PRAKIRAAN CUACA MENGGUNAKAN JARINGAN HOPFIELD YANG DIOPTIMASI DENGAN PARTICLE SWAARM OPTIMIZATION

MAITSA, RIFDAH YUMNA FARHAH and Rini, Dian Palupi and Marieska, Mastura Diana (2020) PRAKIRAAN CUACA MENGGUNAKAN JARINGAN HOPFIELD YANG DIOPTIMASI DENGAN PARTICLE SWAARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

[img] Text
RAMA_55201_09021181621006.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (2MB) | Request a copy
[img] Text
RAMA_55201_09021181621006_TURNITIN.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (5MB) | Request a copy
[img]
Preview
Text
RAMA_55201_09021181621006_0023027804_0021038607_01_front_ref.pdf - Accepted Version
Available under License Creative Commons Public Domain Dedication.

Download (1MB) | Preview
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_02.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (723kB) | Request a copy
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_03.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (469kB) | Request a copy
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_04.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (704kB) | Request a copy
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_05.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (426kB) | Request a copy
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_06.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (203kB) | Request a copy
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_06_ref.pdf - Bibliography
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (323kB) | Request a copy
[img] Text
RAMA_55201_09021181621006_0023027804_0021038607_07_lamp.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (257kB) | Request a copy

Abstract

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

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Artificial Neural Network,Hopfield, Particle Swarm Optimization, Weather Forecast
Subjects: Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Rifdah Yumna Farhah Maitsa
Date Deposited: 04 Jan 2021 05:43
Last Modified: 04 Jan 2021 05:43
URI: http://repository.unsri.ac.id/id/eprint/39194

Actions (login required)

View Item View Item