AIMC Topic: Algorithms

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Healthy and unhealthy red blood cell detection in human blood smears using neural networks.

Micron (Oxford, England : 1993)
One of the most common diseases that affect human red blood cells (RBCs) is anaemia. To diagnose anaemia, the following methods are typically employed: an identification process that is based on measuring the level of haemoglobin and the classificati...

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Computational intelligence and neuroscience
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, l...

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

PloS one
Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system...

Drug-Drug Interaction Extraction via Convolutional Neural Networks.

Computational and mathematical methods in medicine
Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a lar...

Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization.

Computational intelligence and neuroscience
Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a nove...

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

Neural networks : the official journal of the International Neural Network Society
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identifie...

Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks.

PloS one
Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with ...

Combination of the Manifold Dimensionality Reduction Methods with Least Squares Support vector machines for Classifying the Species of Sorghum Seeds.

Scientific reports
This study was carried out for rapid and noninvasive determination of the class of sorghum species by using the manifold dimensionality reduction (MDR) method and the nonlinear regression method of least squares support vector machines (LS-SVM) combi...

ChemTok: A New Rule Based Tokenizer for Chemical Named Entity Recognition.

BioMed research international
Named Entity Recognition (NER) from text constitutes the first step in many text mining applications. The most important preliminary step for NER systems using machine learning approaches is tokenization where raw text is segmented into tokens. This ...

Swing Phase Control of Semi-Active Prosthetic Knee Using Neural Network Predictive Control With Particle Swarm Optimization.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In recent years, intelligent prosthetic knees have been developed that enable amputees to walk as normally as possible when compared to healthy subjects. Although semi-active prosthetic knees utilizing magnetorheological (MR) dampers offer several ad...