Classification is one of the key issues in the fields of decision sciences and knowledge discovery. This paper presents a new approach for constructing a classifier, based on an extended association rule mining technique in the context of classification. The characteristic of this approach is threefold: first, applying the information gain measure to the generation of candidate itemsets; second...

In this paper we propose a framework for estimation and quality control of conditional neural network volatility models for market risk management. In a first step, we derive a conditional volatility model based on gaussian mixture densities, that can be used with linear or neural regression models (extendable even to rule systems or decision trees). In a second step, we introduce performance m...

land cover information is one of the most important prerequisite in urban management system. in this way remote sensing, as the most economic technology, is mainly used to produce land cover maps. considering the complicated and dense urban areas in third world countries, object based approaches are suggested as an effective image processing technique. the purpose of this paper are the introduc...

In this communication, a thermodynamic model is presented to predict the dissociation conditions of structure H (sH) clathrate hydrates with methane as help gas. This approach is an extension of the Klauda and Sandler fugacity model (2000) for prediction of phase boundaries of sI and sII clathrate hydrates. The phase behavior of the water and hydrocarbon system is modeled using the Peng-Robinso...

dara' rule changes in islamic penal code with the modern penology teachings approach keyvan heidar nejad [1] fatemeh ahadi [2] seyyed abulfazl mirjafar pour [3]   abstract:                        dara' is one of the rules that is derived from figh. the rule indicates that by proving doubt or hesitancy at the time of committing crime, the offence cannot be proved. in the former penal c...

We consider the model: Y = X+ , where X and are independent random variables. The density of is known whereas the one of X is a finite mixture with unknown components. Considering the ”ordinary smooth case” on the density of , we want to estimate a component of this mixture. To reach this goal, we develop two wavelet estimators: a nonadaptive based on a projection and an adaptive based on a har...

We present a neural-network approach which allows sequential extraction of source signals from a linear mixture of multiple sources in the order determined by absolute values of normalized kurtosis. To achieve this, we develop a non-linear Hebbian learning rule for extraction of a single signal. We discuss several techniques which enable extraction of signals not randomly but in the desired ord...