A NEURAL-NETWORK ANALYZER FOR MORTALITY FORECAST

Artificial neural network forecast application for fine particulate matter concentration using meteorological data

Most parts of the urban areas are faced with the problem of floating fine particulate matter. Therefore, it is crucial to estimate the amounts of fine particulate matter concentrations through the urban atmosphere. In this research, an artificial neural network technique was utilized to model the PM2.5 dispersion in Tehran City. Factors which are influencing the predicted value consi...

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

Low-cost Vector Network Analyzer for Biomedical Applications

A low-cost and portable vector network analyzer (VNA) which covered operating frequency between 1MHz to 3GHz is used for vector reflection coefficient and standing wave ratio (swr) of the various microstrip antennas. This paper presents measurements of various ultra wideband (uwb) microstrip antennas for applications in biomedical field. Selection of antenna is an important key for detection of...

A rainfall forecast model using Artificial Neural Network

An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S. Weesakul, and N. K. Tripathi School of Engineering and Technology, Asian Institute of Technology, Thailand Received: 14 December 2007 – Accepted: 17 December 2007 – Published: 30 January 2008 Correspondence to: N. Q. Hung ([email protected]) Published by Copernicus Publications ...

A Radon-based Convolutional Neural Network for Medical Image Retrieval

Image classification and retrieval systems have gained more attention because of easier access to high-tech medical imaging. However, the lack of availability of large-scaled balanced labelled data in medicine is still a challenge. Simplicity, practicality, efficiency, and effectiveness are the main targets in medical domain. To achieve these goals, Radon transformation, which is a well-known t...