Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not...
Identifying the genes that cause disease is one of the most challenging issues to establish the diagnosis and treatment quickly. Several interesting methods have been introduced for disease gene identification for a decade. In general, the main diffe...
Many text mining applications in the biomedical domain benefit from automatic clustering of relational phrases into synonymous groups, since it alleviates the problem of spurious mismatches caused by the diversity of natural language expressions. Mos...
BACKGROUND: There are currently no neuroanatomical biomarkers of anorexia nervosa (AN) available to make clinical inferences at an individual subject level. We present results of a multivariate machine learning (ML) approach utilizing structural neur...
Neural networks : the official journal of the International Neural Network Society
May 5, 2015
In this paper, multistability analysis for a class of stochastic delayed Hopfield neural networks is investigated. By considering the geometrical configuration of activation functions, the state space is divided into 2(n) + 1 regions in which 2(n) re...
When computing the trajectory of an autonomous vehicle, inevitable collision states must be avoided at all costs, so no harm comes to the device or pedestrians around it. In dynamic environments, considering collisions as binary events is risky and i...
IEEE transactions on neural networks and learning systems
Feb 19, 2015
This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimension...
The max-min composition in fuzzy set theory has attained reasonable success in medical diagnosis in the past thirty years for estimating the probability of a patient diagnosed with a certain disease. However, there has been no theoretical justificati...
INTRODUCTION: The ambiguity of biomedical abbreviations is one of the challenges in biomedical text mining systems. In particular, the handling of term variants and abbreviations without nearby definitions is a critical issue. In this study, we adopt...
IEEE transactions on neural networks and learning systems
Dec 19, 2014
In this paper, we propose new methods for the choice and adaptation of the smoothing parameter of the probabilistic neural network (PNN). These methods are based on three reinforcement learning algorithms: Q(0)-learning, Q(λ)-learning, and stateless ...