Relevant bibliographies by topics / Adaptive Neural Network Fuzzy Inference System / Dissertations / Theses
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Dissertations / Theses on the topic 'Adaptive Neural Network Fuzzy Inference System'

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Published: 3 June 2025
Last updated: 20 July 2025

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1

Weeraprajak, Issarest. "Faster Adaptive Network Based Fuzzy Inference System." Thesis, University of Canterbury. Mathematics and Statistics, 2007. http://hdl.handle.net/10092/1234.

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It has been shown by Roger Jang in his paper titled "Adaptive-network-based fuzzy inference systems" that the Adaptive Network based Fuzzy Inference System can model nonlinear functions, identify nonlinear components in a control system, and predict a chaotic time series. The system use hybrid-learning procedure which employs the back-propagation-type gradient descent algorithm and the least squares estimator to estimate parameters of the model. However the learning procedure has several shortcomings due to the fact that * There is a harmful and unforeseeable influence of the size of the pa
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Funsten, Brad Thomas Mr. "ECG Classification with an Adaptive Neuro-Fuzzy Inference System." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1380.

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Heart signals allow for a comprehensive analysis of the heart. Electrocardiography (ECG or EKG) uses electrodes to measure the electrical activity of the heart. Extracting ECG signals is a non-invasive process that opens the door to new possibilities for the application of advanced signal processing and data analysis techniques in the diagnosis of heart diseases. With the help of today’s large database of ECG signals, a computationally intelligent system can learn and take the place of a cardiologist. Detection of various abnormalities in the patient’s heart to identify various heart diseases
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Jahankhani, Pari. "Development of a decision support framework for electroencephalography signals based on an adaptive fuzzy inference neural network system." Thesis, University of Westminster, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507837.

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Aslan, Muhittin. "Modeling The Water Quality Of Lake Eymir Using Artificial Neural Networks (ann) And Adaptive Neuro Fuzzy Inference System (anfis)." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610211/index.pdf.

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Lakes present in arid regions of Central Anatolia need further attention with regard to water quality. In most cases, mathematical modeling is a helpful tool that might be used to predict the DO concentration of a lake. Deterministic models are frequently used to describe the system behavior. However most ecological systems are so complex and unstable. In case, the deterministic models have high chance of failure due to absence of priori information. For such cases black box models might be essential. In this study DO in Eymir Lake located in Ankara was modeled by using both Artificial Neural
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Ollé, Tamás. "Klasifikace vzorů pomocí fuzzy neuronových sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219728.

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Práce popisuje základy principu funkčnosti neuronů a vytvoření umělých neuronových sítí. Je zde důkladně popsána struktura a funkce neuronů a ukázán nejpoužívanější algoritmus pro učení neuronů. Základy fuzzy logiky, včetně jejich výhod a nevýhod, jsou rovněž prezentovány. Detailněji je popsán algoritmus zpětného šíření chyb a adaptivní neuro-fuzzy inferenční systém. Tyto techniky poskytují efektivní způsoby učení neuronových sítí.
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Mohammadzadeh, Soroush. "System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/868.

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"Maintaining an efficient and reliable infrastructure requires continuous monitoring and control. In order to accomplish these tasks, algorithms are needed to process large sets of data and for modeling based on these processed data sets. For this reason, computationally efficient and accurate modeling algorithms along with data compression techniques and optimal yet practical control methods are in demand. These tools can help model structures and improve their performance. In this thesis, these two aspects are addressed separately. A principal component analysis based adaptive neuro-fuzzy in
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Lau, Chun Yin. "Extended adapative [i.e. adaptive] neuro-fuzzy inference systems." Access electronically, 2006. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20070130.170625/index.html.

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Xu, Andong. "Flexible adaptive-network-based fuzzy inference system." Diss., Online access via UMI:, 2006.

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Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Dept. of Systems Science and Industrial Engineering, 2006.<br>Includes bibliographical references.
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Vasilic, Slavko. "Fuzzy neural network pattern recognition algorithm for classification of the events in power system networks." Diss., Texas A&M University, 2004. http://hdl.handle.net/1969.1/436.

