the management of machine replacement (specifically tractors) is one of the most critical factors for performing field operations on time. therefore, tractor repair and maintenance costs must be accurately predicted. this research was carried out to evaluate the use of the regression technique in predicting tractor repair and maintenance costs. the study was conducted using empirical data on 60...

This paper presents a relative humidity predictions using feedforward artificial neural network (FFNN). Relative humidity values obtained from weather records for Malaysia are used in training the FFNNs. The prediction of the relative humidity is in terms of Sun shine ration and cloud cover. However, three statistical parameters, namely, mean absolute percentage error, MAPE, mean bias error, MB...

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mini...

The vast use of Linear Prediction Coefficients (LPC) in speech processing systems has intensified the importance of their accurate computation. This paper is concerned with computing LPC coefficients using evolutionary algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Dif-ferential Evolution (DE) and Particle Swarm Optimization with Differentially perturbed Velocity (PSO-DV...

A simple approach was developed to predict corn yields using the MoDerate Resolution Imaging Spectroradiometer (MODIS) data product from two geographically separate major corn crop production regions: Illinois, USA and Heilongjiang, China. The MOD09A1 data, which are eight-day interval surface reflectance data, were obtained from day of the year (DOY) 89 to 337 to calculate the leaf area index ...

In this paper we present a new type of binary classifier defined on the unit cube. This classifier combines some of the aspects of the standard methods that have been used in the logical analysis of data (LAD) and geometric classifiers, with a nearest-neighbor paradigm. We assess the predictive performance of the new classifier in learning from a sample, obtaining generalization error bounds th...

the current study aims to investigate the relationship between stock liquidity risk and financial information quality criteria (i.e. the timely dividends announcement, accruals quality and the percentage of profitability prediction error) of companies listed on the tehran stock exchange. for this purpose, 148 cases of data from listed companies, collected from 2007 to 2012, were employed in ord...

Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...

Objective: Cone beam computed tomography (CBCT) is applied for the imaging of the maxillofacial and dental structures, particularly for surgical treatments and dental implants. The aim of this study was to assess the effect of slice thickness on the accuracy of CBCT linear measurements. Methods: In this diagnostic accuracy study, forty-two titanium pins with the same dimensions were inserted...

PURPOSE To quantify the effect on refractive outcomes after cataract surgery of personalization of Haigis intraocular lens (IOL) constants for a given surgeon-IOL combination. SETTING Institute of Eye Surgery and Institute of Vision Research, Whitfield Clinic, Butlerstown North, Waterford, Ireland. METHODS Personalization of Haigis IOL constants was performed using a series of 248 suitable ...