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Menampilkan 1–3 dari 3 artikel
Leveraging Variational Quantum-Classical Algorithms for Enhanced Lung Cancer Prediction
Journal of Computing Theories and Applications
Vol 2
, No 3
(2024)
This work explores the potential of PennyLane and variational quantum-classical algorithms (VQCA) to forecast lung cancer using a structured dataset. The VQCA model performs exceptionally well, with flawless training, validation, and test accuracies of 1.0, demonstrating its capacity to identify patterns in the dataset and provide reliable predictions successfully. Contrarily, the accuracy of the quantum neural network (QNN) and classical neural network (NN) models is lower, demonstrating the be...
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A Mathematical Model for Analyzing the Spread of Infectious Diseases Using Differential Equations
Proceeding of the International Conference on Mathematical Sciences, Natural Sciences, and Computing
Vol 1
, No 1
(2024)
The spread of infectious diseases has become a critical issue in public health, requiring effective mathematical models to understand and control their dynamics. This study aims to develop a mathematical model based on differential equations to analyze the transmission patterns of infectious diseases. By dividing the population into distinct compartments—susceptible, infected, and recovered—this model provides a framework to study disease progression. The methodology involves formulating a syste...
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Optimizing Data Transmission in Wireless Sensor Networks Using Machine Learning
International Journal of Electrical Engineering, Mathematics and Computer Science
Vol 1
, No 2
(2024)
Data transmission efficiency is crucial in wireless sensor networks (WSNs), where limited battery life and signal reliability are significant concerns. This research explores various machine learning algorithms aimed at optimizing data transmission in WSNs, focusing on reducing energy consumption and enhancing network stability. Simulation results indicate marked improvements in efficiency, making WSNs more viable for long-term deployment across diverse environments.
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