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This dissertation introduces advanced artificial intelligence based algorithm for detecting and classifying faults on the power system transmission line. The proposed algorithm is aimed at substituting classical relays susceptible to possible performance deterioration during variable power system operating and fault conditions. The new concept relies on a principle of pattern recognition and detects the existence of the fault, identifies fault type, and estimates the transmission line faulted section. The approach utilizes self-organized, Adaptive Resonance Theory (ART) neural network, combin
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Štechová, Edita. "Application of the Artificial Intelligence in the Real Estate Valuation." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-192596.

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The main purpose of this study is to develop a predictive model capable to forecast residential real estate prices in the city of Prague using Artificial Intelligence methods. The first part of this study discusses fundamentals of Artificial Neural Networks and Fuzzy Inference Systems in the context of real estate valuation. The second part demonstrates a development and testing of such models using a dataset of real estate market transactions. In the third part, results are compared to Multiple Regression and an explanatory power of each model is evaluated. Conclusions of this research are: (
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Cakit, Erman. "Investigating The Relationship Between Adverse Events and Infrastructure Development in an Active War Theater Using Soft Computing Techniques." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5777.

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The military recently recognized the importance of taking sociocultural factors into consideration. Therefore, Human Social Culture Behavior (HSCB) modeling has been getting much attention in current and future operational requirements to successfully understand the effects of social and cultural factors on human behavior. There are different kinds of modeling approaches to the data that are being used in this field and so far none of them has been widely accepted. HSCB modeling needs the capability to represent complex, ill-defined, and imprecise concepts, and soft computing modeling can deal
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Ara?jo, J?nior Jos? Medeiros de. "Identifica??o n?o linear usando uma rede fuzzy wavelet neural network modificada." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15249.

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Made available in DSpace on 2014-12-17T14:55:19Z (GMT). No. of bitstreams: 1 JoseMAJ_TESE.pdf: 3560157 bytes, checksum: 2f20316c7b980a74bdb7b82e97e3bb43 (MD5) Previous issue date: 2014-03-24<br>Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico<br>In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning abili
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Cho, B. "Control of a hybrid electric vehicle with predictive journey estimation." Thesis, Cranfield University, 2008. http://hdl.handle.net/1826/2589.

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Battery energy management plays a crucial role in fuel economy improvement of charge-sustaining parallel hybrid electric vehicles. Currently available control strategies consider battery state of charge (SOC) and driver’s request through the pedal input in decision-making. This method does not achieve an optimal performance for saving fuel or maintaining appropriate SOC level, especially during the operation in extreme driving conditions or hilly terrain. The objective of this thesis is to develop a control algorithm using forthcoming traffic condition and road elevation, which could be fed fr
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"On implementation and applications of the adaptive-network-based fuzzy inference system." Chinese University of Hong Kong, 1994. http://library.cuhk.edu.hk/record=b5888200.

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Lai, Wei-Jia, and 賴偉嘉. "Predicting Photochemical Pollutants in Taoyuan Area Using Adaptive Network Based Fuzzy Inference System and Backpropagation Neural Network." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/54865040070692536139.

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碩士<br>朝陽科技大學<br>環境工程與管理系碩士班<br>100<br>This study employed adaptive network based fuzzy inference system (ANFIS) and Back-Propagation Neural Network (BNN) method to establish an air quality prediction model of Taoyuan area .Variable factors used Ozone, Temp, Wind direc, Wind speed, Nitrogen oxides, Nitric oxide, Nitrogen dioxide, Sulfur dioxide. We input data between January and November, 2011 as parameters to establish an optimizing network to predict the air quality of O3 and NOx on December, 2011. BNN research shows that the best mean absolute percentage error (MAPE) 14.92% by using three i
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Nein, Hsiao-Chen, and 粘孝溱. "Adaptive neural fuzzy inference system based data rate and powercontroller for cognitive radio mobile wireless network." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/61390454367640104551.

