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Dissertations / Theses on the topic 'ANFS- adaptive neuro-fuzzy system'

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Published: 4 June 2025

Last updated: 1 August 2025

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1

Guner, Evren. "Adaptive Neuro Fuzzy Inference System Applications In Chemical Processes." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1252246/index.pdf.

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Neuro-Fuzzy systems are the systems that neural networks (NN) are incorporated in fuzzy systems, which can use knowledge automatically by learning algorithms of NNs. They can be viewed as a mixture of local experts. Adaptive Neuro-Fuzzy inference system (ANFIS) is one of the examples of Neuro Fuzzy systems in which a fuzzy system is implemented in the framework of adaptive networks. ANFIS constructs an input-output mapping based both on human knowledge (in the form of fuzzy rules) and on generated input-output data pairs. Effective control for distillation systems, which are one of the importa

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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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Hamdan, Hazlina. "An exploration of the adaptive neuro-fuzzy inference system (ANFIS) in modelling survival." Thesis, University of Nottingham, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594875.

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Medical prognosis is the prediction of the future course and outcome of a disease and an indication of the likelihood of recovery from that disease. Prognosis is important because it is used to guide the type and intensity of the medication administered to patients. Patients are usually concerned with how long they will survive after diagnosis. Survival analysis describes the analysis of data that corresponds to the time from when an individual enters a study until the occurrence of some particular event or end-point. It is concerned with the comparison of survival curves for different combina

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Khanfar, Ahmad A. "Forecasting failure of information technology projects using an adaptive neuro-fuzzy inference system." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2019. https://ro.ecu.edu.au/theses/2262.

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The role of information technology (IT) applications has become critical for organisations in various sectors such as education, health, finance, logistics, manufacturing and project management. IT applications provide many advantages at strategic, management and operational levels, and the investment in IT applications is therefore growing; however, the failure rate of IT projects is still high, despite the development of theories, methodologies and frameworks for IT project management in recent decades. The consequences of failure of an IT project can be devastating, and can threaten the exi

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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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Kiani, Mavi Neda. "Forecasting project success in the construction industry using multi-criteria decision-making tools and adaptive neuro fuzzy inference system." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2024. https://ro.ecu.edu.au/theses/2791.

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The construction industry plays a significant role in the development of economies. This industry in Australia contributed around 20% Australian Trade and Investment Commission (2023) to its gross domestic product (GDP) of over US$1.80 trillion (approximately AUD 2.85 trillion) (OECD, 2023).The federal budget for 2022–23 allocates AUD 17.9 billion over a decade towards major infrastructure projects, encompassing substantial funding for nationwide road and rail projects. The overall investment in major public infrastructure is anticipated to surpass AU$218 billion from 2021 to 2025. Approximate

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Chotikorn, Nattapong. "Implementations of Fuzzy Adaptive Dynamic Programming Controls on DC to DC Converters." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1505139/.

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DC to DC converters stabilize the voltage obtained from voltage sources such as solar power system, wind energy sources, wave energy sources, rectified voltage from alternators, and so forth. Hence, the need for improving its control algorithm is inevitable. Many algorithms are applied to DC to DC converters. This thesis designs fuzzy adaptive dynamic programming (Fuzzy ADP) algorithm. Also, this thesis implements both adaptive dynamic programming (ADP) and Fuzzy ADP on DC to DC converters to observe the performance of the output voltage trajectories.

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8

Jain, Aakanksha. "Application of Artificial Intelligence Techniques in the Prediction of Industrial Outfall Discharges." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39812.

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Artificial intelligence techniques have been widely used for prediction in various areas of sciences and engineering. In the thesis, applications of AI techniques are studied to predict the dilution of industrial outfall discharges. The discharge of industrial effluents from the outfall systems is broadly divided into two categories on the basis of density. The effluent with density higher than the water receiving will sink and called as negatively buoyant jet. The effluent with density lower than the receiving water will rise and called as positively buoyant jet. The effluent discharge in the

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Arsava, Kemal Sarp. "Modeling, Control and Monitoring of Smart Structures under High Impact Loads." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-dissertations/105.

