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Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models (2017)
Book Chapter

The ability to predict future states is fundamental for a wide variety of applications, from weather forecasting to stock market analysis. Understanding the related data attributes that can influence changes in time series is a challenging task that... Read More about Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models.

Exploiting antipheromone in ant colony optimisation for interactive search-based software design and refactoring (2016)
Presentation / Conference Contribution

Preventing user-fatigue in interactive meta-heuristic search places as great an emphasis on efficiency as it does on ef- fectiveness. Engagement may also be boosted if the system provides a sense of “responsiveness” - for example, avoiding unpopular... Read More about Exploiting antipheromone in ant colony optimisation for interactive search-based software design and refactoring.