In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sarimsakli and Sosun streams in Turkey. The accuracy of the applied models was compared with the multiple-linear regression (MLR). The results showed t...

A linear quantitative structure-activity relationship (QSAR) model is presented for modeling and predicting induction of apoptosis by 4-aryl-4H-chromenes. The model was produced by using the multiple linear regression (MLR) technique on a database that consists of 43 recently discovered 4-aryl-4H-chromenes. Among the 61 different physicochemical, topological, and structural descriptors that wer...

Models for the prediction of conductance in nonbrine water samples through the measurement of ionic concentrations and other parameters are compared. Such predictions are often used for quality assurance purposes by comparing them with actual measurements to determine whether gross analysis errors have been made. A currently recommended method for making such predictions is a semiempirical rela...

one of the most important aspects of software project management is the estimation of cost and time required for running information system. therefore, software managers try to carry estimation based on behavior, properties, and project restrictions. software cost estimation refers to the process of development requirement prediction of software system. various kinds of effort estimation patter...

Quantitative structure–activity relationship (QSAR) models were developed to predict for CCR5 binding affinity of substituted 1-(3, 3-diphenylpropyl)-piperidinyl amides and ureas using multiple linear regression (MLR) and artificial neural network (ANN) techniques. A model with four descriptors, including Hydrogen-bonding donors HBD(R7), the partition coefficient between n-octanol and water log...

OBJECTIVE Multiple linear regression (MLR) and machine learning techniques in pharmacogenetic algorithm-based warfarin dosing have been reported. However, performances of these algorithms in racially diverse group have never been objectively evaluated and compared. In this literature-based study, we compared the performances of eight machine learning techniques with those of MLR in a large, rac...

One of the essential sectors of Myanmar economy is agriculture which is sensitive to climate variation. The most important climatic element which impacts on agriculture sector is rainfall. Thus rainfall prediction becomes an important issue in agriculture country. Multi variables polynomial regression (MPR) provides an effective way to describe complex nonlinear input output relationships so th...

Support vector regression (SVR) is used in this study to develop models to estimate apparent metabolizable energy (AME), AME corrected for nitrogen (AMEn), true metabolizable energy (TME), and TME corrected for nitrogen (TMEn) contents of corn fed to ducks based on its chemical composition. Performance of the SVR models was assessed by comparing their results with those of artificial neural net...