Sharif Digital Repository

This study implements an adaptive neuro-fuzzy inference system (ANFIS) approach to predict the precipitation amount of the asphaltene using temperature (T), dilution ratio (Rv), and molecular weight of different n-alkanes. Results are then evaluated using graphical and statistical error analysis methods, confirming the model’s great ability for appropriate prediction of the precipitation amount. Mean squared error and determination coefficient (R2) values of 0.036 and 0.995, respectively are obtained for the proposed ANFIS model. Results are then compared to those from previously reported correlations revealing the better performance of the proposed model. © 2018, © 2018 Taylor & Francis... 

Content-based image retrieval (CBIR) makes use of low-level image features, such as color, texture and shape, to index images with minimal human interaction. Considering the gap between low-level image features and the high-level semantic concepts in the CBIR, we proposed an image retrieval system for brain magnetic resonance images based on saliency map. The saliency map of an image contains important image regions which are visually more conspicuous by virtue of their contrast with respect to surrounding regions. First, the proposed approach exploits the ant colony optimization (ACO) technique to measure the image's saliency through ants' movements on the image. The textural features are... 

Content-based image retrieval (CBIR) makes use of image features, such as color, texture or shape, to index images with minimal human intervention. Content-based image retrieval can be used to locate medical images in large databases. In this paper, the fundamentals of the key components of content-based image retrieval systems are introduced first to give an overview of this area. Then, a case study which describes the methodology of a CBIR system for retrieving human brain magnetic resonance images, is presented. The proposed method is based on Adaptive Neuro-fuzzy Inference System (ANFIS) learning and could classify an image as normal and tumoral. This research uses the knowledge of CBIR... 

In recent years, Iran has experienced many landslides due to high tectonic activity, and a variety of geological and climatic conditions. This paper proposes a novel hybrid model based on step-wise weight assessment ratio analysis (SWARA) method and adaptive neuro-fuzzy inference system (ANFIS) to evaluate landslide susceptible areas using geographical information system (GIS). At first, based on an inventory map, landslide locations were randomly divided into two parts, 70% of which were used for generating the landslide hazard map and 30% of which were used for the validation of the model. Then, twelve landslide predisposing factors, such as lithology, slope angle, slope aspect, plan... 

Due to the presence of excessive noise in the recorded partial discharge (PD) current signals, de-noising of these signals is a crucial task for performing any investigation on the subject. Meanwhile, to accelerate this de-noising process a single PD pulse can be extracted from the train of those recorded pulses, followed by its de-noising. In this paper a single PD pulse is extracted from the train of recorded PD pulses, using noisy recorded data cumulative energy. A de-noising technique based on adaptive neuro-fuzzy inference systems is proposed. To verify the validity of the proposed method, four different sources of PD signals are physically simulated. The proposed method is applied on... 

Asphaltene precipitation in petroleum industries is known as major problems. To solve problems there are approaches for inhibition of asphaltene precipitation, Asphaltene inhibitors are known effective and economical approach for inhibition and prevention of asphaltene precipitation. In the present study Adaptive neuro-fuzzy inference system (ANFIS) was coupled with Particle swarm optimization (PSO) to create a novel approach to predict effect of inhibitors on asphaltene precipitation as function of crude oil properties and concentration and structure of asphaltene inhibitors.in order to training and testing the algorithm, a total number of 75 experimental data was gathered from the... 

In the open-pit mines and civil projects, drilling and blasting is the most common method for rock fragmentation aims. This article proposes a new hybrid forecasting model based on firefly algorithm, as an algorithm optimizer, combined with the adaptive neuro-fuzzy inference system for estimating the fragmentation. In this regard, 72 datasets were collected from Shur river dam region, and the required parameters were measured. Using the different input parameters, six hybrid models were constructed. In these models, 58 and 14 data were used for training and testing, respectively. The proposed hybrid models were then evaluated in accordance with statistical criteria such as coefficient of... 

One of the important parameters in economic study of energy sources and bioenergy is higher heating value (HHV). In this investigation, adaptive neuro fuzzy inference system (ANFIS) was applied as a novel method to predict HHV of biomass in terms of fixed carbon (FC), ash content (ASH), and volatile matters (VMs). Due to the fact that experimental investigations are time- and cost-consuming, this investigation was selected purely computational and a total number of 350 experimental data were extracted from literature for different steps of modeling. The proposed algorithm was evaluated by statistical indexes such as coefficient of determination (R2), root mean squared error (RMSE), and... 

In this paper, dynamic modelling and control of WindPACT 1.5 MW wind turbine in Region 2 for extracting the maximum energy from wind is investigated (where the wind velocity is greater than ‘cut in’ and below ‘rated’ wind speeds). In this region, the generator torque must regulate the rotor speed in its optimal value while the blade pitch angle is considered constant in its optimal value. To achieve a more accurate model, wind turbine is modeled as an electromechanical system with two masses dynamics. A new method based on adaptive neuro fuzzy inference system (ANFIS) is considered for wind speed estimation; where rotor speed, output power and pitch angle are inputs of such system and... 

A novel UWB MIMO antenna with band-notched characteristic operating in the frequency range between 3.1 GHz and 10.6 GHz is presented. The designed MIMO antenna has two ports and the size of 32×14 mm2 which is fabricated on an FR-4 printed-circuit-board. The feeding system of the proposed antenna is a microstrip line. The two antennas are positioned face to face but laid reversely upon the substrate in order to have a good isolation, less cross polarization, high gain and good envelope correlation coefficient. S-parameters describe the input-output relationship between ports (or terminals) in a MIMO antenna. The effects of the strip feed line width on the variations in reflection coefficient... 

This paper presents a comparative study of various soft computing algorithms for reconstruction of neutron noise sources in the nuclear reactor cores. To this end, the computational code for reconstruction of neutron noise source is developed based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), Radial Basis Function (RBF) and Support Vector Machine (SVM) algorithms. Neutron noise source reconstruction process using the developed computational code consists of three stages of training, testing and validation. The information of neutron noise sources and induced neutron noise distributions are used as output and input data of training stage, respectively. As input... 

Integrating humans and robotics technology into one system offers multiple opportunities for creating assistive technologies that can be employed in biomechanical, industrial, and aerospace applications. The present study deals with employing the adaptive neuro-fuzzy inference system (ANFIS) approach in rule base derivation for powered exoskeleton intelligent control to assist paraplegic patient mobility. By employing the hybrid learning algorithm, optimal distributed membership functions to describe the mapping relation in the input and output parameters of the gait cycle were derived. As the proposed control strategy was unaffected by changing human dynamics, the reliability and robustness... 

Electromyogram (EMG) signal is an electrical manifestation of muscle contractions. EMG signal collected from surface of the skin, a non-invasive bioelectric signal, can be used in different rehabilitation applications and artificial extremities control. This study has proposed to utilize the surface EMG (SEMG) signal to recognize patterns of hand prosthesis movements. It suggests using an adaptive neuro-fuzzy inference system (ANFIS) to identify motion commands for the control of a prosthetic hand. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP) and least mean square (LMS) is utilized. Also in order to optimize the number of fuzzy rules, a...