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碩士<br>元智大學<br>通訊工程學系<br>99<br>In this paper, an adaptive neural fuzzy inference system (ANFIS)based data rate and power controller (DRPC) for cognitive radio (CR)mobile wireless network is proposed to enable flexible, efficient and reliable resource management. The proposed DRPC consists of a cascaded data rate controller (DRC) and a power controller (PC). The optimization objective of the proposed DRPC is to maximize the average throughput of the mobile wireless network and to minimize the transmit power.Simulation results show that the ANFIS-DRPC combined with the priority-based bandwidth al
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Hsu, Yi-Ling, and 許意鈴. "An Application of Grey System, Neural Network and Adaptive Network-based Fuzzy Inference System on the Prediction of Mutual Fund NAV." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/74980245844089674973.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>91<br>Nowadays, investment and financial management become epidemic. All the channels for investment related have become necessary for modern people. The percentage of the investment in stock markets involved by professional organizations increases gradually. With the active participation of professional cooperation, the condition of the domestic stock market has been transformed. In the future, professional management in investment and finance will become a trend, due to mature in stock markets, boom of the listed companies and complex correlation in global financia
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Chen, Chien-Ku, and 陳建谷. "Application Comparison of Neural Network and Adaptive Neural Fuzzy Inference System to the Forecasting of Flue gas quality of incineration plants." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/08963646981076310847.

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碩士<br>國立雲林科技大學<br>環境與安全工程系碩士班<br>91<br>In Taiwan, the existing landfill sites reach saturation population density arising and human activities. The thermal treatment process of solid waste will be the most an important method in the future. Because of the secondary pollution generation by combustion thermal process will result in the pollution problem of ambient environment. Specially, the emission of the flue gas will influence ambient gas quality and human health. Gas pollution emission control becomes a major consideration in the design and operation of incineration plants. In recent year
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Yang, Renpei, and 楊人霈. "Comparison Between The Neural Network And Adaptive Neuro-Fuzzy Inference System For The Optimal Design Of Reinforced Concrete Beams." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/66235375874377152650.

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碩士<br>義守大學<br>土木與生態工程學系<br>100<br>This paper first works on the optimal design of reinforced concrete beams using the genetic algorithm. Given conditions are the span, dead and live loads, compressive strength of concrete and yield strength of steel. Single tensile reinforcement and No. 3 vertical stirrups are adopted. The strength requirements of the maximum positive and negative moments and shear as well as the service requirement of deflection are considered. The constraints are built based on the local reinforced concrete design code and the objective function is the total cost of the stee
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Popoola, Olawale Muhammed. "Adaptive neuro-fuzzy inference system (ANFIS)-based modelling of residential lighting load profile." 2015. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1001770.

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D. Tech. Electrical Engineering.<br>Aims of this study is to develop a residential customers' lighting profile ANFIS-based model. This model is expected to address lighting load usage estimation in relation to the dynamic occupancy presence in a residential dwelling, which will take into account the climatic condition (natural lighting) of such an environment (e.g. South Africa) and its income. The objectives are as follows: 1. Develop an ANFIS-based residential lighting load profile model for middle income, low income and high-income earners. 2. Error reduction in residential lighting demand
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Chung, Cheng-Long, and 鍾政隆. "On the Design of Adaptive Image Watermarking Based on Human Visual System, Neural Networks, and Fuzzy Inference Systems." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/84876097539616276151.

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Wang, Yu-Hsuan, and 王宇軒. "Application of a scooter fault diagnosis system using fuzzy-logic inference and neural networks with adaptive order tracking technique." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/93045823007896041429.

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碩士<br>國立彰化師範大學<br>車輛與軌道技術研究所<br>94<br>In the present study, a fault diagnosis system using acoustic emission with adaptive order tracking technique, fuzzy-logic interference and neural networks for scooter platform is described. Order tracking of acoustic or vibration signal is a well-known technique that can be used for fault diagnosis of rotating machinery. Unfortunately, most of the conventional order-tracking methods are primarily based on Fourier analysis with the revolution of the machinery, the frequency smearing effect is often arises in some critical conditions. In the present study,
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Nguyen, Huy Huynh. "A neural fuzzy approach to modeling the thermal behavior of power transformers." Thesis, 2007. https://vuir.vu.edu.au/1495/.

