AIMC Topic: Bees

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A lightweight, inexpensive robotic system for insect vision.

Arthropod structure & development
Designing hardware for miniaturized robotics which mimics the capabilities of flying insects is of interest, because they share similar constraints (i.e. small size, low weight, and low energy consumption). Research in this area aims to enable robots...

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

Computational intelligence and neuroscience
Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized ...

A robotic system for researching social integration in honeybees.

PloS one
In this paper, we present a novel robotic system developed for researching collective social mechanisms in a biohybrid society of robots and honeybees. The potential for distributed coordination, as observed in nature in many different animal species...

Computational intelligence applied to discriminate bee pollen quality and botanical origin.

Food chemistry
The aim of this work was to develop computational intelligence models based on neural networks (NN), fuzzy models (FM), and support vector machines (SVM) to predict physicochemical composition of bee pollen mixture given their botanical origin. To ob...

Honey bee hairs and pollenkitt are essential for pollen capture and removal.

Bioinspiration & biomimetics
While insect grooming has been observed and documented for over one hundred years, we present the first quantitative analysis of this highly dynamic process. Pollinating insects, like honey bees, purposely cover themselves with millions of pollen par...

Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees.

PLoS computational biology
The ability to generalize over naturally occurring variation in cues indicating food or predation risk is highly useful for efficient decision-making in many animals. Honeybees have remarkable visual cognitive abilities, allowing them to classify vis...

A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps.

Computational intelligence and neuroscience
As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapp...

An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch.

Computational intelligence and neuroscience
The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptan...

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...

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

Journal of integrative bioinformatics
Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big...