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Machine learning models for predicting the use of different animal breeding services in smallholder dairy farms in Sub-Saharan Africa.
(Springer Nature Switzerland AG., 2020-05-01)
This study is concerned with developing predictive models using machine learning techniques to be used in identifying factors that influence farmers' decisions, predict farmers' decisions, and forecast farmers' demands ...
Deep Reinforcement Learning based Handover Management for Millimeter Wave Communication
(International Journal of Advanced Computer Science and Applications,, 2021)
The Millimeter Wave (mm-wave) band has a broad-spectrum capable of transmitting multi-gigabit per-second date-rate. However, the band suffers seriously from obstruction and high path loss, resulting in line-of-sight (LOS) ...
Early-Warning Dropout Visualization Tool for Secondary Schools: Using Machine Learning, QR Code, GIS and Mobile Application Techniques
(International Journal of Advanced Computer Science and Applications, 2022)
: Investment in education through the provision of secondary school to the community is geared to develop human capital in Tanzania. However, these investments have been hampered by unacceptable higher rates of school ...
Data Balancing Techniques for Predicting Student Dropout Using Machine Learning
(MDPI, 2023-02-27)
Predicting student dropout is a challenging problem in the education sector. This is due to an imbalance in student dropout data, mainly because the number of registered students is always higher than the number of dropout ...
A Survey of Machine Learning Modelling for Agricultural Soil Properties Analysis and Fertility Status Predictions
(Preprints (www.preprints.org), 2023-08-21)
The problem of low soil fertility and limited research in agricultural data driven tools, may lead to
low crop productivity which makes it imperative to research in applications of high throughput computational
algorithms ...
Sensor-Based River Monitoring System: A Case for Kikuletwa River Floods in Tanzania
(Preprints, 2023-02-01)
Reliable and accurate flood prediction is a challenging task in poorly gauged basins due 1 to data scarcity. Data is an essential component of any AI/ML model today, and the performance 2 of such models hugely depends on ...
Extreme Rainfall Events Classification Using Machine Learning for Kikuletwa River Floods
(Preprints, 2023-02-20)
Advancements in Machine Learning techniques, availability of more data-sets, and 1 increased computing power have enabled a significant growth in a number research areas. Predicting, 2 detecting and classifying complex ...