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This thesis presents an investigation and a comparative study of four different approaches namely ANSI/IEEE standard models, Adaptive Neuro-Fuzzy Inference System (ANFIS), Multilayer Feedforward Neural Network (MFNN) and Elman Recurrent Neural Network (ERNN) to modeling and prediction of the top and bottom-oil temperatures for the 8 MVA Oil Air (OA)-cooled and 27 MVA Forced Air (FA)-cooled class of power transformers. The models were derived from real data of temperature measurements obtained from two industrial power installations. A comparison of the proposed techniques is presented for pred
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I-Hsieh, Shih, and 施宜協. "An Application of Grey Prediction , Markov GM(1,1) and Adaptive Network-based Fuzzy Inference System on the Management of Market Neutral-Security Hedge Fund." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/86230834252525520163.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>92<br>The 21st century in Taiwan will be confronted with trends relating to liberalization and internationalization of financial markets. The government pays attention to financial reforms. Therefore, the development of financial innovation is rising and flourishing. The hedge fund industry which seeks absolute returns has experienced enormous growth in the last decade. It is believed that hedge funds will soon become one of the financial investment options in Taiwan. This study is aimed at the electronics stock on the TSEC (1999.1~2003.12, 60 observation
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Patel, Pretesh Bhoola. "A forecasting of indices and corresponding investment decision making application." Thesis, 2007. http://hdl.handle.net/10539/2191.

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Student Number : 9702018F - MSc(Eng) Dissertation - School of Electrical and Information Engineering - Faculty of Engineering and the Built Environment<br>Due to the volatile nature of the world economies, investing is crucial in ensuring an individual is prepared for future financial necessities. This research proposes an application, which employs computational intelligent methods that could assist investors in making financial decisions. This system consists of 2 components. The Forecasting Component (FC) is employed to predict the closing index price performance. Based on these predi
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Lian, Ying-Ying, and 連螢瑩. "Analysis of physiological signals using adaptive neural-fuzzy inference system." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/8k7h68.

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碩士<br>國立臺北科技大學<br>電機工程系研究所<br>98<br>The measured physiological signals are often contaminated due to fluid flow and surrounding environment. In order to extract effective use of physiological signals become an important research topic in signal processing. This paper uses adaptive neural-fuzzy system (ANFIS) to process physiological signals, mainly divided into two parts：(1) Using ANFIS for fetal ECG extraction from abdominal ECG which contains maternal ECG and various sources of interferences. (2) Using ANFIS in polysomnography analysis: estimate the interferences and to separate the EEG sign
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Chen, Young-Jeng, and 陳永鎮. "Neural-Network-Based Fuzzy Inference System and Its Application on Fuzzy Modeling." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/46734390467494760257.

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碩士<br>國立交通大學<br>控制工程系<br>82<br>In this thesis, we study the neural-network-based fuzzy inference systems. To realize the rule reasoning of fuzzy inference systems, two fuzzy neural networks, the FNN and NFNN, are presented in this thesis. The proposed fuzzy neural networks can acquire the fuzzy logical rules by employing the learning capability of neural networks. Moreover, for simplifying the structures of the proposed fuzzy neural networks, the redundan
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Chen, Chi-Ming, and 陳啟銘. "Adaptive Network-Based Fuzzy Inference System for Driving Status Analysis." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/49789636410910847334.

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碩士<br>長庚大學<br>電機工程研究所<br>95<br>This thesis proposes an intelligent system which analyzes driving status. The system infrastructure is utilized two fixed cameras on the host vehicle. One is used to capture driver’s image in order to analyze driver’s sight line, and the other is used to capture image of road ahead for analyzing driving pattern. In the section of driver’s image, it’s necessary to utilize AdaBoost algorism to recognize face and then get the positions of eyes, nose and lips to diagnose the angles of driver’s head and driver’s sight line. In the section of road image, it’s used edge
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Tai, Gay-Ping, and 田佳平. "Application of Adaptive Neural Fuzzy Inference System to Construct A Fuzzy Power System Stabilizer Automatically." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/09187185118634763683.

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碩士<br>義守大學<br>電機工程學系<br>92<br>This thesis presents an approach to construct fuzzy power system stabilizer，s（FPSS，S） membership functions as well as fuzzy rules automatically. The proposed method contains two stages. Firstly, a set of training data is obtained from the proportional-derivative (PD) PSS of simulation results. This data can be considered as expert experience. Secondly, this training data is fed into the Adaptive Neural Fuzzy Inference System (ANFIS) so as to determine the membership functions and fuzzy rules of FPSS automatically. The whole design process can be done wi
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Han-LungLin and 林漢龍. "Application of Adaptive Neural Fuzzy Inference System in Sleep Apnea Diagnosis." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/76048989132712442740.

