Results 201 to 210 of about 31,665 (232)

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
openaire   +1 more source

Bayesian inference using an adaptive neuro-fuzzy inference system

Fuzzy Sets and Systems, 2023
Mohammed Knaiber, Leen Alawieh
openaire   +1 more source

Designing an Adaptive Neuro Fuzzy Inference System for Prediction of Customers Satisfaction

Journal of Information & Knowledge Management, 2016
Nowadays, in order to succeed in business and presence in the world markets, it is essential to outperform the competitors to get bigger market share. To get customers satisfaction of products is the first stage of success in business. Studying the different factors involved in increasing the level of customer's satisfaction and researching in this ...
Mehdi Neshat, Ali Akbar Pourahmad, Mohammad Reza Hasani   +2 more
openaire   +2 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
openaire   +2 more sources

Neural Networks, Fuzzy Inference Systems and Adaptive-Neuro Fuzzy Inference Systems for Financial Decision Making

2006
This paper employs pattern classification methods for assisting investors in making financial decisions. Specifically, the problem entails the categorization of investment recommendations. Based on the forecasted performance of certain indices, the Stock Quantity Selection Component is to recommend to the investor to purchase stocks, hold the current ...
Pretesh B. Patel, Tshilidzi Marwala
openaire   +1 more source

Extraction of Fetal Electrocardiogram Using Adaptive Neuro-Fuzzy Inference Systems

IEEE Transactions on Biomedical Engineering, 2007
In this paper, we investigate the use of adaptive neuro-fuzzy inference systems (ANFIS) for fetal electrocardiogram (FECG) extraction from two ECG signals recorded at the thoracic and abdominal areas of the mother's skin. The thoracic ECG is assumed to be almost completely maternal (MECG) while the abdominal ECG is considered to be composite as it ...
openaire   +2 more sources

An Adaptive Neuro-Fuzzy Inference System for Diagnosis of Aphasia

2008 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008
Aphasia is a language disability that has several subdivisions such as Anomic, Broca, Global, and Wernicke. Some reasons such as dissension in description of aphasia and its symptoms, large number of test items which are not quite accurate, linguistic ambiguity and uncertainty as well as typical complexities of medical diagnosis cause accurate ...
Sepideh Fazeli, Maryam Naghibolhosseini, Fariba Bahrami   +2 more
openaire   +1 more source

Adaptive Neuro Fuzzy Inference System for Extraction of fECG

2005 Annual IEEE India Conference - Indicon, 2006
Fetal ECG (IECG) monitoring enables accurate measurement of fetal cardiac performance including transient or permanent abnormalities of rhythm. Thie fetal signal obtained from the maternail abdomnen is mixed with much interference. The major source of this interference is maternal ECG (mECG).
C. Kezi Selva Vijila, P. Kanagasabapathy, S. Johnson   +2 more
openaire   +1 more source

Adaptive Neuro-Fuzzy Inference Systems for Automatic Detection of Breast Cancer

Journal of Medical Systems, 2008
This paper intends to an integrated view of implementing adaptive neuro-fuzzy inference system (ANFIS) for breast cancer detection. The Wisconsin breast cancer database contained records of patients with known diagnosis. The ANFIS classifiers learned how to differentiate a new case in the domain by given a training set of such records.
openaire   +3 more sources

Comparative evaluation of adaptive fuzzy inference system and adaptive neuro-fuzzy inference system for mandatory lane changing decisions on freeways

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 2022
Matthew Vechione, Ruey Long Cheu
exaly