scholarly journals PENGGUNAAN MOVING AVERAGE DENGAN METODE HYBRID ARTIFICIAL NEURAL NETWORK DAN FUZZY INFERENCE SYSTEM UNTUK PREDIKSI CUACA

2016 ◽  
Vol 1 (02) ◽  
Author(s):  
Fahrur Rozi ◽  
Farid Sukmana
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Moving Average ◽  
Inference System ◽  
System Data ◽  
Artificial Neural ◽  
Hybrid Artificial Neural Network

<p class="Abstract">Kebutuhan akan prediksi sangat diperlukan diberbagai sektor kehidupan, salah satunya adalah mengenai prediksi cuaca. Prediksi mengenai cuaca dapat dilakukan dalam rentang waktu tertentu, sehingga untuk dapat memprediksi keadaan cuaca dalam rentang waktu tertentu penelitian ini akan menggunakan moving average dengan metode hybrid artificial neural network dan fuzzy inference system. Data yang digunakan berasal dari BMKG Karangploso, Malang dengan menggunakan empat buah parameter yang mempengaruhi kondisi cuaca, yaitu suhu, tekanan udara, kelembapan udara, dan kecepatan angin. Performa model menghasilkan tingkat akurasi mencapai 73.91 %.</p>

scholarly journals Inverse Kinematic Solution of 5R Manipulator using ANN and ANFIS

2015 ◽  
Vol 4 (2) ◽  
pp. 109
Author(s):  
Panchand Jha
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fuzzy Inference System ◽  
Inverse Kinematics ◽  
Fuzzy Inference ◽  
Robot Manipulator ◽  
Ann Model ◽  
Inference System ◽  
Artificial Neural ◽  
Neural Fuzzy

<span>Inverse kinematics of manipulator comprises the computation required to find the joint angles for a given Cartesian position and orientation of the end effector. There is no unique solution for the inverse kinematics thus necessitating application of appropriate predictive models from the soft computing domain. Artificial neural network and adaptive neural fuzzy inference system techniques can be gainfully used to yield the desired results. This paper proposes structured artificial neural network (ANN) model and adaptive neural fuzzy inference system (ANFIS) to find the inverse kinematics solution of robot manipulator. The ANN model used is a multi-layered perceptron Neural Network (MLPNN). Wherein, gradient descent type of learning rules is applied. An attempt has been made to find the best ANN configuration for the problem. It is found that ANFIS gives better result and minimum error as compared to ANN.</span>

Modeling of rheological behavior of honey using genetic algorithm–artificial neural network and adaptive neuro-fuzzy inference system

2015 ◽  
Vol 9 ◽  
pp. 60-67 ◽  
Author(s):  
Marziyeh Ramzi ◽  
Mahdi Kashaninejad ◽  
Fakhreddin Salehi ◽  
Ali Reza Sadeghi Mahoonak ◽  
Seyed Mohammad Ali Razavi
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Rheological Behavior ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Artificial Neural
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