[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …
installed in residential buildings. If leveraged properly, that data could assist end-users …
[图书][B] Advances in financial machine learning
ML De Prado - 2018 - books.google.com
Learn to understand and implement the latest machine learning innovations to improve your
investment performance Machine learning (ML) is changing virtually every aspect of our …
investment performance Machine learning (ML) is changing virtually every aspect of our …
Drivers of domestic electricity users' price responsiveness: A novel machine learning approach
Time-based pricing for domestic electricity users has been effective in reducing peak
demand and facilitating integration of renewable energies. However, high cost, price non …
demand and facilitating integration of renewable energies. However, high cost, price non …
Detection of sources of instability in smart grids using machine learning techniques
D Moldovan, I Salomie - 2019 IEEE 15th International …, 2019 - ieeexplore.ieee.org
The prediction of smart grid stability represents a challenging research problem because
this information can be very useful for the identification of the participants that lead to …
this information can be very useful for the identification of the participants that lead to …
Fusion-based machine learning approach for classification of algae varieties exposed to different light sources in the growth stage
Microalgae are one of the most important organisms in the ecosystem, and they have
important roles in terms of their function and continuity in the ecosystem. Additionally …
important roles in terms of their function and continuity in the ecosystem. Additionally …
Meta-learning-based prediction of different corn cultivars from color feature extraction
Image analysis techniques are developing as applicable to the approaches of quantitative
analysis, which is aimed to determine cultivar grains. Additionally, corn (Zea mays) grain …
analysis, which is aimed to determine cultivar grains. Additionally, corn (Zea mays) grain …
Time series features extraction versus lstm for manufacturing processes performance prediction
In this article is addressed the complexity of predicting the performance of manufacturing
processes in cyber-physical systems in cases when the products go through hundreds of …
processes in cyber-physical systems in cases when the products go through hundreds of …
Spillover as a cause of bias in baseline evaluation methods for demand response programs
A Todd, P Cappers, CA Spurlock, L Jin - Applied Energy, 2019 - Elsevier
Prior research has shown load reduction estimates from residential event-driven demand
response programs (eg, Critical Peak Pricing) using X of the highest Y days with a weather …
response programs (eg, Critical Peak Pricing) using X of the highest Y days with a weather …
Data Driven Dimensionality Reduction to Improve Modeling Performance✱
In a number of applications, data may be anonymized, obfuscated, or highly noisy. In such
cases, it is difficult to use domain knowledge or low-dimensional visualizations to engineer …
cases, it is difficult to use domain knowledge or low-dimensional visualizations to engineer …
[PDF][PDF] Predictive analytics for application management services
With digitization efforts running across all industries, IT consulting firms have enjoyed ever-
increasing demand for their services. To cope with this demand surge, long-term hiring …
increasing demand for their services. To cope with this demand surge, long-term hiring …