In most application of the data classifications, the data sets contain both continuous and categorical variables. In other word, multivariate data sets containing mixtures of continuous and categorical variables arise frequently in practice. This paper presents a novel Probability Neural Network (PNN) which can classify the data for both continuous and categorical input data types. The case wit...

In this paper, I propose that the availability of a bound variable reading for pronouns is predictable from their morphological structure of the pronouns. More specifically I argue that noun-containing pronouns cannot be bound variables. My proposal is different from D&W's (2002) argument in that in their theory, every DPs cannot have a bound variable reading, while in my theory, even DPs can h...

Uncertain input parameters may result from "fuzziness", "randomness" or "fuzzy randomness". With the use of fuzzy set theory, uncertain input parameters may be described mathematically as fuzzy variables or fuzzy random variables and may be integrated into safety assessment analysis. With the aid of -discretization involving the multiple solution of special optimization problems, fuzzy input pa...

This paper proposes a probabilistic load flow (PLF) methodology using uniform design sampling (UDS). The correlation between input random variables has been taken into consideration. The random numbers of random variables uniformly distributed in (0,1) are generated by UDS, and subsequently converted into random numbers of input random variables with desired marginal distributions by marginal t...

Friction welding is a solid state bonding technique which utilizes the heat generated by rubbing of two faying surfaces for the coalescence of material. Friction welding process is normally considered as a multi-input and multi-output process. Optimization of friction welding parameters is required to get good quality joints. Present study establishes the relationship between the input variable...

Considering the importance of Cd and U as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the Eshtehard region in Iran by means of a developed artificial neural network (ANN) model. The forward selection (FS) method is used to select the input variables and develop hybrid models by ANN. From 45 input candidates, 13 and 14 ...

Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily C...

The equivalence between autonomicity and the absence of free variables is a well-known result for linear, shift-invariant and complete behaviors over a field. However, this no longer holds for a behavior that does not satisfy one of those properties. In this paper we consider linear, shift-invariant and complete behaviors over the ring Zpr and study under which conditions such behaviors are aut...