Adaptive Neuro Fuzzy Inference System Optimization by Genetic Algorithm pada Time Series
نویسندگان
چکیده
<p class="Abstract">Abstrak: Data deret waktu adalah serangkaian pengamatan yang diambil secara berurutan dari ke waktu. Salah satu kegunaan data <em>time series</em> untuk <em>forecasting</em>, yaitu memprediksi kemungkinan akan terjadi di masa datang berdasarkan lalu. metode dapat digunakan series forecasting</em> <em>Adaptive Neuro Fuzzy Inference System</em> (ANFIS). Namun, ANFIS memiliki keterbatasan dalam memilih hiperparameternya. Keterbatasan ini diatasi dengan optimasi<em> Genetic Algorithm</em> (GA) sehingga penulis mengajukan dan dioptimasi GA. penelitian konsumsi pemakaian listrik. Penelitian bertujuan mengetahui bagaimana performa algoritma GA mengoptimasi nilai RMSE sebagai acuannya. Setelah dilakukan empat eksperimen pada ANFIS, peneliti mendapatkan hasil minimum 0,2323 <em>test</em> menggunakan <em>electricity consumption </em><em>E</em><em>uropean</em><em> high</em>. Untuk ANFIS-GA, juga terkecil test 0,2018; populasi = 100, mutasi 0,01 crossover 0,5 </em><em>S</em><em>iberian </em><em>low</em>.</p>
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ژورنال
عنوان ژورنال: DoubleClick
سال: 2022
ISSN: ['2579-5317']
DOI: https://doi.org/10.25273/doubleclick.v6i1.13368