Research Article
Exploring a Novel Approach of K-mean Gradient Boosting Algorithm with PCA for Drought Prediction
Babatunde Isaiah Ayinla*
,
Rasheedat Aderonke Abdulsalam
Issue:
Volume 9, Issue 1, June 2024
Pages:
1-19
Received:
11 June 2024
Accepted:
8 July 2024
Published:
23 July 2024
Abstract: Drought poses a significant threat to essential resources like food, land, and public health. Machine Learning (ML) has emerged as a powerful tool in weather forecasting, leveraging algorithms to predict weather phenomena with remarkable accuracy. ML models excel in navigating complex atmospheric systems, including those affected by climate change, offering precision beyond traditional forecasting methods. However, predicting drought remains challenging due to its uneven distribution and varying degrees. To tackle this challenge, an exploration of a novel approach of combining K-means++ clustering and Gradient Boosting Algorithm (KGBA) with Principal Component Analysis (PCA) for dimensionality reduction was carried out. Using a dataset spanning from 2000 to July 2016, comprising 2,756,796 US Drought Monitor records, the study developed and evaluated the KGBA model's effectiveness in drought prediction. The results demonstrated the superiority of high precision and recall rates, particularly in forecasting extreme and exceptional drought periods. Specifically, KGBA attained precision accuracies of 33% and 74%, along with recall rates of 72% and 77% for predicting extreme and exceptional drought periods, respectively. The model had an overall accuracy of 46% in predicting all the multiple classes of droughts. A performance that is slightly better than other ensemble methods that had the closest performance. These findings underscore the potential of KGBA in enhancing the predictive capabilities for drought mitigation efforts, as it outperformed other models such as Gradient Boosting, Random Forest, Bayes Naive, and K-Nearest Neighbor.
Abstract: Drought poses a significant threat to essential resources like food, land, and public health. Machine Learning (ML) has emerged as a powerful tool in weather forecasting, leveraging algorithms to predict weather phenomena with remarkable accuracy. ML models excel in navigating complex atmospheric systems, including those affected by climate change,...
Show More
Research Article
Deciphering the Symptom Spectrum: A Comprehensive Analysis of Migraine Patterns and Types
Firoz Hasan,
Rubina Khatun*,
Engr. Mohammad Salman,
Tarek Mahmud,
Dewan Mamun Raza,
Aynul Hasan Nahid
Issue:
Volume 9, Issue 1, June 2024
Pages:
20-31
Received:
14 August 2024
Accepted:
11 September 2024
Published:
29 October 2024
DOI:
10.11648/j.ajdmkd.20240901.12
Downloads:
Views:
Abstract: Complex neurological diseases like migraine migraine affect a large section of the global population, causing health, social, and economic issues. Migraine causes intense, painful headaches that are usually one-sided and pulsing. Auras, nausea, vomiting, and excessive light and sound sensitivity may precede these episodes. Migraine affect millions worldwide and can be intermittent or persistent, impairing function. Diet and stress may induce it, but the cause is unknown. Prevention and symptom treatment drugs and lifestyle changes are used. Debilitating migraines are hard to diagnose due to their varied presentation and subjective symptom reporting. Traditional migraine diagnosis, based on clinical evaluation, typically fails to classify migraine types, requiring more objective and rigorous instruments. This study proposes a machine learning-based migraine categorization method to address this issue. The dataset includes different patient demographics and clinical variables; thus, we use complex algorithms like Random for Forest, XGBoost, and Extra Trees. These algorithms are great for deciphering migraine patterns because they excel at evaluating complex datasets. The research seeks to close this gap to improve migraine classification accuracy, objectivity, and reliability, enabling tailored migraine management and treatment. This neurology study could im- prove migraine diagnosis and treatment with more effective and personalized plans.
Abstract: Complex neurological diseases like migraine migraine affect a large section of the global population, causing health, social, and economic issues. Migraine causes intense, painful headaches that are usually one-sided and pulsing. Auras, nausea, vomiting, and excessive light and sound sensitivity may precede these episodes. Migraine affect millions ...
Show More