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碩士<br>國立成功大學<br>工程科學系<br>103<br>Sleep apnea has become one of the most significant health problems in recent years. However, because examinations are time consuming and involve high costs, the diagnosis of sleep apnea is limited. The purpose of this thesis is to develop a mathematical prediction model that can identify critical patients who really need to take the examination. The prediction model would be extremely helpful in increasing the effectiveness of sleep centers. This research used the questionnaire scores and clinical data of patients, which includes anthropometric measurements, the
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Huang, Tai-Ying, and 黃泰穎. "Using Adaptive Network-Based Fuzzy Inference System to forecast the TAIEX." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/kv597x.

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Chi-HungJhu and 朱啟宏. "Application of Adaptive Neural Fuzzy Inference System in Cardio Vascular Disease Diagnosis." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/89368929639441179626.

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碩士<br>國立成功大學<br>工程科學系<br>104<br>Heart disease is one of the top ten causes of death in global, and coronary artery disease (CAD) is the main form of heart disease. Cardiac catheterization gives accurate results, but it is expensive and may be harmful to patients. Non-invasive methods can reduce damage risk but have lower accuracy and other problems like time-consuming and expensive. Therefore, a diagnosis method that is accurate, cost-effective, and time-saving is desirable. In this thesis, a model that uses an adaptive neural fuzzy inference system (ANFIS) is presented, which is able to buil
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Chang, Chun-Wei, and 張峻瑋. "Design and Implementation of an Adaptive Fuzzy Neural Network System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/68614797294833979821.

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碩士<br>淡江大學<br>電機工程學系碩士班<br>102<br>In recent years, fuzzy neural network (FNN) has been developed. But the FNN have two major drawbacks, one is their application domain is limited to the static problem due to their feedforward network structure, and the other is their unable to directly handle the rule uncertainties due to the membership function is a crisp number. To attack this problem, this paper proposes a perturbed fuzzy neural network (PFNN) and recurrent fuzzy neural network (RFNN). Meanwhile, a fuzzy neural network sliding-mode control (FNSMC) system and a fuzzy neural network second-o
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Chang, Ya-Ting, and 張雅婷. "A Study of Adaptive Network-based Fuzzy Inference System for Reservoir Operation." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/73701486579185392239.

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博士<br>國立臺灣大學<br>生物環境系統工程學研究所<br>94<br>Resulting from the continuous increase in water demand and uneven water distribution both on time and space, the efforts of pursuing integrated optimal water resource management become critical. Intelligent control is a state-of-the-art technology that resembles the human thinking process in decision making and strategy learning, and it has been well recognized for its outstanding ability in controlling complex systems In this study, we continue to pursue the novel intelligent control methodology, which includes genetic algorithm (GA), fuzzy theory, and ad
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Lin, Chun-Chung, and 林春欉. "Application of Adaptive Network-Based Fuzzy Inference System to Predict Milling Model." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/79118683883477278995.

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碩士<br>國立高雄第一科技大學<br>機械與自動化工程所<br>94<br>Abstract This thesis presents a prediction model archived by the experiment which collects the data of the average milling surface roughness on center line at end mill, and trained and tested with the adaptive network-based fuzzy inference system (ANFIS). Spindle speed, feed rate, and depth of cut are chose as the input parameters, and average surface roughness on center line is chose as the output parameter. In this thesis, the premise part of the ANFIS is applied by Gauss membership function, and the consequent part is applied by the Takagi-Sugeno (TS)
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Yang, Tsung-wen, and 楊宗文. "Application of Adaptive Network based Fuzzy Inference System in thermal comfort modeling." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/02114027812907663213.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>89<br>The purpose of air conditioner is to provide an environment in which people can feel comfortable. However, most air conditioners can not predict exactly how people feel about for the thermal environment. People always setup temperatures themselves instead of air conditioning devices but it will waste lots of energy if the set point isn’t proper. International Standard Organization (ISO) had defined a model which can be used to predict how people feel based on Fanger’s research in 1970. But the accuracy of Fanger model is under 40 percents after testing by expe
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Lin, Che-Fu, and 林哲甫. "Applying Adaptive-Network-based Fuzzy Inference System in Predicting Construction Project Performance." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/56714012727457099176.

