This
study presents a multi-objective model for scheduling Intensity Modulated
Radiotherapy Treatment (IMRT) in patients with lung cancer, based on Genetic
Algorithms (GA). Cancer classification can be beneficial to forecast the
results of certain diseases or to find tumours' genetic behaviour. The
suggested approach is used to minimise the fitness function defined as the mean
squared error by optimizing the weight between layers and biases. The data set
consists of 120 cases of CT indicators of lung cancer, 26 of which are chosen
as the basis of diagnosis of lung cancer. In this study, a new approach is used
to establish an accurate classification model by combining the recently
developed heuristic algorithm Firefly Algorithm with the Genetic Algorithm in order
to optimiseoptimize the values of weights and biases with the purpose of
decreasing the mean squared error (mse), which is the study’s objective
function. When compared to existing algorithms, the suggested GA-based Firefly
Algorithm (FA) technique was shown to
have the lowest mean squared error of 0.0014. The GA schedules, using real data
acquired at the Cancer Center in collaboration, are effective. The suggested
GA-based FA is discussed and assessment results are displayed. In terms of
accuracy and mse, the proposed model, which is based on the GA, beats other
algorithms, according to the evaluation data.
Author(s) Details:
Keshav Kumar K.,
Department
of Humanities and Mathematics, G. Narayanamma Institute of Technology and
Science (for Women), Hyderabad-500 104, Telangana, India.
N.
V. S. L. Narasimham,
Department
of Humanities and Mathematics, G. Narayanamma Institute of Technology and
Science (for Women), Hyderabad-500 104, Telangana, India.
Please see the link here: https://stm.bookpi.org/CPSTR-V5/article/view/13277
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