AIMC Topic: Neural Networks, Computer

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Tracing Road Network Bottleneck by Data Driven Approach.

PloS one
Urban road congestions change both temporally and spatially. They are essentially caused by network bottlenecks. Therefore, understanding bottleneck dynamics is critical in the goal of reasonably allocating transportation resources. In general, a typ...

A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints.

IEEE transactions on cybernetics
Pseudoconvex optimization problem, as an important nonconvex optimization problem, plays an important role in scientific and engineering applications. In this paper, a recurrent one-layer neural network is proposed for solving the pseudoconvex optimi...

A neural model of the frontal eye fields with reward-based learning.

Neural networks : the official journal of the International Neural Network Society
Decision-making is a flexible process dependent on the accumulation of various kinds of information; however, the corresponding neural mechanisms are far from clear. We extended a layered model of the frontal eye field to a learning-based model, usin...

Co-combustion of peanut hull and coal blends: Artificial neural networks modeling, particle swarm optimization and Monte Carlo simulation.

Bioresource technology
Co-combustion of coal and peanut hull (PH) were investigated using artificial neural networks (ANN), particle swarm optimization, and Monte Carlo simulation as a function of blend ratio, heating rate, and temperature. The best prediction was reached ...

Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy, USA.

Environmental science and pollution research international
This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In the proposed model, four water quality variables that are water temperature, dissolved oxygen, pH, and...

Analysis of complex neural circuits with nonlinear multidimensional hidden state models.

Proceedings of the National Academy of Sciences of the United States of America
A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamica...

Adaptive Neuro-Fuzzy Determination of the Effect of Experimental Parameters on Vehicle Agent Speed Relative to Vehicle Intruder.

PloS one
Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have go...

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.

Scientific reports
Pathologists face a substantial increase in workload and complexity of histopathologic cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic protocols have to focus equally on efficiency and accuracy. In this paper we int...

Lung sound classification using cepstral-based statistical features.

Computers in biology and medicine
Lung sounds convey useful information related to pulmonary pathology. In this paper, short-term spectral characteristics of lung sounds are studied to characterize the lung sounds for the identification of associated diseases. Motivated by the succes...