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In recent years, response analysis of complex structures under impact loads has attracted a great deal of attention. For example, a collision or an accident that produces impact loads that exceed the design load can cause severe damage on the structural components. Although the AASHTO specification is used for impact-resistant bridge design, it has many limitations. The AASHTO specification does not incorporate complex and uncertain factors. Thus, a well-designed structure that can survive a collision under specific conditions in one region may be severely damaged if it were impacted by a dif

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10

Spadotto, Marcelo Montepulciano [UNESP]. "Lógica ANFIS aplicada na estimação da rugosidade e do desgaste da ferramenta de corte no processo de retificação plana de cerâmicas avançadas." Universidade Estadual Paulista (UNESP), 2010. http://hdl.handle.net/11449/87176.

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Made available in DSpace on 2014-06-11T19:22:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-07-29Bitstream added on 2014-06-13T19:08:09Z : No. of bitstreams: 1 spadotto_mm_me_bauru.pdf: 1459647 bytes, checksum: c67d870286e648ad917f7e25b8b18d56 (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>A necessidade de aplicação de novos equipamentos em ambientes cada vez mais agressivos demandou a busca por novos produtos capazes de suportar altas temperaturas, inertes às corroções químicas e com alta rigidez mecânica. O avanço tecnógico na produção de materia

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Kuo, Chia-Hung. "THE ANALYSIS OF HIGH FREQUENCY OSCILLATIONS AND SUPPRESSION IN EPILEPTIC SEIZURE DATA." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1396411237.

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Govindasamy, Kannan Wilamowski Bogdan M. "Neuro-fuzzy system with increased accuracy suitable for hardware implementation." Auburn, Ala., 2009. http://hdl.handle.net/10415/1591.

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Hashemifarzad, Ali [Verfasser], and Martin [Akademischer Betreuer] Faulstich. "Electrical load forecasting using adaptive neuro-fuzzy inference system / Ali Hashemifarzad ; Betreuer: Martin Faulstich." Clausthal-Zellerfeld : Technische Universität Clausthal, 2019. http://d-nb.info/1231363088/34.

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França, Daniel cruz de. "Modelagem de um adaptive neuro fuzzy inference system para análise de risco em projetos." Universidade Federal da Paraíba, 2016. http://tede.biblioteca.ufpb.br:8080/handle/tede/8163.

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Submitted by Maike Costa (maiksebas@gmail.com) on 2016-04-29T13:48:06Z No. of bitstreams: 1 arquivo total.pdf: 1906817 bytes, checksum: 6bf3c54782cfdea75b86311d9bc28cb9 (MD5)<br>Made available in DSpace on 2016-04-29T13:48:06Z (GMT). No. of bitstreams: 1 arquivo total.pdf: 1906817 bytes, checksum: 6bf3c54782cfdea75b86311d9bc28cb9 (MD5) Previous issue date: 2016-02-22<br>Several researches highlight the importance of risk management in project management. Many authors propose traditional models with statistical and deterministic methods, though some risk project management issues are ba

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Chintapalli, Sahithi. "Transmission Scheduling Using Adaptive Neuro-Fuzzy Inference System For Minimizing Interference in Wireless Body Area Networks (WBANs)." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447071467.

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16

Forouhari, Mohammadsaleh. "Remnant Life Estimation of Power Transformers Based on Chemical Diagnostic Parameters Using Adaptive Neuro-Fuzzy Inference System." Thesis, Curtin University, 2017. http://hdl.handle.net/20.500.11937/56428.

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Power transformer plays a critical role in the reliability of the electrical networks. Thus, continuous monitoring and management of power transformers is of great importance. This research study aims at developing an integrated life estimation and asset management decision model based on adaptive neuro fuzzy inference system. Implementation of this methodology is expected to project patterns in the practical measurements history of power transformers and to provide utilities with a more reliable asset management tool.

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Shekarriz, Mona. "The foundation of capability modelling : a study of the impact and utilisation of human resources." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/5257.

