In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
The paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural network model which is inspired by human parietal cortex functio...
Jun Tani, Ryunosuke Nishimoto, Jun Namikawa, Masat...
Abstract. We introduce the notion of tamper-evidence for mix networks in order to defend against attacks aimed at covertly leaking secret information held by corrupted mix servers....
This article provides a basic introduction to neural networks and neural network programming using the Encog Artificial Intelligence Framework. Encog is an AI framework that is ava...