Sharif Digital Repository

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α-cuts. Then, we propose a regression model for obtaining membership function for the considered addition. Finally, we present a dynamic programming method for finding a shortest path in the network. An example is worked out to illustrate the applicability of the proposed approach  

A quantitative structure-property relationship study based on multiple linear regression (MLR) and artificial neural network (ANN) techniques was carried out to investigate the retention behavior of some terpenes on the polar stationary phase (Carbowax 20 M). A collection of 53 noncyclic and monocyclic terpenes was chosen as data set that was randomly divided into two groups, a training set and a prediction set consist of 41 and 12 molecules, respectively. A total of six descriptors appearing in the MLR model consist of one electronic, two geometric, two topological and one physicochemical descriptors. Except for the geometric parameters the remaining descriptors have a pronounced effect on... 

Empirical mode decomposition as a complete data driven method is typically employed to obtain constitutive components of all kinds of signal including non-stationary and nonlinear. Extracting modes using this method is normally associated with multiple sources of errors such as stop criteria, end effects, interpolation function and etc. In order to reduce end effects errors in this paper a modified method is proposed based on combination of auto regressive model and mirror method. In this combination method, to extract some of first intrinsic mode functions of a given signal, auto regressive model is initially implemented to forecast tails of maximum and minimum envelops for only a short... 

Although it is known that synonymous codons are not chosen randomly, the role of the codon usage in gene regulation is not clearly understood, yet. Researchers have investigated the relation between the codon usage and various properties, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Recently, a universal codon usage based mechanism for gene regulation is proposed. We studied the role of protein sequence patterns on the codons usage by related genes. Considering a subsequence of a protein that matches to a pattern or motif, we showed that, parts of the genes, which are translated to this subsequence, use specific ratios of... 

We propose an approach for computing the product of various fuzzy numbers using a-cuts. A regression model is used to obtain the membership function of the product. Then, we make use of the approach to compute solutions of fully fuzzy linear systems. We also show how to compute solutions of fully fuzzy linear systems with various fuzzy variables. Examples are worked out to illustrate the approach. Copyright © 2018 Inderscience Enterprises Ltd  

For a set of 846 organic compounds, relevant in forensic analytical chemistry, with highly diverse chemical structures, the gas chromatographic Kovats retention indices have been quantitatively modeled by using a large set of molecular descriptors generated by software Dragon. Best and very similar performances for prediction have been obtained by a partial least squares regression (PLS) model using all considered 529 descriptors, and a multiple linear regression (MLR) model using only 15 descriptors obtained by a stepwise feature selection. The standard deviations of the prediction errors (SEP), were estimated in four experiments with differently distributed training and prediction sets.... 

Artificial neural networks (ANNs) were successfully developed for the modeling and prediction of electrophoretic mobility of a series of sulfonamides in capillary zone electrophoresis. The cross-validation method was used to evaluate the prediction ability of the generated networks. The mobility of sulfonamides as positively charged species at low pH and negatively charged species at high pH was investigated. The results obtained using neural networks were compared with the experimental values as well as with those obtained using the multiple linear regression (MLR) technique. Comparison of the results shows the superiority of the neural network models over the regression models. © 2001... 

The reinforcement of concrete columns with fabric reinforced cementitious matrix (FRCM) is one of the most challenging issues in the construction of concrete structures, as there is still an absence of a promising model to assess their performance. This is because the behavior of such elements is complex and accompanied by a high margin of uncertainty. To address this issue, this study compiles a large dataset of the performance of FRCM-reinforced concrete columns under monotonic load. The obtained dataset is then used to train an artificial neural network (ANN) as a promising method for predicting the compressive strength of concrete columns with acceptable accuracy. Afterward, using a... 

The main aim of the present work was the development of a quantitative structure-activity relationship method using an artificial neural network (ANN) for predicting the thermal conductivity detector response factor. As a first step a multiple linear regression (MLR) model was developed and the descriptors appearing in this model were considered as inputs for the ANN. The descriptors of molecular mass, number of vibrational modes of the molecule, molecular surface area and Balaban index appeared in the MLR model. In agreement with the molecular diameter approach, molecular mass and molecular surface area play a major role in estimating the thermal conductivity detector response factor... 

We are concerned with the design of a model and an algorithm for computing the shortest path in a network having various types of fuzzy arc lengths. First, a new technique is devised for the addition of various fuzzy numbers in a path using α-cuts by proposing a least squares model to obtain membership functions for the considered additions. Due to the complexity of the addition of various fuzzy numbers for larger problems, a genetic algorithm is presented for finding the shortest path in the network. For this, we apply a recently proposed distance function for comparison of fuzzy numbers. Examples are worked out to illustrate the applicability of the proposed approach  

Autoregressive models are among the most successful neural network methods for estimating a distribution from a set of samples. However, these models, such as other neural methods, need large data sets to provide good estimations. We believe that knowing structural information about the data can improve their performance on small data sets. Masked autoencoder for distribution estimation (MADE) is a well-structured density estimator, which alters a simple autoencoder by setting a set of masks on its connections to satisfy the autoregressive condition. Nevertheless, this model does not benefit from extra information that we might know about the structure of the data. This information can... 

In recent years, much attention has been given to monitoring multistage processes in order to effectively improve the product reliability. To this end, the output of the process is investigated under special circumstances, and the values corresponding to reliability-related quality characteristic are measured. However, analyzing reliability data is quite complicated because of their unique features such as being censored and obeying nonnormal distributions. A more sophisticated picture arises when the observations of the process are autocorrelated in some cases, which makes the application of previous control procedures futile. In this paper, the accelerated failure time (AFT) regression... 

We investigate the resistance of reinforced concrete panels (RCPs) due to explosive loading using nonlinear finite element analysis and surrogate models. Therefore, gene expression programming model (GEP), multiple linear regression (MLR), multiple Ln equation regression (MLnER), and their combination are used to predict the maximum deflection of RCPs. The maximum positive and negative errors, mean of absolute percentage error (MAPE), and statistical parameters such as the coefficient of determination, root mean square error (RMSE). Normalized square error (NMSE), and fractional bias are utilized to evaluate and compare the performance of the models. We also present a novel statistical table... 

It is proved that the endothelial (artery inner lumen cells) function is associated with cardiovascular risk factors. Among all the common non-invasive methods employed in the research setting for assessing endothelial function, flow-mediated dilation is the most widely used one. This technique measures endothelial function by inducing reactive hyperemia using temporary arterial occlusion and measuring the resultant relative increase in blood vessel diameter via ultrasound. In this paper, the limitations associated with the ultrasound technique are overcome by using the photoplethysmogram (PPG) signal recorded during FMD. The correctness of this approach is investigated by modeling the AC...