AIMC Topic: Algorithms

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From honeybees to robots and back: division of labour based on partitioning social inhibition.

Bioinspiration & biomimetics
In this paper, a distributed adaptive partitioning algorithm inspired by division of labor in honeybees is investigated for its applicability in a swarm of underwater robots in one hand and is qualitatively compared with the behavior of honeybee colo...

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm.

Computational intelligence and neuroscience
For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO...

Exploiting ensemble learning for automatic cataract detection and grading.

Computer methods and programs in biomedicine
Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a...

Global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
The present paper studies global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays (FDNN). Firstly, some sufficient conditions are established to ensure that a non-au...

A linear functional strategy for regularized ranking.

Neural networks : the official journal of the International Neural Network Society
Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularizati...

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

ISA transactions
This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to de...

Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm.

Talanta
Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is pro...

Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span.

Medical engineering & physics
In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI datase...

Constructing general partial differential equations using polynomial and neural networks.

Neural networks : the official journal of the International Neural Network Society
Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transfo...