In the present study, five modeling approaches of RA, MLP, MNN, GFF, and CANFIS were applied so as to estimate the radial overcut values in electrochemical drilling process. For these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. The developed models were evaluated in terms of their prediction capability with m...

in the present study, five modeling approaches of ra, mlp, mnn, gff, and canfis were applied so as to estimate the radial overcut values in electrochemical drilling process. for these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. the developed models were evaluated in terms of their prediction capability with m...

Effective prediction of defect-prone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Support vector machines (SVM) have been successfully applied for solving both classification and regression problems in many applications. This paper evaluates the capability of SVM in predicting defect-prone software modu...

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. ...

The EODES suite of electro-optical system models is designed to provide a high-fidelity simulation capability and accurate performance prediction tools. EODES simulations are being used to analyze the performance of existing electro-optical identification (EOID) systems and to inform new system design concepts. Performance prediction tools are being incorporated into tactical decision aids with...

Prediction of adversarial course of actions (COA) is critical to many applications including: crime prediction, Unmanned Aerial Vehicle (UAV) threat prediction, and terrorism attack prevention. Researchers have shown that integrating behavior features (or preferences/patterns/modes) into prediction systems, which utilize random process theory and likelihood estimation calculations, can improve ...

We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We find that the edge of chaos predicts quite well those values of circuit parameters that yield maximal computational performance. But obviously it makes no prediction of their computational performance for other parameter...

A target recognition capability is described that performs: color target detection, target type and pose hypothesis generation, and target type veri cation by 3-D alignment of target models to range and electro-optical imagery. The term `coregistration' is introduced to describe target, range and electro-optical (color and IR) sensor alignment correction. Online model feature prediction using 3...

Peer review is an effective and useful method for improving students’ learning through review by student peers. Peer review has been used in classes for several decades. To ensure the success of peer review, research challenges such as the quality of peer review must be addressed. It is challenging to identify how good the reviewer is. We develop a prediction model to assess students’ reviewing...