Nowadays, effort estimation in software projects is turned to one of the key concerns for project managers. In fact, accurately estimating of essential effort to produce and improve a software product is effective in software projects success or fail, which is considered as a vital factor. Lack of access to satisfying accuracy and little flexibility in existing estimation models have attracted ...

estimation of gold reserves and resources has been of interest to mining engineers and geologists for ages. the existence of outlier values shows the economic part of the deposits subject to the fact that don’t depend on the human or technical errors. the presence of these high values causes a pseudo dramatically increment in variance estimation of economical blocks when applying conventional m...

State estimation in the energy management center of active distribution networks has attracted many attentions. Considering an increase in complexity and real-time management of active distribution networks and knowing the network information at each time instant are necessary. This article presents a two-step multi-area state estimation method in balanced active distribution networks. The prop...

Propagation of radio occultation (RO) signals through the lower troposphere results in high phase acceleration and low signal to noise ratio signal. The excess Doppler estimation accuracy in lower troposphere is very important in receiving RO signals which can be estimated by sliding window spectral analysis. To do this, various frequency estimation methods such as MUSIC and ESPRIT can be adopt...

In this paper we present a statistical method for estimating the relative geometry between two images and give useful methods to characterise motion estimation error. We argue that the estimation of the camera motion should be done in a statistical framework and describe a solution for the case of calibrated images. Statistical bootstrap is used to compute the underlying probability structure o...

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

Pose estimation involves reconstructing the configuration of a moving body from images sequences. In this paper we present a general framework for pose estimation of unknown objects based on Shafer’s evidential reasoning. During learning an evidential model of the object is built, integrating different image features to improve both estimation robustness and precision. All the measurements comi...

Previous attempts at defining other correlation measures mostly tried to generalize the inner product definition used in Pearson’s correlation coefficient. This does allow for certain useful correlations, like the Greatest Deviation, or Gini’s. In this work the idea in Gideon and Hollister (1987) of seeing correlation as the difference between distance from perfect negative and perfect positive...

This tutorial describes a parameter estimation technique that is little-known in social sciences, namely maximum a posteriori estimation. This technique can be used in conjunction with prior knowledge to improve maximum likelihood estimation of the best-fitting parameters of a data set. The estimates are based on the mode of the posterior distribution of a Bayesian analysis. The relationship be...

Previous attempts at defining other correlation measures mostly tried to generalize the inner product definition used in Pearson’s correlation coefficient. This does not allow for certain useful correlation’s, like the Greatest Deviation, or Gini’s. In this work the idea in Gideon and Hollister (1987) of seeing correlation, as the difference between distance from perfect negative and perfect po...