نتایج جستجو برای: مدلهای rbf و anfis

تعداد نتایج: 768072  

2004
A. JALALI

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track a reference engine rotational speed and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the engine is simulated and simulation results presented. ANFIS implements a first order Sugeno-style fuzzy system. It is a method for tuning an existin...

2011
Murad Shibli

This paper presents an adaptive neural fuzzy inference system (ANFIS) approach to predict the location, occurrence time and the magnitude of earthquakes. The analysis conducted in this paper is based on the principle of conservation of energy and momentum of annual earthquakes which has been validated by analyzing data obtained from United Sates Geographical Survey (USGS). This principle shall ...

Journal: :Expert Syst. Appl. 2013
Ebru Akcapinar Sezer Biswajeet Pradhan Candan Gokceoglu

This note is to point out and correct an error in Sezer et al. (2011). İn the paper (Sezer et al. 2011), the authors mention “ANFIS model has not been used for landslide susceptibility mapping previously”. This statement must be corrected as “The ANFIS model has been applied in landslide susceptibility mapping previously by Pradhan, Sezer, Gokceoglu, and Buchroithner (2010) in a different ...

2006
ABDULKADIR CÜNEYT AYDIN AHMET TORTUM MURAT YAVUZ

The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normaland high-strength concrete was investigated. Results indicate that the proposed ANFIS modeling approach outperforms the other given models in terms of prediction capability. According to ...

2014
Jayesh S. Patel S. S. Singh

Dissolved oxygen (DO) & COD is a parameter frequently used to evaluate the water quality on different rivers. The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in water quality DO & COD prediction for the case study, Mahi river at Khanpur in Thasara Taluka of Kheda District in Gujarat State, I...

Journal: :Earth Science Informatics 2021

Landslide susceptibility analysis is beneficial information for a wide range of applications, including land use management plans. The present attempt has shed light on an efficient landslide mapping framework that involves adaptive neural-fuzzy inference system (ANFIS), which incorporates three metaheuristic methods grey wolf optimization (GWO), particle swarm (PSO), and shuffled frog leaping ...

2007
G. ATSALAKIS

One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines a methodology for consumer demand modeling and prediction in a real-time environment of an irrigation water distribution system. The approach is based on Adaptive Neuro-Fuzzy Inferences System (AN...

2011
V M Varatharaju B L Mathur

The paper presents a methodology for developing adaptive speed controllers in a permanent-magnet brushless DC (BLDC) motor drive system. A proportional-integral controller is employed in order to obtain the controller parameters at each selected load. The resulting data from PI controller are used to train adaptive neuro-fuzzy inference systems (ANFIS) that could deduce the controller parameter...

2004
Seref Naci Engin Janset Kuvulmaz Vasfi Emre Ömürlü

Since liquid tank systems are commonly used in industrial applications, system-related requirements results in many modeling and control problems because of their interactive use with other process control elements. Modeling stage is one of the most noteworthy parts in the design of a control system. Although nonlinear tank problems have been widely addressed in classical system dynamics, when ...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی خواجه نصیرالدین طوسی - دانشکده مهندسی مکانیک 1392

مدل¬سازی وکنترل سیستم¬های پیچیده¬ای که در صنایع مهم وکاربردی مورد استفاده هستند یکی از بحث¬های مهم وکاربردی می¬باشد، و لذا مدل¬سازی و کنترل دقیق آن¬ها بسیار مهم است زیرا هرگونه اشتباه در مدل¬سازی چنین سیستم¬هایی منجر به کنترل غیر دقیق ودر نهایت عملکرد ضعیف می¬گردد. در این نوشتار مدل¬سازی توربین گازی v94.2 زیمنس به صورت یک سیستم دو ورودی و چهار خروجی در نظر گرفته شده است به این صورت که پس از ذخی...

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