Results 21 to 30 of about 254,846 (297)

Egg hatchability prediction by multiple linear regression and artificial neural networks

Brazilian Journal of Poultry Science, 2008
An artificial neural network (ANN) was compared with a multiple linear regression statistical method to predict hatchability in an artificial incubation process. A feedforward neural network architecture was applied.
AC Bolzan, RAF Machado, JCZ Piaia
doaj   +1 more source

Designing short term trading systems with artificial neural networks [PDF]

, 2009
There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-
A. Elder, D. Guppy, J. Sweeney, V. K. Tharp   +3 more
core   +1 more source

Neural Network Characterization of Reflectarray Antennas [PDF]

, 2012
An efficient artificial neural network (ANN) approach for the modeling of reflectarray elementary components is introduced to improve the numerical efficiency of the different phases of the antenna design and optimization procedure, without loss in ...
Freni, A., Mussetta, Marco, Pirinoli, Paola   +2 more
core   +4 more sources

The Use of Graph Databases for Artificial Neural Networks

Journal of Advanced Research in Natural and Applied Sciences, 2021
Storing and using trained artificial neural network (ANN) models face technical difficulties. These models are usually stored as files and cannot be run directly. An artificial neural network can be structurally expressed as a graph.
Ahmet Cumhur Kınacı, Doğa Barış Özdemir   +1 more
doaj   +1 more source

Kendali Aliran dan Tekanan Adaptif dengan Metode Artificial Neural Network pada Alat Terapi Oksigen

Jurnal Elkomika
ABSTRAK Penelitian ini bertujuan untuk merancang prototype pengendalian aliran dan tekanan adaptif pada alat terapi oksigen. Sensor yang digunakan yaitu sensor MAX30100 untuk membaca saturasi oksigen dan sensor MLX90614 sebagi sensor yang dapat ...
ABYANUDDIN SALAM, NUR WISMA NUGRAHA, WILDAN ALFARIDHANI   +2 more
doaj   +1 more source

Artificial Neural Network (ANN) to Predict Mathematics Students’ Performance

Journal of Computing Research and Innovation, 2022
Predicting students’ academic performance is very essential to produce high-quality students. The main goal is to continuously help students to increase their ability in the learning process and to help educators as well in improving their teaching skills. Therefore, this study was conducted to predict mathematics students’ performance using Artificial
Norpah Mahat, Nor Idayunie Nording, Jasmani Bidin, Suzanawati Abu Hasan, Teoh Yeong Kin   +4 more
openaire   +3 more sources

Chaos Game Optimization-Hybridized Artificial Neural Network for Predicting Blast-Induced Ground Vibration

Applied Sciences
In this study, we introduced the chaos game optimization-artificial neural network (CGO-ANN) model as a novel approach for predicting peak particle velocity (PPV) induced by mine blasting.
Shugang Zhao, Liguan Wang, Mingyu Cao
doaj   +1 more source

State-of-the-art in artificial neural network applications: A survey

Heliyon, 2018
This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and area of focus ...
Oludare Isaac Abiodun, Aman Jantan, Abiodun Esther Omolara, Kemi Victoria Dada, Nachaat AbdElatif Mohamed, Humaira Arshad   +5 more
doaj   +1 more source

An artificial neural network (ANN) as solute geothermometer

, 2021
The application of geothermometry has been used for the last six decades for geothermal reservoir temperature estimation. A steady evolution of conventional geothermometers to multicomponent tools as well as application of artificial intelligence are nowadays available.
Ystroem, Lars, Vollmer, Mark, Nitschke, Fabian, Kohl, Thomas   +3 more
openaire   +3 more sources

Solar desalination system for fresh water production performance estimation in net-zero energy consumption building: A comparative study on various machine learning models

Water Science and Technology
This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as ...
Ali Hussain Alhamami, Emmanuel Falude, Ahmed Osman Ibrahim, Yakubu Aminu Dodo, Okpakhalu Livingston Daniel, Farruh Atamurotov   +5 more
doaj   +1 more source