Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during...

Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower. Using the long-term observations of discharges of monthly river flow discharges during 1953-2003, different types of membership functions and antecedent input flo...

Photovoltaic merupakan pembangkit energy listrik terbarukan yang sangat cocok untuk negara trapis banyak mendapat sinar matahari. Akan tetapi ini mempunyai efisiensi masih kecil. Untuk mengatasi kekurangan ini, beberapa peneliti telah megoptimasi dengan metode dual axis tracking solar secara konvensional. Diperlukan penelitian mengoptimasi menggunakan kecerdasan buatan, dalam hal Adaptive Neuro...

Search engines are crucial for information gathering systems (IGS). New challenges face search concerning automatic learning from user requests. In this paper, a new hybrid intelligent system is proposed to enhance the process. Based on Multilayer Fuzzy Inference System (MFIS), first step implement scalable relay logical rules in order produce three classifications behavior, profiles, and query...

In this paper, multi user detection in Code Division Multiple Access (CDMA) was realized with an adaptive neuro-fuzzy inference system (ANFIS) and the bit error rate (BER) performance was compared with the performances of the matched filter and a neural network receiver. Increment of the number of the active users and the receiving various user signals at the receiver input stage in different p...

Parallel robots exhibit good performance in terms of rigidity, accuracy, and dynamic characteristics. However, parallel robots have complex configurations and their dynamic model is highly nonlinear, and conventional PID controllers are not sufficiently robust for their motion control. In this paper, we have investigated the intelligent control of a hydraulically driven parallel robot based on ...

This paper discusses the application of support vector machine in the area of identification of nonlinear dynamical systems. The aim of this paper is to identify suitable model structure for nonlinear dynamic system. In this paper, Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Support Vector Regression (SVR) models are applied for identification of highly nonlinear dynamic process. The res...

Reinforced concrete beam; Shear strength; Artificial neural network; Adaptive neuro-fuzzy inference system; Iranian concrete institute code; American concrete institute code. Abstract In this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to predict the shear strength of Reinforced Concrete (RC) beams, and the models are compared with A...

The cart-and-pendulum system is a highly nonlinear and under-actuated system that is a great source of interest and motivation for researchers all over the world. There are various configurations of the cart-and-pendulum system that finds wide applications in areas of manufacturing, robotics and control. This paper presents an offline mode control of the Flexible Inverted Pendulum (FIP), which ...

non-invasive fetal electrocardiogram (FECG) signal extraction from signals recorded at abdominal area of mother is a challenging problem for the biomedical and signal processing communities. In this paper, we improve the FECG extraction approaches which consist to find the relation-ships between the cardiac potentials generated at the heart level of mother and the potentials recorded on the abd...