The aim of this study is to evaluate the ability soft computing models including multilayer perceptron- (MLP-) water wave optimization (MLP-WWO), MLP-particle swarm (MLP-PSO), and MLP-genetic algorithm (MLP-GA), simulate daily monthly reference evapotranspiration (ET) at Aidoghmoush basin (Iran). Principal component analysis (PCA) was used find best input combination lagged ETs. According resul...

Although the physiological states of hypertrophic remodeling and congestive heart failure have been intensively studied, less is known about the transition from one to the other. The use of genetically engineered murine models of heart failure has proven valuable in characterizing the progression of remodeling and its ultimate decompensation to failure. Mice deficient in the cytoskeletal muscle...

Gaussian mixture models (GMM) and support vector machines (SVM) are introduced to classify faults in a population of cylindrical shells. The proposed procedures are tested on a population of 20 cylindrical shells and their performance is compared to the procedure, which uses multi-layer perceptrons (MLP). The modal properties extracted from vibration data are used to train the GMM, SVM and MLP....

Although medical language processing (MLP) has achieved some success, the actual use and dissemination of data extracted from free text by MLP systems is still very limited. We claim that the adoption of an 'enriched-document' paradigm (or 'document-centered' view) can help to address this issue. We present this paradigm and explain how it can be implemented, then discuss its expected benefits ...

In recent years numerous articles have been published which advocate a multi-level perspective (MLP) for the analysis of long term technological transitions. This paper reviews current transitions research and considers the limitations of the MLP which need to be addressed to enhance understanding of processes of innovation affecting the transformation of technology and society. The paper sugge...

In this paper we compare two machine learning algorithms (Support Vector Machine and Multi Layer Perceptrons) to perform online dynamic security assessment of an electric power system. Dynamic simulation is properly emulated by training SVM and MLP models, with a small amount of information. The experiments show that although both models produce reasonable predictions, the performance indexes o...

This paper introduces a no vel quaternion{valued MLP{ type net w ork called the Quaternionic Spinor MLP (QSMLP). In con trast to another recently proposed Quaternionic MLP it uses spinors in its propagation function. This allows very eÆciently the processing of 3D vector data, whic his demonstrated by experiments. The QSMLP is pro ven to be a universal approximator and a learning algorithm for ...

The OWE (Orthogonal Weight Estimator) architecture is constituted of a main MLP in which the values of each weight is computed by another MLP (an OWE). The number of OWEs is equal to the number of weights of the main MLP. But the computation of each OWE is done independently. Therefore the training and relaxation phases can straightforward parallelized. We report the implementation of this arch...

In this paper we demonstrate the explicative capabilities of multilayer perceptron neural networks (MLP) with automatic relevance determination (ARD) weight regularization for personal injury protection (PIP) automobile insurance claim fraud detection. The ARD objective function hyperparameter scheme provides a means for soft input selection as it allows to determine which predictor variables a...