A Machine learning framework to predict reverse flow and water level: A case study of Tonle Sap Lake
Reliable assessment of the natural interactions in large river–lake systems is vital for water
supply planning, flood regulation, and ecosystem services. The existing interaction between …
supply planning, flood regulation, and ecosystem services. The existing interaction between …
Determining the number of hidden layer and hidden neuron of neural network for wind speed prediction
Artificial neural network (ANN) is one of the techniques in artificial intelligence, which has
been widely applied in many fields for prediction purposes, including wind speed prediction …
been widely applied in many fields for prediction purposes, including wind speed prediction …
Improved Otsu and Kapur approach for white blood cells segmentation based on LebTLBO optimization for the detection of Leukemia.
The diagnosis of leukemia involves the detection of the abnormal characteristics of blood
cells by a trained pathologist. Currently, this is done manually by observing the …
cells by a trained pathologist. Currently, this is done manually by observing the …
Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion
Due to the impact of climate change, the groundwater level (GWL) has been declining
recently in Malaysia, which is essential to protect the groundwater aquifer against depletion …
recently in Malaysia, which is essential to protect the groundwater aquifer against depletion …
Improving hyper-parameter self-tuning for data streams by adapting an evolutionary approach
Hyper-parameter tuning of machine learning models has become a crucial task in achieving
optimal results in terms of performance. Several researchers have explored the optimisation …
optimal results in terms of performance. Several researchers have explored the optimisation …
A novel multi-objective rat swarm optimizer-based convolutional neural networks for the diagnosis of covid-19 disease
GI Sayed - Automatic Control and Computer Sciences, 2022 - Springer
Early detection of coronavirus disease (COVID-19) is considered an essential task for
disease control and cure. Thus, an automated diagnosis of COVID-19 is highly desirable …
disease control and cure. Thus, an automated diagnosis of COVID-19 is highly desirable …
[PDF][PDF] An Improving Long Short Term Memory-Grid Search Based Deep Learning Neural Network for Software Effort Estimation.
One of the main reasons that hinders making software effort estimation remains a most of the
unresolved problem due to the heterogeneous nature of software data with complex …
unresolved problem due to the heterogeneous nature of software data with complex …
Optimizing RNNs for EMG Signal Classification: A Novel Strategy Using Grey Wolf Optimization
Accurate classification of electromyographic (EMG) signals is vital in biomedical
applications. This study evaluates different architectures of recurrent neural networks for the …
applications. This study evaluates different architectures of recurrent neural networks for the …
[HTML][HTML] Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer
Time series forecasting is crucial across various sectors, aiding stakeholders in making
informed decisions, planning for the short and long term, managing risks, optimizing profits …
informed decisions, planning for the short and long term, managing risks, optimizing profits …
[PDF][PDF] Obstacle Avoidance and Path Planning for UAV Using Laguerre Polynomial.
BS Shihab, HN Abdullah, LA Hassnawi - International Journal of …, 2022 - inass.org
Recently, path planning algorithms have been one of the primary and important functions of
unmanned aerial vehicles (UAVs). Path planning algorithms in UAVs focused on path …
unmanned aerial vehicles (UAVs). Path planning algorithms in UAVs focused on path …