Academic Articles & Research Papers

Statistical Mechanics of Neural Networks

A neural network is a large, highly interconnected assembly of simple elements. The elements, called neurons, are usually two-state devices that switch from one state to the other when their input exceeds a specific threshold value. In this...

Neural Networks in Structural Engineering

In the past few years literature on computational civil engineering has concentrated primarily on artificial intelligence (Al) applications involving expert system technology. This article discusses a different Al approach involving neural ...

A Survey on Neural Network Interpretability

Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g.,...

A renaissance of neural networks in drug discovery

INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...

LSTM neural networks for language modeling

Neural networks have become increasingly popular for the task of language modeling.Whereas feed-forward networks only exploit a fixed context length to predict the next word of a sequence, conceptually, standard recurrent neural networks ca...

A neural-network-based detection of epilepsy

Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced ne...

Neural Networks in Clinical Medicine

Neural networks are parallel, distributed, adaptive information-processing systems that develop their functionality in response to exposure to information. This paper is a tutorial for researchers intending to use neural nets for medical de...

Neural networks in process fault diagnosis

Fault detection and diagnosis is an important problem in process automation. Both model-based methods and expert systems have been suggested to solve the problem, along with the pattern recognition approach. A number of possible neural netw...

Artificial neural networks for speech and vision

Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...

Artificial neural networks in process engineering

Artificial neural networks are made up of highly interconnected layers of simple ‘neuron-like’ nodes. The neurons act as nonlinear processing elements within the network. An attractive property of artificial neural networks is that, given t...

Neural networks for control

Provides a quick overview of neural networks and explains how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorit...

iNNvestigate neural networks!

In recent years, deep neural networks have revolutionized many application domains of machine learning and are key components of many critical decision or predictive processes. Therefore, it is crucial that domain specialists can understand...

Ensemble with neural networks for bankruptcy prediction

Neural networks and fuzzy systems

Emerging Principles Governing The Operation Of Neural Networks

ical, and computational techniques have provided the tools to begin uncovering concepts underlying neural network function. This review is a summary of insights into the organization and operation of neural circuits acquired through applica...

Using neural networks for data mining

Neural Networks for Postprocessing Ensemble Weather Forecasts

Abstract Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the pa...

Neural networks and fuzzy systems

Artificial Neural Networks

Neural networks for classification: a survey

Classification is one of the most active research and application areas of neural networks. The literature is vast and growing. This paper summarizes some of the most important developments in neural network classification research. Specifi...