This paper examined the efficiency of artificial neural network (ANN) and multivariate linear regression (MLR) models in prediction groundwater quality parameters such as ecological risk index (ERI), pollution load (PLI), metal (MPI), Nemerow (NPI), geoaccumulation (Igeo). 40 samples were collected systematically analyzed for mainly heavy metals. Results revealed that adopting measured is effec...

realizing the difficulties involved in direct measurement of soil properties, in recent years, alternative methods have been employed. in the present research, soil texture, organic carbon, saturation percentage and lime as readily measurable parameters, wilting point, field capacity, cation exchange capacity as well as bulk density, as predicted variables were evaluated. the data set was then ...

The 17β-HSD3 enzyme plays a key role in treatment of prostate cancer and small inhibitorscan be used to efficiently target it. In the present study, the multiple linear regression (MLR),and support vector machine (SVM) methods were used to interpret the chemical structuralfunctionality against the inhibition activity of some 17β-HSD3inhibitors. Chemical structuralinformation were described thro...

The 17β-HSD3 enzyme plays a key role in treatment of prostate cancer and small inhibitorscan be used to efficiently target it. In the present study, the multiple linear regression (MLR),and support vector machine (SVM) methods were used to interpret the chemical structuralfunctionality against the inhibition activity of some 17β-HSD3inhibitors. Chemical structuralinformation were described thro...

Structural design of ships and offshore structures has been moving towards limit state design or reliability-based design. Improving the accuracy and efficiency of predicting ultimate strength of structural components, such as unstiffened panels and stiffened panels, has significant impact on our daily structural design. Empirical formulations have been widely used because of its simplicity and...

Background: The complexity of the fermentation processes is mainly due to the complex nature of the biological systems which follow the life in a non-linear manner. Joined performance of artificial neural network (ANN) and genetic algorithm (GA) in finding optimal solutions in experimentation has found to be superior compared to the statistical methods. Range of applications of β-cyclodextrin (...

The credit scoring aim is to classify the customer credit as defaulter or non-defaulter. The credit risk analysis is more effective with further boosting and smoothing of the parameters of models. The objective of this paper is to explore the credit score classification models with an imputation technique and without imputation technique. However, data availability is low in case of without imp...

BACKGROUND & AIMS Hepatitis B surface antigen (HBsAg) seroclearance and seroconversion are regarded as favorable outcomes of chronic hepatitis B (CHB). This study aimed to develop artificial neural networks (ANNs) that could accurately predict HBsAg seroclearance or seroconversion on the basis of available serum variables. METHODS Data from 203 untreated, HBeAg-negative CHB patients with spon...

Official statistics on monthly export values have a publicity lag between the current period and published publication. None of previous researchers estimated value exports for period. This circumstance is due to limitations in obtaining supporting data that can predict criteria goods. AIS one type big provide solutions producing latest indicators forecast values. Statistical Methods Convention...