Results 191 to 200 of about 12,863 (232)

An adaptive neuro-fuzzy inference system for bridge risk assessment

Expert Systems with Applications, 2008
Bridge risks are often evaluated periodically so that the bridges with high risks can be maintained timely. This paper develops an adaptive neuro-fuzzy system (ANFIS) using 506 bridge maintenance projects for bridge risk assessment, which can help Highways Agency to determine the maintenance priority ranking of bridge structures more systematically ...
Ying-Ming Wang 0001, Taha M. S. Elhag
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Analog VLSI implementation of adaptive neuro-fuzzy inference systems

ICECS 2000. 7th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.00EX445), 2002
This paper presents an analog VLSI implementation of adaptive neuro-fuzzy inference systems (ANFIS). Stochastic perturbative techniques, which are more VLSI friendly than standard learning techniques such as back-propagation, are used for on-chip learning. The system is tested by the task of predicting the Mackey-Glass chaotic time series.
Ahmed Sultan, Mohamed El-Sayed
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Design Pattern Recognition by Using Adaptive Neuro Fuzzy Inference System

2013 IEEE 25th International Conference on Tools with Artificial Intelligence, 2013
Software design patterns describe recurring design problems and provide the essence of best practice solutions. It is useful and important, for various software engineering tasks, to know which design pattern is implemented where in a software design.
Sultan Alhusain, Simon Coupland, Robert I. John, Maria Kavanagh   +3 more
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A hybrid of adaptive neuro-fuzzy inference system and genetic algorithm

Journal of Intelligent & Fuzzy Systems, 2013
Premature convergence is an important problem in evolutionary algorithms, in particular genetic algorithm. The diversity of the population is a very influence paprameter on premature convergence in genetic algorithm. In this paper, we attempt to improve the performance of genetic algorithms by providing a bi-linear allocation lifetime approach to label
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Channel Estimation Based on Adaptive Neuro-Fuzzy Inference System in OFDM

IEICE Transactions on Communications, 2008
In this letter we purpose adaptive neuro-fuzzy inference system (ANFIS) for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. To evaluate the performance of this estimator, we compare the ANFIS with least square (LS) algorithm, minimum mean square error (MMSE) algorithm by using bit error rate (BER) and mean square error (
Muhammet Nuri Seyman, Necmi Taspinar
openaire   +3 more sources

GSM Churn Management Using an Adaptive Neuro-Fuzzy Inference System

The 2007 International Conference on Intelligent Pervasive Computing (IPC 2007), 2007
The movement of subscribers from one operator to another operator is named as churn management for looking for better and cheaper products and services. As markets become saturated and competition intensifies, customers have more choices to take promotions from alternative telecom operators in Turkish GSM (Global Services of Mobile Communications ...
Adem Karahoca, Dilek Karahoca, Nizamettin Aydin   +2 more
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APPLICATION OF ADAPTIVE NEURO FUZZY INFERENCE SYSTEM IN THE PROCESS OF TRANSPORTATION SUPPORT

Asia-Pacific Journal of Operational Research, 2013
The possibility for more confidential predictions, leaning on scientific methods and accomplishments of information technology leaves more time for the realization of logistic needs. Longstanding ambitions to acquire desired levels of efficiency within the system with minimal costs of resources, materials, energy and money are the features of ...
Dragan Pamucar, Vesko Lukovac, Snezana Pejcic-Tarle   +2 more
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Realization of an Improved Adaptive Neuro-Fuzzy Inference System in DSP

2007
Scaled conjugate gradient (SCG) algorithm was used to improve adaptive neuro-fuzzy inference system (ANFIS). It's proved by applications in chaotic time-series prediction that the improved ANFIS converges with less time and fewer iterations than standard ANFIS or ANFIS improved with the Fletcher-Reeves update method.
Xingxing Wu, Xilin Zhu, Xiaomei Li, Haocheng Yu   +3 more
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Hysteresis Modeling with Adaptive Neuro-Fuzzy Inference System

Ferroelectrics, 2008
The accurate characterization and modeling of magnetic material are critical in simulating the performance analysis of electrical circuits incorporating magnetic components. In this study, a new approach for modeling hysteresis loop of ferromagnetic material based on adaptive neuro-fuzzy inference system (ANFIS) was presented.
M. Mordjaoui, M. Chabane, B. Boudjema, R. Daira   +3 more
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Adaptive neuro-fuzzy inference system for modelling and control

Proceedings First International IEEE Symposium Intelligent Systems, 2003
A new approach for an adaptive neuro-fuzzy inference system for modeling and control is proposed. This approach uses a general regression neural network with a different learning capability from the classical clustering algorithm normally used by this specific network.
T.G.B. Amaral, M.M. Crisostomo, V.F. Pires   +2 more
openaire   +1 more source