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This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common ground for assessing individuals’ applied capability in a given job based on literature review of various disciplines in engineering, human sciences and economics. A set of criteria is found to be common and appropriate to be used as the basis of this assessment. Applied Capability is then described in this research as the impact of the person in fulfilling job requirements and also their level of usage from their resources with rega

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18

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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20

Silva, Sanchez Rosa Elvira. "Contribution au pronostic de durée de vie des systèmes piles à combustible PEMFC." Thesis, Besançon, 2015. http://www.theses.fr/2015BESA2005/document.

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Les travaux de cette thèse visent à apporter des éléments de solutions au problème de la durée de vie des systèmes pile à combustible (FCS – Fuel Cell System) de type à « membrane échangeuse de protons » (PEM – Proton Exchange Membrane) et se décline sur deux champs disciplinaires complémentaires :Une première approche vise à augmenter la durée de vie de celle-ci par la conception et la mise en œuvre d'une architecture de pronostic et de gestion de l'état de santé (PHM – Prognostics & Health Management). Les PEM-FCS, de par leur technologie, sont par essence des systèmes multi-physiques (é

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21

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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22

Ho, Tung-Han, and 何東翰. "The Application of Adaptive Neuro-Fuzzy Inference System(ANFIS) for Dynamic Trading Decision Support System-Evidence from TAIEX Stock Index Futures." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/98528710392268342127.

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碩士<br>淡江大學<br>財務金融學系碩士班<br>99<br>Stock market prediction is important because successful prediction of stock prices may promise attractive benefits. Yet, these tasks are highly complicated and very difficult. This thesis extends the Adaptive Neuro-Fuzzy Inference System (ANFIS), to create a trading decision support system that is capable of using fuzzy reasoning combined with the pattern recognition capability of neural networks to be used in forecasting and trading the futures of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). This study, as a result, proposes an approach o

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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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"ADAPTIVE NEURO FUZZY INFERENCE SYSTEM APPLICATIONS IN CHEMICAL PROCESSES." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1252246/index.pdf.

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Chia-Hsiang, Tu. "Adaptive Critic Learning Algorithm of Neuro-Fuzzy Inference System." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-0307200617025800.

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Tu, Chia-Hsiang, and 塗家祥. "Adaptive Critic Learning Algorithm of Neuro-Fuzzy Inference System." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/93846229938334905896.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>94<br>The goal of this research is to develop an adaptive critic neuro-fuzzy inference system (NFIS) for modeling and control. On the backbone of dual heuristic programming (DHP), a DHP adaptive critic learning scheme that utilizes an effective network Jacobian acquisition is proposed. In control applications, the adaptive critic NFIS can learn from scratch to achieve the control objective. In modeling applications, it can approximate arbitrary continuous function through sequential optimization. The learning structure is based on NFIS that contains fuzzy if-then ru

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Hong, Yu-Shiang, and 洪煜翔. "Function Modeling by Using Adaptive Neuro-Fuzzy Inference System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/38128031217981368859.

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碩士<br>國立屏東大學<br>資訊科學系碩士班<br>103<br>Adaptive neuro fuzzy inference system (ANFIS) is used to build function models. The discussed issues in building the accurate model include a number of data and fuzzy rules, data distribution, and data condition. Many researchers used ANFIS to build models and to forecast parameters, but they used different number of training data for modeling and no clear standards. In this study, the data by using random generated, full-factorial experiment, and Taguchi orthogonal experiment are collected to build model and the statistical formula is used to determine the a

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LIN, SHU-WEI, and 林書瑋. "Short Term Load Forecasting Using Adaptive Neuro-Fuzzy Inference System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/03839687090353502083.

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碩士<br>聖約翰科技大學<br>電機工程系碩士班<br>105<br>This thesis presented an adaptive neuro-based fuzzy inference system (ANFIS) based method using for the short-term load forecasting. Rising load demand has resulted in the development of the short-term load forecasting. Short-term load forecasting is used for the power system dispatch and operation. To evaluate the accuracy of the proposed load forecasting method, the load data of the Taipower system and the temperature data of Taiwan are used. The data includes 4 regions: the northern, the central the southern and whole Taiwan region. The accuracy of the pr

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Hua, Jian-Zhi, and 華建智. "Application of Adaptive Neuro Fuzzy Control System on a Braille Printer." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/03226569581406594964.

