NDLI: Cost Optimization in Neural Network using Whale Swarm Algorithm with Batched Gradient Descent Optimizer

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Cost Optimization in Neural Network using Whale Swarm Algorithm with Batched Gradient Descent Optimizer

Content Provider	Scilit
Author	Karthikeyan, C. Sreedevi, E. Kumar, Naveen Vamsidhar, E. Kumar, T. Rajesh Babu, D. Vijendra
Copyright Year	2020
Description	Journal: Iop Conference Series: Materials Science and Engineering Optimization algorithms are liable for sinking the losses and to give the most precise outcomes conceivable. Optimizers are utilized to modify the properties of neural network, for example, training rate and weights are used to reduce the losses. Optimization means a procedure of obtaining a global optimal solution for a given problem under given conditions. The real-world problems in the scientific fields, such as engineering design and economic planning, mostly are multimodal, high-dimensional, disconnected, and oscillated optimization problems. These complex problems cannot be solved well within reasonable time using traditional method based on gradient. Nature-inspired algorithms are becoming delightful in resolving mathematical optimization problems, like multiprocessor scheduling problem, vehicle routing and classification problems etc. In this manuscript, Whale Swarm Optimization algorithm on optimizing the neural networks, one of the meta-heuristic algorithms is applied to analysis of the cardiovascular disease dataset and compares the performance with Gradient Descent and RMSprop optimization techniques.
Related Links	https://iopscience.iop.org/article/10.1088/1757-899X/993/1/012047/pdf
ISSN	17578981
e-ISSN	1757899X
DOI	10.1088/1757-899x/993/1/012047
Journal	Iop Conference Series: Materials Science and Engineering
Issue Number	1
Volume Number	993
Language	English
Publisher	IOP Publishing
Publisher Date	2020-12-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Materials Science and Engineering Information Systems Whale Swarm Optimizer Optimization Algorithms
Content Type	Text
Resource Type	Article

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