Industrial practitioners now face a bewildering array of possible configurations for effort estimation. How to select the best one for a particular dataset? This paper introduces OIL (short for optimized learning), a novel configuration tool for effort estimation based on differential evolution. When tested on 945 software projects, OIL significantly improved effort estimations, after exploring...

Case-Based Reasoning (CBR) has been widely used to generate good software effort estimates. The predictive performance of CBR is a dataset dependent and subject to extremely large space of configuration possibilities. Regardless of the type of adaptation technique, deciding on the optimal number of similar cases to be used before applying CBR is a key challenge. In this paper we propose a new t...

thickness and corrosion/erosion rate. In this thesis, a combination of signal processing techniques are used to estimate the corrosion rate estimates based on MBE. Corrosion rate is estimated based on ultrasonic pipe wall thickness data is collected over a short period of time using MBE model. This technique is based on data collected from the speedometer applied for thinning and both indicate ...

In this paper, a novel approach based on the Thévenin tracing is presented to modified conventional impedance-based out-of-step (OOS) protection. In conventional approach, the OOS detection is done by measuring positive sequence impedance. However, the measured impedance may be change due to different factors such as capacitor bank switching and reactive power compensators that it can cause the...

Software Cost Estimation is the challenging factor in project management. Accurate cost estimation helps to complete project with in time and budget. Due to this behavior of the project it is considered as a risky project .Under these conditions risk management is mandatory. Large numbers of estimation models have been proposed over the last 30 years. Constructive Cost Model (COCOMO) is one of ...

We propose novel discrete cosine transform (DCT) pseudophase techniques to estimate shift/delay between two one-dimensional(1-D) signals directly from their DCT coefficients by computing the pseudophase shift hidden in DCT and then employing the sinusoidal orthogonal principles, applicable to signal delay estimation remote sensing. Under the two-dimensional (2-D) translational motion model, we ...

ost estimation for an engineering project traditionally involves development of an “engineer’s estimate” of the project cost to which contingency is added to develop the “total project cost.” Contingency is used to reflect the fact that regardless of the diligence and competence of the estimator, there is uncertainty in the final cost of the project. Material costs change over time, markups and...

We focus on solving the problem of learning an optimal smoothing kernel for the unsupervised learning problem of kernel density estimation(KDE) by using hyperkernels. The optimal kernel is the one which minimizes the regularized negative leave-one-out-log likelihood score of the train set. We demonstrate that ”fixed bandwidth” and ”variable bandwidth” KDE are special cases of our algorithm.