AIMC Topic: Neural Networks, Computer

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Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

Waste management (New York, N.Y.)
Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of ...

Real-time multi-channel monitoring of burst-suppression using neural network technology during pediatric status epilepticus treatment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To develop a real-time monitoring system that has the potential to guide the titration of anesthetic agents in the treatment of pediatric status epilepticus (SE).

On the Computational Power of Spiking Neural P Systems with Self-Organization.

Scientific reports
Neural-like computing models are versatile computing mechanisms in the field of artificial intelligence. Spiking neural P systems (SN P systems for short) are one of the recently developed spiking neural network models inspired by the way neurons com...

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

Scientific reports
The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoen...

Hazard Detection for Motorcycles via Accelerometers: A Self-Organizing Map Approach.

IEEE transactions on cybernetics
This paper deals with collision and hazard detection for motorcycles via inertial measurements. For this kind of vehicles, the most difficult challenge is to distinguish road's anomalies from real hazards. This is usually done by setting absolute thr...

Statistical Performance Analysis of Data-Driven Neural Models.

International journal of neural systems
Data-driven model-based analysis of electrophysiological data is an emerging technique for understanding the mechanisms of seizures. Model-based analysis enables tracking of hidden brain states that are represented by the dynamics of neural mass mode...

Using self-organizing maps to infill missing data in hydro-meteorological time series from the Logone catchment, Lake Chad basin.

Environmental monitoring and assessment
Hydro-meteorological data is an important asset that can enhance management of water resources. But existing data often contains gaps, leading to uncertainties and so compromising their use. Although many methods exist for infilling data gaps in hydr...

Forecast Modelling via Variations in Binary Image-Encoded Information Exploited by Deep Learning Neural Networks.

PloS one
Traditional forecasting models fit a function approximation from dependent invariables to independent variables. However, they usually get into trouble when date are presented in various formats, such as text, voice and image. This study proposes a n...

Metaheuristic Algorithms for Convolution Neural Network.

Computational intelligence and neuroscience
A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metah...

Predictive models reduce talent development costs in female gymnastics.

Journal of sports sciences
This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection proced...