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碩士<br>國立高雄應用科技大學<br>土木工程與防災科技研究所<br>103<br>Construction projects are getting more complex and bigger day by day, also the workload is increased. If early planning is done more properly, it would avoid unnecessary project delays and the cost over-run, make the construction phase more smooth. For construction projects, implementation of early planning is very important. This research investigate the relationship of project pre-planning efforts and project performance. 105 domestic construction projects data are collected. By using the artificial intelligence methods to establish relevant models
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Yu, Chien-hsin, and 游建欣. "A Study of Adaptive Network-based Fuzzy Inference System for TAIEX Prediction." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/92034377928946948849.

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碩士<br>東吳大學<br>經濟學系<br>94<br>There have been a great number of literatures on how to predict TAIEX by the neural networks up to the present, while few of papers have adopted ANFIS to undertake prediction. ANFIS combines the advantage of fuzzy logic and artificial neural network. Fuzzy logic plays a role to formulate the relationship among the input variables, which describe the situation when one signal takes place, and output variables. Artificial neural network is used to train the formulated knowledge by the mass of historical data, and find out the best prediction models. This paper is to s
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Tseng, Yao-Te, and 曾耀德. "Applying Adaptive Fuzzy Neural-based Inference System to the evaluation of warrant market." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/93537430308939502217.

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Hsu, Hsin-Yin, and 許馨尹. "Developing Adaptive In-vehicle Navigation System based on Fuzzy-Neural Network." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/72288843359154949543.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>98<br>Nowadays, the technology on Advanced Traveler Information Systems (ATIS) becomes more and more progressive. This well-developed technology not only keeps travelers from getting lost, but greatly decreases the time people spend on searching the routes to destination. Navigation system provides drivers some choices on selecting routes, for example, shortest time, shortest distance, use of freeways, etc. However, the path which system provides is not always the “optimal” one, since drivers may consider other factors such as familiarity of the route, traffic condit
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Chang, Chih-Hsiang, and 張致祥. "Application of Adaptive Network based Fuzzy Inference System on Predicting Grinding Surface Quality." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/81773302878836662496.

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碩士<br>國立高雄第一科技大學<br>機械與自動化工程所<br>92<br>Grinding is commonly used precision work method in the machining. But in grinding process, grinding parameter, such as the grinding wheel rotational speed, feed rate, depth of cut, grinding wheel grit size often is the influence of work piece quality. In the tradition grinding processing, frequently refers to the technical manual and the operator itself experience, is choosing these parameters by try-and-error method. As this reason, each period of work piece surface quality, often changes because of operator''s difference, and don’t easily control. There
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Chao, Chen, and 曹鎮. "Study on Climate Cycle in Taiwan by Adaptive Network-Based Fuzzy Inference System." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/91736396968469775331.

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博士<br>國立中興大學<br>水土保持學系所<br>97<br>Recent years, the greenhouse effect due to industry and commerce prolonged development has influenced hydrological circulation. In order to realize the situation of Taiwan, this study intends to find the correlations through the principal component analysis, thus, the obvious correlations has found in CO2 emission and temperature; evaporation and sunshine duration; cloud amount and relative humidity. Furthermore, this study calculates the regularized major period in rainfall based on time-series spectral analysis. The maximum monthly rainfall shows approximatel
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Chang, Shu-Chuan, and 張淑娟. "Applying the Adaptive Network-based Fuzzy Inference System Predicts the Ship Intact Stability." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/03740775803443633603.

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碩士<br>國防大學管理學院<br>運籌管理學系<br>101<br>Stability is a critical factor for the ship safety. There are three parameters to evaluate the ship stability, including KG (the distance between the keel and the center of gravity), KM (the distance between the keel and the metacenter) and GM (the distance between the center of gravity and metacenter). We can get the actual value by way of the inclining experiment for those light duty vessels. This thesis combined back-propagation network and Sugeno to form Adaptive Network-Based Fuzzy Inference System (ANFIS) to forecast the intact stability. The results of
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Tzeng, Chih-wei, and 曾治瑋. "To Forecast Automobile Sale in Taiwan Using Adaptive Network-Based Fuzzy Inference System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/43579642446208903153.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>97<br>The demand forecasting of automobile sales is one of critical issues for national economic growth. Our model considers several variables such as current automobile sales quantity, coincident indicator, leading indicator, wholesale price index and income. Here, we only focus on new automobile sales in Taiwan. The data set is based on monthly sales which the data can be divided into three types of automobile sales. Thus, there are two levels in this study. First, we use the stepwise method to select most influential variables as our input variables. Then, we use
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丁士哲. "Application of Adaptive-Network-Based Fuzzy Inference System for Assessment of Postural Stability." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/55061131084680892633.

