[HTML][HTML] Stability improvement of the PSS-connected power system network with ensemble machine learning tool
Stability is a primary requirement of the electrical power system for its flawless, secure, and
economical operation. Low-frequency oscillations (LFOs), commonly seen in interconnected …
economical operation. Low-frequency oscillations (LFOs), commonly seen in interconnected …
An adaptive approach-based ensemble for 1 day-ahead production prediction of solar PV systems
The world is becoming more reliant on renewable energy sources to satisfy its growing
energy demand. The primary disadvantage of such sources is their significant uncertainty in …
energy demand. The primary disadvantage of such sources is their significant uncertainty in …
Prediction of air pollution hotspot to prevent post effects of pollution by comparing logistic regression with random forest
MJ Sairam, T Sathish, V Nagaraju - AIP Conference Proceedings, 2024 - pubs.aip.org
This research evaluates the Logistic Regression (LR) and Random Forest (RF) algorithms,
two popular statistical approaches for long-term pollution forecasting. The Parts and …
two popular statistical approaches for long-term pollution forecasting. The Parts and …
[PDF][PDF] Energy Reports
abstract Stability is a primary requirement of the electrical power system for its flawless,
secure, and economical operation. Low-frequency oscillations (LFOs), commonly seen in …
secure, and economical operation. Low-frequency oscillations (LFOs), commonly seen in …
Predicting Breast Cancer with Ensemble Methods on Cloud
There are many dangerous diseases and high mortality rates for women (including breast
cancer). If the disease is detected early, correctly diagnosed and treated at the right time, the …
cancer). If the disease is detected early, correctly diagnosed and treated at the right time, the …
Improved Adaptive Boosting in Heterogeneous Ensembles for Outlier Detection: Prioritizing Minimization of Bias, Variance and Order of Base Learners
JK Bii - 2023 - ir.jkuat.ac.ke
Real-world data suffer from corruption caused by human errors, for instance, rounding
errors, wrong measurements, biases, faults, or rare events, including malicious activities like …
errors, wrong measurements, biases, faults, or rare events, including malicious activities like …
[PDF][PDF] Brute Exhaustive Optimization of Intelligent Small Weighted Voting Ensembles in 1EXP (-) Z+ Initial-Term based Arithmetic Sequence's Multi Precision Search …
AJ Malamsha, MA Dida, S Moebbs - researchmathsci.org
Other than the individual machine learning models' capabilities, the weighted voting
ensemble (WVE) technique relies on appropriate weight assignment in order to significantly …
ensemble (WVE) technique relies on appropriate weight assignment in order to significantly …
Dynamic Ensemble Selection Based on Hesitant Fuzzy Multiple Criteria Decision-Making
M Eftekhari, A Mehrpooya, F Saberi-Movahed… - How Fuzzy Concepts …, 2022 - Springer
One of the robust approaches in supervised classification learning is Multi Classifier
Systems (MCSs). These systems combine predictions of some weak classifiers in a way that …
Systems (MCSs). These systems combine predictions of some weak classifiers in a way that …