The following study is based on a hybrid statistical-deterministic model designed for the assessment of the daily concentration of sulfur dioxide, carbon monoxide  and particulate matter (PM10) as major pollutants in the Greater Tehran Area (GTA): the capital of Iran. The model uses three available or assessable variables including economic, meteorological and environmental in the GTA for the y...

Aggregation of data flows has two major advantages. One is the reduction of state complexity within the network, the other is the saving of resources by statistical multiplexing between the aggregated flows. In this paper, we show a simple, yet effective scheme to aggregate real-time flows which require a statistical guarantee on experienced loss and a deterministic guarantee on the maximum del...

In this paper, a Multi-Choice Stochastic Bi-Level Programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general tran...

|In this paper, we develop bounds on the individual session backlog and delay distribution under the Generalized Processor Sharing (GPS) scheduling discipline. This work is motivated by, and is an extension of, Parekh and Gal-lager's deterministic study of the GPS scheduling discipline with leaky-bucket token controlled sessions 15], 16]. Using the exponentially bounded burstiness (E.B.B.) proc...

Equalizer design for multi-path channels is closely linked to the distribution of zeros of mobile channels. While in a deterministic scenario, equalizers can be designed based on knowledge of the exact locations of zeros in the complex plane, mobile channels like in GSM/EDGE systems ask for a different approach. Various channel distortions make the derivation of a deterministic model a hard if ...

This article explains how to apply the deterministic annealing (DA) and simulated annealing (SA) methods to fuzzy entropy based fuzzy c-means clustering. By regularizing the fuzzy c-means method with fuzzy entropy, a membership function similar to the Fermi-Dirac distribution function, well known in statistical mechanics, is obtained, and, while optimizing its parameters by SA, the minimum of t...