanced …
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Theory and Background. Advanced Technologies. Expert systems, fuzzy logic and artificial neural networks are classified as "artificial intelligence" technologies. Each of these is a component of intelligent systems.
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[DOC File]An artificial neural network (ANN), often just called a ...
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This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained.
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[DOC File]Detecting Smoke from Boreal Forest Fires using Neural ...
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Both artificial neural networks (NN) and multi-threshold techniques were explored for application with imagery from the Advanced Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. The NN was designed such that it does not only classify a scene into smoke, cloud, or clear background land, but also generates continuous outputs ...
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[DOC File]MIT - Massachusetts Institute of Technology
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The following section presents background information on WinBank and neural networks, and is followed by a discussion of the procedures used to test the different types of neural networks considered. This procedural information is followed by an explanation the different parameters (and their associated values) used for creating and training ...
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[DOC File]Abstract:
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This paper compares the performance of machine learning models based on fuzzy rules (FR), fuzzy decision trees (FDT), artificial neural networks (aNN) and logistic regression (LR) and examines how these models behave in the face of noisy and variant data. Results suggest that FDT models may be more resistant to data noise. Background
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[DOC File]NEURAL NETWORKS
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This report is an introduction to Artificial Neural Networks. The different types of neural networks are explained and shown, applications of neural networks like ANNs in medicine are described, and historical background is provided. The connection between the artificial …
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[DOC File]LECTURE #9: FUZZY LOGIC & NEURAL NETS
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1.4 Artificial neural networks. An artificial neural network is a collection of connected McCulloch-Pitts neurons. Neural networks can formally represent almost any functional map provided that: (1) A proper number of basic neurons are appropriately connected (2) Appropriate weights are selected
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[DOC File]The Use of Artificial Neuronal Networks to Generate
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“An artificial neural network (ANN) … is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. An ANN consists of an interconnected group of artificial neurons and processes information using …
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Artificial neural networks background