AIMC Topic: Neural Networks, Computer

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Forecasting mergers and acquisitions failure based on partial-sigmoid neural network and feature selection.

PloS one
Traditional forecasting methods in mergers and acquisitions (M&A) data have two limitations that significantly reduce forecasting accuracy: (1) the imbalance of data, that is, the failure cases of M&A are far fewer than the successful cases (82%/18% ...

A Connectionist Model for Dynamic Economic Risk Analysis of Hydrocarbons Production Systems.

Risk analysis : an official publication of the Society for Risk Analysis
This study presents a connectionist model for dynamic economic risk evaluation of reservoir production systems. The proposed dynamic economic risk modeling strategy combines evidence-based outcomes from a Bayesian network (BN) model with the dynamic ...

A second-order accelerated neurodynamic approach for distributed convex optimization.

Neural networks : the official journal of the International Neural Network Society
Based on the theories of inertial systems, a second-order accelerated neurodynamic approach is designed to solve a distributed convex optimization with inequality and set constraints. Most of the existing approaches for distributed convex optimizatio...

An inertial neural network approach for robust time-of-arrival localization considering clock asynchronization.

Neural networks : the official journal of the International Neural Network Society
This paper presents an inertial neural network to solve the source localization optimization problem with l-norm objective function based on the time of arrival (TOA) localization technique. The convergence and stability of the inertial neural networ...

Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images.

Experimental eye research
The purpose of this study was to develop an automatic deep learning-based approach and corresponding free, open-source software to perform segmentation of the Schlemm's canal (SC) lumen in optical coherence tomography (OCT) scans of living mouse eyes...

Analysis of Gastrointestinal Acoustic Activity Using Deep Neural Networks.

Sensors (Basel, Switzerland)
Automated bowel sound (BS) analysis methods were already well developed by the early 2000s. Accuracy of ~90% had been achieved by several teams using various analytical approaches. Clinical research on BS had revealed their high potential in the non-...

Automated Quantification of Brittle Stars in Seabed Imagery Using Computer Vision Techniques.

Sensors (Basel, Switzerland)
Underwater video surveys play a significant role in marine benthic research. Usually, surveys are filmed in transects, which are stitched into 2D mosaic maps for further analysis. Due to the massive amount of video data and time-consuming analysis, t...

Monitoring Illegal Tree Cutting through Ultra-Low-Power Smart IoT Devices.

Sensors (Basel, Switzerland)
Forests play a fundamental role in preserving the environment and fighting global warming. Unfortunately, they are continuously reduced by human interventions such as deforestation, fires, etc. This paper proposes and evaluates a framework for automa...

Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality.

Epidemiology and infection
This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e. the Hubei province in China, the epicentre of the coronavirus disease-2019 (COVID-19) pandemic], w...

Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.

Computational and mathematical methods in medicine
Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the ear...