An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3
Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Population Based Meta Heuristics Algorithm for Performance Improvement of Feed Forward Neural Network
Volume-2 | Issue-1
Comparative Analysis of an Efficient Image Denoising Method for Wireless Multimedia Sensor Network Images in Transform Domain
Volume-3 | Issue-3
A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems
Volume-3 | Issue-3
An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4
Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4
Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4
Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Volume - 5 | Issue - 1 | march 2023
Published
19 April, 2023
Congestion in the Emergency Department (ED) is a major problem in the hospital for patients and staff, due to the increased waiting times, length of stay, and medical errors, thus causing great losses to the hospital. Emergency services are essential in society, given the human need for them at any stage of life. The emergency department is characterized by the complex nature of its resources, as it consists of different parts. Many solutions are being proposed in order to solve the numerous problems in the ED, and to improve the quality of service. Researchers rely on many techniques such as optimization algorithms, simulations, data mining, and other methods to solve congestion. In this research, an approach based on PSO algorithm and coloured Petri net has been proposed. The emergency department is modelled using a coloured Petri net, and PSO algorithm is used to determine the human resources. Based on the results, the simulation model is modified, restarted, and the results are compared with the Benchmark model. This research helps decision makers in the ED to find appropriate solutions for human resources.
KeywordsEmergency department Coloured Petri Net PSO simulation optimization
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