AIMC Topic: Algorithms

Clear Filters Showing 22461 to 22470 of 28713 articles

An Ensemble Approach for Cognitive Fault Detection and Isolation in Sensor Networks.

International journal of neural systems
Cognitive fault detection and diagnosis systems are systems able to provide timely information about possibly occurring faults without requiring any a priori knowledge about the process generating the data or the possible faults. This ability is cruc...

Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.

Artificial intelligence in medicine
OBJECTIVE: The combination of phenomic data from electronic health records (EHR) and clinical data repositories with dense biological data has enabled genomic and pharmacogenomic discovery, a first step toward precision medicine. Computational method...

Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.

IEEE transactions on neural networks and learning systems
In this paper, we have introduced a general modeling approach for dynamic nonlinear systems that utilizes a variant of the simulated annealing algorithm for training the Laguerre-Volterra network (LVN) to overcome the local minima and convergence pro...

Bloodstain pattern analysis as optimisation problem.

Forensic science international
Bloodstain pattern analysis (BPA) is an approach to support forensic investigators in reconstructing the dynamics of bloody crimes. This forensic technique has been successfully applied in solving heinous and complex murder cases around the world and...

Machine learning approaches in medical image analysis: From detection to diagnosis.

Medical image analysis
Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging...

Extreme learning machine and adaptive sparse representation for image classification.

Neural networks : the official journal of the International Neural Network Society
Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks,...

Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification.

Computational intelligence and neuroscience
The latest generation of convolutional neural networks (CNNs) has achieved impressive results in the field of image classification. This paper is concerned with a new approach to the development of plant disease recognition model, based on leaf image...

Neural network training as a dissipative process.

Neural networks : the official journal of the International Neural Network Society
This paper analyzes the practical issues and reports some results on a theory in which learning is modeled as a continuous temporal process driven by laws describing the interactions of intelligent agents with their own environment. The classic regul...

Using Machine Learning to Predict Laboratory Test Results.

American journal of clinical pathology
OBJECTIVES: While clinical laboratories report most test results as individual numbers, findings, or observations, clinical diagnosis usually relies on the results of multiple tests. Clinical decision support that integrates multiple elements of labo...

Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm.

SAR and QSAR in environmental research
Large worldwide use of chemicals has caused great concern about their possible adverse effects on human health, flora and fauna. Increased production of new chemicals has also increased demand for their risk assessment. Traditionally, results from an...