A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. Defining HMMs with side-constraints in Constraint Logic Programming has advantages in terms of more co...

today, due to rising passenger expectations and other resource constraints, the airport managers and staff do to develop appropriate programs in order to optimize the allocation of the resources. gates and counters are important resources in airport. in this research problem of gate and counter for arrival flights is considered simultaneously and mathematical model is prepared. the objectives o...

We present the Multivariable Fuzzy Temporal Profile model (MFTP), a formal model which allows us to represent signal patterns and identify their occurrences over the temporal evolution of a set of physical parameters. The pattern comprises a set of findings, each one of which may, in turn, be a pattern, so that its recognition is organized into a hierarchy of abstraction levels, and ultimately ...

We have previously reported a Bayesian algorithm for determining the coordinates of points in three­ dimensional space from uncertain constraints. This method is useful in the determination of biological molecular structure. It is limited, however, by the requirement that the uncertainty in the constraints be normally distributed. In this paper, we present an extension of the original algorithm...

We demonstrate a reliable and computationally feasible method for determining whether a given threshold autoregression autoregressive conditional heteroscedastic (AR-ARCH) model is ergodic, and for determining which moments exist when it is ergodic. This method may be used to delineate the parameter space of the model. We show (for an order 2 model) that the parameter space is much less constra...

In the real world there are groups which composed of independent units. The conventional data envelopment analysis(DEA) model treats groups as units, ignoring the operation of individual units within each group.The current paper, investigates parallel system network approach proposed by Kao and modifies it. As modied Kao' model is more eligible to recognize ecient groups, a new ranking method i...

This paper presents an approach contributing to the evaluation of linguistic complexity. Many different studies address this question. However, it remains very difficult to propose a precise evaluation on the basis of quantifiable criteria. The model we propose answers to this need thanks to an original representation of linguistic information by means of constraints. It brings together differe...

Background:Despite some successful dynamic simulation of self-impact double pendulum (SIDP)-as humanoid robots legs or arms- studies, there is limited information available about the control of one leg locomotion.Objective :The main goal of this research is to improve the reliability of the mammalians leg locomotion and building more elaborated models close to the natural movements, by modelin...

introduction: several techniques are used to evaluate decision making units in dmus with a restricted multiplier. dea is recognized as a methodology widely used to evaluate the relative efficiency of a set of decision-making units (dmus) involved in a production process. this approach assumes that the input and output data of the different decision making units (dmus) are measured with precisio...