Skripsi

PRAKIRAAN CUACA MENGGUNAKAN JARINGAN HOPFIELD YANG DIOPTIMASI DENGAN PARTICLE SWAARM OPTIMIZATION

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Penilaian

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Weather forecasting is one of the application of science and technology to determine the atmosphere condition at certain area in the future. Weather forecast using the Hopfield network was choosen in this weather forecasting problem because Hopfield has the ability to store information that has been given and it can select the pattern that most closely matches its memory. Hopfield has difficulty in finding the right weight value to produce a convergent network. Therefore, Particle Swarm Optimization is used to optimize the weight value. This study compares the Hopfield network and the Hopfield network that are optimized with Particle Swarm Optimization to obtain the most accurate weather forecasts. Based on the results of testing weather forecasts using Hopfield which is optimized with Particle Swarm Optimization, it produces an accuracy of 75.068% while Hopfield without optimization produces an accuracy of 58.082%. Keywords: Artificial Neural Networks, Hopfield, Particle Swarm Optimization, Weather Forecast

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2007000852	T39194	T391942020	Central Library (REFERENSI)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T391942020

Publisher

Inderalaya : Fakultas Ilmu Komputer., 2020

Collation

xv, VI-2 hlm.; ilus., tab.: 28 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Particle Swarm Optimization
Teknik Informatika
Jaringan Hopfield

Specific Detail Info

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Statement of Responsibility

EM

Other version/related

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