Background: Human brucellosis is widespread in Fars province. The present study aimed to investigate the effect of climate on its incidence and determine the areas prone to the infection.Methods: Monthly meteorological data and the incidence rate of human brucellosis during 2009-2015 were collected and their correlation was studied using Pearson’s correlation coefficient. Additionally, th...

A Kalman-Filtered Feature-space approach is taken to forecast changes in the ISEQ (Irish Stock Exchange Equity Overall) Index using the previous five days' lagged returns solely as inputs. The resulting model is tantamount to a time-varying (adaptive) technical trading rule, one which achieves an out-of-sample Sharpe ('reward-to-variability') Ratio far superior to the 'buy-and-hold' strategy an...

This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensembl...

We compared the performance of several supervised classification algorithms on multi-source remotely sensed images. Apart from the Multi-Layer Perceptron, K-Nearest-Neighbour and Radial Basis Function network approaches, we looked more in detail at the Support Vector Machine classifier, which recently showed promising results in our setting. In particular, it is able to provide meaningful answe...

Respiratory auscultation is a fundamental tool in assessing the physiological state of a patient. Second opinions are regularly sought by medical practitioners which allows for a framework of reasoning between different hypotheses in establishing a final diagnosis. Here we assess two such reasoning mechanisms: a novel, structured approach of serially propagating knowledge from a Fuzzy C-Means (...

estimating of forest equipment productivity is an important aspect of managing cost in forestry, which leads to reduction of operations expenses. in other words, high capital cost in forest harvesting, is a good reason to argue forest engineering research and time modeling. this paper applied one of the artificial intelligence subsets, which are called artificial neural networks (anns), to pred...

Water policies have evolved enormously since the Rio Earth Summit (1992). These changes have led to the strategic importance of Water Demand Management. The aim is to provide water where and when it is required using the fewest resources. A key variable in this process is the demand forecasting. It is not sufficient to have long term forecasts, but the current context requires the continuous av...

In this paper, the grouting ability of sandy soils is investigated by artificial neural networks based on the results of chemical grout injection tests. In order to evaluate the soil grouting potential, experimental samples were prepared and then injected. The sand samples with three different particle sizes (medium, fine, and silty) and three relative densities (%30, %50, and %90) were injecte...

Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibility of unlearning past experiences. Moreover, since the target values in the training examples are bootstraps values, this is, estimates of other estimates, the chances to get stuck in a local minimum are increased. The...

Learning controllers based on dynamic programming require some means of storing arbitrary functions and finding global minima within cross sections of those functions. There are many general methods for learning and representing functions, including polynomials, multi-layer perceptrons with backpropagation, and radial basis functions, but these systems do not allow the minima to be found easily...