Use of binary sigmoid function and linear identity in artificial neural networks for forecasting population density
Abstract Artificial Neural Network (ANN) is often used to solve forecasting cases. As in this
study. The artificial neural network used is with backpropagation algorithm. The study …
study. The artificial neural network used is with backpropagation algorithm. The study …
Healthcare and anomaly detection: using machine learning to predict anomalies in heart rate data
E Šabić, D Keeley, B Henderson, S Nannemann - Ai & Society, 2021 - Springer
The application of machine learning algorithms to healthcare data can enhance patient care
while also reducing healthcare worker cognitive load. These algorithms can be used to …
while also reducing healthcare worker cognitive load. These algorithms can be used to …
Modeling flood plain wetland transformation in consequences of flow alteration in Punarbhaba river in India and Bangladesh
S Talukdar, S Pal - Journal of Cleaner Production, 2020 - Elsevier
Ecologically precious and economically remunerative wetland resources in the riparian
flood plain of Punarbhaba river basin are under massive transformation in post hydrological …
flood plain of Punarbhaba river basin are under massive transformation in post hydrological …
[PDF][PDF] Levenberg-Marquardt algorithm combined with bipolar sigmoid function to measure open unemployment rate in Indonesia
ZM Nasution - 2021 - scitepress.org
The purpose of this research is to see how much open unemployment rate according to the
highest education completed in the country of Indonesia for subsequent years through …
highest education completed in the country of Indonesia for subsequent years through …
Analysis of Standard Gradient Descent with GD Momentum And Adaptive LR for SPR Prediction
Gradient Descent (GD) is used to find the local minimum value, its purpose is to find
variables on the error function so that a function can model the data with minimum error …
variables on the error function so that a function can model the data with minimum error …
A novel and reliable framework of patient deterioration prediction in intensive care unit based on long short-term memory-recurrent neural network
TI Alshwaheen, YW Hau, N Ass'Ad… - IEEE …, 2020 - ieeexplore.ieee.org
The clinical investigation explored that early recognition and intervention are crucial for
preventing clinical deterioration in patients in Intensive Care units (ICUs). Deterioration of …
preventing clinical deterioration in patients in Intensive Care units (ICUs). Deterioration of …
Churn classification model for local telecommunication company based on rough set theory
Customer care plays an important role in a company especially in managing churn for
Telecommunication Company. Churn is perceived as the behaviour of a customer to leave …
Telecommunication Company. Churn is perceived as the behaviour of a customer to leave …
A deep neural network electrocardiogram analysis framework for left ventricular hypertrophy prediction
Heart disease is ranked second in the top ten death causes in Taiwan in 2016, while the
amount of heart disease fatalities is increasing by about 700 individuals each year …
amount of heart disease fatalities is increasing by about 700 individuals each year …
Tansig activation function (of MLP network) for cardiac abnormality detection
Heart abnormality often occurs regardless of gender, age and races. This problem
sometimes does not show any symptoms and it can cause a sudden death to the patient. In …
sometimes does not show any symptoms and it can cause a sudden death to the patient. In …
Heterogeneous sensor data analysis using efficient adaptive artificial neural network on FPGA based edge gateway
We propose a FPGA based design that performs real-time power-efficient analysis of
heterogeneous sensor data using adaptive ANN on edge gateway of smart military …
heterogeneous sensor data using adaptive ANN on edge gateway of smart military …