Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...

What is the powerful ingredient which allows a dramatic speed-up of quantum computation over classical computation ? We propose that this ingredient is an implicit use of the Bayesian probability theory. Furthermore, we argue that both classical and quantum computation are special cases of probability reasoning. On these grounds, introducing Bayesian probability theory in classical computation ...

This paper responds to a number of criticisms of Dempster-Shafer theory made by Judea Pearl. He criticises Dempster-Shafer belief for not obeying the laws of Bayesian belief," however, these laws lead to well-known problems in the face of ignorance, and seem unreasonably restrictive. It is argued that it is not reasonable to expect a measure of belief to obey Pearl's sandwich principle. The sta...

A utility function is an important tool for representing a DM’s preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utili...

here in, an application of a new seismic inversion algorithm in one of iran’s oilfields is described. stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. this method integrates information from different data sources with different scales, as prior informat...

Context-sensing for context-aware HCI challenges the traditional sensor fusion methods with dynamic sensor configuration and measurement requirements commensurate with human perception. The Dempster-Shafer theory of evidence has uncertainty management and inference mechanisms analogous to our human reasoning process. Our Sensor Fusion for Contextaware Computing Project aims to build a generaliz...

Bayesian theory [5] is one of the most commonly utilized theories for managing uncertainty in information fusion [20, 12]. The theory relies on two main assumptions: (1) a probability function should be used for representing belief and (2) Bayes’ theorem should be used for belief updating when a new observation has been made. The main criticism of Bayesian theory that can be found in the litera...