AIMC Topic: Forecasting

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Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

PloS one
In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. ...

Robotics in Arthroplasty: A Comprehensive Review.

The Journal of arthroplasty
Robotic-assisted orthopedic surgery has been available clinically in some form for over 2 decades, claiming to improve total joint arthroplasty by enhancing the surgeon's ability to reproduce alignment and therefore better restore normal kinematics. ...

Artificial neural network models for prediction of daily fine particulate matter concentrations in Algiers.

Environmental science and pollution research international
Neural network (NN) models were evaluated for the prediction of suspended particulates with aerodynamic diameter less than 10-μm (PM10) concentrations. The model evaluation work considered the sequential hourly concentration time series of PM10, whic...

Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans.

International journal of environmental research and public health
BACKGROUND: We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was ...

State of the Art and Future Directions for Lower Limb Robotic Exoskeletons.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Research on robotic exoskeletons has rapidly expanded over the previous decade. Advances in robotic hardware and energy supplies have enabled viable prototypes for human testing. This review paper describes current lower limb robotic exoskeletons, wi...

Artificial intelligence and synthetic biology: A tri-temporal contribution.

Bio Systems
Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing ...

FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.

Computational intelligence and neuroscience
Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC...

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks.

Computational intelligence and neuroscience
The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN...

Prediction of Soil Deformation in Tunnelling Using Artificial Neural Networks.

Computational intelligence and neuroscience
In the past few decades, as a new tool for analysis of the tough geotechnical problems, artificial neural networks (ANNs) have been successfully applied to address a number of engineering problems, including deformation due to tunnelling in various t...

Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting.

Computational intelligence and neuroscience
Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance ...