Abstract: This study develops an Artificial Neural Network (ANN)-based prediction model to estimate the total project cost (TPC) of residential dwellings in Quezon City, the largest local government ...
An evnet driven model that uses financial time series data with New York Times information to form a LSTM recurrent neural network. There are 3 models. The first 2 models are based on price and volume ...
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...
Department of Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States Department of Chemistry, Carnegie Mellon University, 5000 ...
Abstract: The underwater sound speed profile (SSP), that describing the distribution of sound speed, is an important parameter of underwater communication positioning, navigation and timing system due ...
A high-performance neural network implementation written in Rust from scratch. This project demonstrates building AI/ML components in Rust for superior speed and memory safety compared to traditional ...
This study investigates the mechanical performance of Steel Fibre-Reinforced Concrete (SFRC) subjected to elevated temperatures using artificial neural network (ANN) modeling. While existing ...
Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...
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