Results 71 to 80 of about 2,398,960 (400)

Neural network learning dynamics in a path integral framework [PDF]

Eur.Phys.J.B15, 679 (2000), 2003
A path-integral formalism is proposed for studying the dynamical evolution in time of patterns in an artificial neural network in the presence of noise. An effective cost function is constructed which determines the unique global minimum of the neural network system.
arxiv   +1 more source

Development of neural network model of disc brake operation [PDF]

FME Transactions, 2010
The quality of artificial neural network models mostly depends on a proper setting of neural network architecture i.e. learning algorithm, transfer functions, range and distribution of data used for training, validation, and testing, etc.
Ćirović Velimir, Aleksendrić Dragan
doaj  

Applications of artificial neural networks for enhanced livestock productivity: A review

Indian Journal of Animal Sciences, 2016
Artificial neural network models are machine-learning systems, a type of artificial intelligence. They have been inspired by and developed along the working principles of the human brain and its nerve cells.
V B DONGRE, R S GANDHI
doaj   +1 more source

A comparative analysis of artificial neural network architectures for building energy consumption forecasting

Int. J. Distributed Sens. Networks, 2019
Smart grids have recently attracted increasing attention because of their reliability, flexibility, sustainability, and efficiency. A typical smart grid consists of diverse components such as smart meters, energy management systems, energy storage ...
Jihoon Moon, Sungwoo Park, Seungmin Rho, Eenjun Hwang   +3 more
semanticscholar   +1 more source

Evaluation of AI‐based auto‐contouring tools in radiotherapy: A single‐institution study

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Accurate delineation of organs at risk (OARs) is crucial yet time‐consuming in the radiotherapy treatment planning workflow. Modern artificial intelligence (AI) technologies had made automation of OAR contouring feasible. This report details a single institution's experience in evaluating two commercial auto‐contouring software ...
Tingyu Wang, James Tam, Thomas Chum, Cyril Tai, Deborah C. Marshall, Michael Buckstein, Jerry Liu, Sheryl Green, Robert D. Stewart, Tian Liu, Ming Chao   +10 more
wiley   +1 more source

Demand forecasting in a Supply Chain using Machine Learning Algorithms [PDF]

مجله مدل سازی در مهندسی, 2015
—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models.
Mohsen Shafiei Nikabadi, Mohsen Shafiei Nikabadi, Ali Azimi   +2 more
doaj   +1 more source

Diabetes Prediction Using Artificial Neural Network [PDF]

, 2018
Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method
Abu-Naser, Samy S., El_Jerjawi, Nesreen Samer   +1 more
core   +3 more sources

The Effect of the Normalization Method Used in Different Sample Sizes on the Success of Artificial Neural Network Model

International Journal of Assessment Tools in Education, 2019
In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes.
G. Aksu, C. Güzeller, M. Eser
semanticscholar   +1 more source

Enhanced dose prediction for head and neck cancer artificial intelligence‐driven radiotherapy based on transfer learning with limited training data

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Training deep learning dose prediction models for the latest cutting‐edge radiotherapy techniques, such as AI‐based nodal radiotherapy (AINRT) and Daily Adaptive AI‐based nodal radiotherapy (DA‐AINRT), is challenging due to limited data.
Hui‐Ju Wang, Austen Maniscalco, David Sher, Mu‐Han Lin, Steve Jiang, Dan Nguyen   +5 more
wiley   +1 more source

An approach based on gamma-ray transmission technique and artificial neural network for accurately measuring the thickness of various materials [PDF]

Nuclear Technology and Radiation Protection
This paper presents an approach based on the gamma-ray transmission technique and artificial neural network for accurately measuring the thickness of various materials in flat sheet form.
Trang Le Thi Ngoc, Linh Nguyen Thi Truc, Thanh Tran Thien, Tam Hoang Duc, Chuong Huynh Dinh   +4 more
doaj   +1 more source