Joseph, A., Vodenska, I., Stanley, E., Chen, G., 2014. Netconomics: Novel Fore- casting Techniques from the Combination of Big Data, Network Science and Economics. Manuscript. Available at http://arxiv.org/pdf/1403.0848v1.pdf
The first step is to load the data and transform it into a structure that we will then use for each of our models. In its raw form, each row of data represents a single day of sales at one of ten stores. Our goal is to predict monthly sales, so we will first consolidate all stor...
This special issue seeks to explore innovative approaches and methodologies to advance responsible AI with a particular emphasis on explainability and responsibility of AI. The focus is on extending traditional IS and human-computer interface theories and techniques by integrating new dimensions, such as...
Tzafestas, S. G. and Mekras, N.: Industrial forecasting using knowledge-based techniques and artificial neural networks, in: S. G. Tzafestas (ed.),Advances in Manufacturing: Decision, Control and Information Technology, Springer, Berlin/London, 1999, pp. 171-180. Google Scholar Tzafestas,...
Second, it is possible to reduce the number of parameters used in the Earth-specific positional bias by parameter sharing or other techniques. However, we did not consider it a key issue, because it is unlikely to deploy the weather forecasting model to edge devices with limited storage. ...
Reservoir-based techniques for speech recognition. In 2006 International Joint Conference on Neural Networks (IJCNN) 1050–1053 (IEEE, 2006). Triefenbach, F., Jalalvand, A., Schrauwen, B. & Martens, J.-P. Phoneme recognition with large hierarchical reservoirs. Adv. Neural Inf. Process. ...
making it challenging for human researchers to keep track of the progress. Here we use AI techniques to predict the future research directions of AI itself. We introduce a graph-based benchmark based on real-world data—the Science4Cast benchmark, which aims to predict the future state of an...
The ability to predict the future and minimize this uncertainty is a key in the success of a company. That is why forecasting is such an important management tool. In forecasting there are several considerations, such as time horizon, technical sophistication, cost, data availability and ...
distillation49and other efficiency techniques should be explored. Furthermore, previous work has shown that the performance of MLWP models that are trained on reanalysis can be further improved by fine-tuning using operational data, such as HRES analysis inputs and targets30. This underscores the ...
The literature review on the application of decomposition time series forecasting techniques in power systems, conducted in line with the approach discussed in Section 2 above, identified several publications. A review of these publications indicated a logical classification by areas of application into ...