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Physical Sciences and Mathematics Commons™

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Artificial Intelligence and Robotics

Selected Works

Machine learning

Articles 1 - 4 of 4

Full-Text Articles in Physical Sciences and Mathematics

Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara May 2013

Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara

Ole J Mengshoel

Mobile devices have evolved to become computing platforms more similar to desktops and workstations than the cell phones and handsets of yesteryear. Unfortunately, today’s mobile infrastructures are mirrors of the wired past. Devices, apps, and networks impact one another, but a systematic approach for allowing them to cooperate is currently missing. We propose an approach that seeks to open key interfaces and to apply feedback and autonomic computing to improve both user experience and mobile system dynamics.

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Financial Time Series Forecasting With Machine Learning Techniques: A Survey, Bjoern Krollner, Bruce Vanstone, Gavin Finnie Apr 2010

Financial Time Series Forecasting With Machine Learning Techniques: A Survey, Bjoern Krollner, Bruce Vanstone, Gavin Finnie

Gavin Finnie

Stock index forecasting is vital for making informed investment decisions. This paper surveys recent literature in the domain of machine learning techniques and artificial intelligence used to forecast stock market movements. The publications are categorised according to the machine learning technique used, the forecasting timeframe, the input variables used, and the evaluation techniques employed. It is found that there is a consensus between researchers stressing the importance of stock index forecasting. Artificial Neural Networks (ANNs) are identified to be the dominant machine learning technique in this area. We conclude with possible future research directions.

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Financial Time Series Forecasting With Machine Learning Techniques: A Survey, Bjoern Krollner, Bruce Vanstone, Gavin Finnie Apr 2010

Financial Time Series Forecasting With Machine Learning Techniques: A Survey, Bjoern Krollner, Bruce Vanstone, Gavin Finnie

Bjoern Krollner

Stock index forecasting is vital for making informed investment decisions. This paper surveys recent literature in the domain of machine learning techniques and artificial intelligence used to forecast stock market movements. The publications are categorised according to their research motivation, the machine learning technique used, the surveyed stock market, the forecasting time-frame, the input variables used, and the evaluation techniques employed. It is found that there is a consensus between researchers stressing the importance of stock index forecasting and that the results are promising. Artificial Neural Networks (ANNs) are identified to be the dominant machine learning technique in this area. …

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Financial Time Series Forecasting With Machine Learning Techniques: A Survey, Bjoern Krollner, Bruce Vanstone, Gavin Finnie Apr 2010

Financial Time Series Forecasting With Machine Learning Techniques: A Survey, Bjoern Krollner, Bruce Vanstone, Gavin Finnie

Bruce Vanstone

Stock index forecasting is vital for making informed investment decisions. This paper surveys recent literature in the domain of machine learning techniques and artificial intelligence used to forecast stock market movements. The publications are categorised according to the machine learning technique used, the forecasting timeframe, the input variables used, and the evaluation techniques employed. It is found that there is a consensus between researchers stressing the importance of stock index forecasting. Artificial Neural Networks (ANNs) are identified to be the dominant machine learning technique in this area. We conclude with possible future research directions.

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