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碩士<br>國立中興大學<br>機械工程學系<br>91<br>In this study emphasis has been placed on the use of force platform to obtain excursions of center of pressure (COP) and to calculate postural stability. Excursions of COP may include medial-lateral and anterior-posterior movement of the COP in the time series. Beside COP, force platform can also be used to obtain shear force, anterior-posterior COG sway angle, sway area and the area of stability as indices for postural stability assessment. Methods incorporating the fuzzy/adaptive -network-based fuzzy inference system with postural stability indices that captu
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Jun-Yu, Lai, and 賴俊宇. "Applying Adaptive-Network-based Fuzzy Inference System in Predicting Building Construction Project Success." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/74062721319150049797.

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碩士<br>國立高雄應用科技大學<br>土木工程與防災科技研究所<br>101<br>The construction industry plays an important role in a country's development process.In recent years, the construction projects have become very complex. The early planning is very crucial to project performance. As a result, if the early planning is done well, the project execution will be smooth and unnecessary cost escalating and project delay can be avoided. Therefore, how well the early planning is executed will huge impact on project performance. This research is set to examine the relationship between early planning and project performances. In
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Chen, Kai-pei, and 陳楷沛. "Estimating the Examinee Ability on the Computerized Adaptive Testing Using Adaptive Network-Based Fuzzy Inference System." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/utppz2.

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碩士<br>國立中山大學<br>資訊工程學系研究所<br>95<br>Computerized adaptive testing attempts to provide the most suitable question for an examinee depending on the examinee’s ability to achieve the best result. Although Maximum Likelihood Estimation (MLE) and Bayesian Likelihood Estimation (BLE) have been provided to solve ability estimation and have good results in the literature, little attention has been paid to the situation when the answer of an item does not conform with the examinee’s ability as expected nor standard derivation changes of the ability estimation. We hypothesized that the Adaptive-Network-B
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Chen, Yu-Sheng, and 陳裕盛. "Using adaptive network based fuzzy inference system optimize MTS strategy in a MTO environment." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/ekmzd4.

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碩士<br>國立高雄第一科技大學<br>運籌管理所<br>96<br>We hypothesize manufacturer adopt make-to-order(MTO) strategy﹐without information sharing﹐and receive downstream order information which only know arrival time and demand﹒Manufacturer use Adaptive Network based Fuzzy Inference System(ANFIS) to train relation between current downstream order information (including arrival time and demand) and next term arrival time or demand﹒Learning their relation to become IF-THEN rule and using these rules to forecast future downstream order information﹐so that manufacturer can purchase material and prepare MTS strategy ahe
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Kuo-LiTseng and 曾國立. "Integrating the Mega-Trend-Diffusion Technique with the Adaptive Network-Based Fuzzy Inference System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/96167523191574445455.

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碩士<br>國立成功大學<br>高階管理碩士在職專班(EMBA)<br>102<br>The Adaptive Network-Based Fuzzy Inference System (ANFIS) is widely applied to classification and numerical forecasting problems nowadays. Although the ANFIS is developed to obtain the optimal results of FIS with artificial neural networks by adapting the initial antecedent parameters in FIS, the profiles of fuzzy membership functions, how to well set the initial antecedent parameters still can affect the learning results. Focusing on the numerical forecasting problems, this study develops a systematic procedure, which employs the Fuzzy C-means with t
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Hsiao, Wei-Chieh, and 蕭維頡. "Application of Kalman Filter and Adaptive-Network-Based Fuzzy Inference System in Indoor Localization." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/11884914828064826829.

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碩士<br>東海大學<br>工業工程與經營資訊學系<br>102<br>Location-based services are widely integrated in our lives, such as inventory management, personal tracking or healthcare. With increasing applications of wireless localization, accuracy and stability of location estimation have become more critical. However, indoor localization suffers from multipath interference that affects traditional algorithm based on received signal strength indicator (RSSI). In this research, an indoor localization algorithm which combined Kalman filter and adaptive-network-based fuzzy inference system (ANFIS) was proposed. This loca
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