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LY, NGUYEN THI HA, and 阮氏荷莉. "Adaptive Neuro-Fuzzy Predictive Control Approach for Design of Cooperative Adaptive Cruise Control System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/94upa4.

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Yeh, Hsin-hung, and 葉信宏. "The Application of Car-following Model on Adaptive Neuro-fuzzy Inference System." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/50871005490260890494.

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碩士<br>國立交通大學<br>交通運輸研究所<br>86<br>Conventional car-following theory discusses the deterministic relationship between drivers''stimulus and response.It assumes all drivers are homogeneous which suggests that different drivers have indentical acceleration under the same stimulus. Such determiniistic relationship and homogeneous driving assumption do not well describe the real world traffic conditions.In order to make the conventional theory more realistic,this study first treats the drivers as

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GUVEN, Suleyman, and Suleyman GUVEN. "Partial Discharges Pattern Classification in GIS Using Adaptive Neuro Fuzzy Inference System." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/72q47n.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>100<br>ABSTRACT Partial discharge (PD) measurement is among the most important diagnostics methods of insulation systems in high voltage equipment, which makes it convenient to assess the insulation status. Partial discharge activities may stem from various defects, and correspondingly behave differently. Here, the PD patterns produced by 3 different laboratory models representing defects in GIS are recorded and analyzed. The research aimed at conducting PD tests with three GIS apparatus including prefabricated defects. From the PD pattern data, statistical features

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Chen, Chong-Guang, and 陳重光. "A Personal Computer Cooling System Based on Adaptive Neuro-Fuzzy Inference Systems." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/j97ecd.

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碩士<br>國立高雄應用科技大學<br>電子工程系碩士班<br>103<br>With advances in integrated circuit technology, the demand for light-weighted, thin, short, small and reduced power consumer products increases day by day, also increased internal heat density. To improve the cooling efficiency of personal computers, many cooling methods are developed out, such as the manual mode, speed cruise mode, thermal cruise mode and multi-point fan control mode, and so on. But it is more difficult to achieve a mathematical model of the fan motor, so let the fan speed control is not good. In this thesis, we propose an adaptive neuro

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Lin, Liang-hsing, and 林良興. "Application of Adaptive Neuro-Fuzzy Inference System to Predict Chiller Power Consumption." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/2sdm22.

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碩士<br>國立臺北科技大學<br>能源與冷凍空調工程系碩士班<br>96<br>It’s a necessary to use considerable electricity in order to compete in science and technology among each industry, and how to save energy become very important in nowadays. Usually we apply linear regression equation to model power consumption of chiller for the purpose of to know the power consumption of chiller. In this research, I apply adaptive neuro-fuzzy inference system to predict chiller power consumption, this method can improve the accuracy of predicting power consumption of chiller, and this method not to adopt the master''s experience fuzzy

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Hsu, Wen-cheng, and 許文政. "Application of Adaptive Neuro-Fuzzy Inference System on Predicting Springback of U-Bending." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/61609839669014215059.

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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>95<br>All sheet metal forming operation incorporate some bending; often it is the major feature. After forming, some elastic springback occurs and considerable residual stresses may result. Accurate prediction and controlling of springback is essential for the design of sheet metal forming tools. In this paper, we used the finite element software Dynaform 5.1 to collect the springback data of U-bending. Three main sheet metal forming parameters are the radius of punch(Rp), the radius of die corner(Rd) and punch-die clearance(C) with four levels respectively

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Hsia, Hsien-Ming, and 夏賢銘. "Optimal Design of Reinforced Concrete Short Columns Using Adaptive Neuro Fuzzy Inference System." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/72546019474807400543.

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碩士<br>義守大學<br>土木與生態工程學系<br>104<br>This thesis aims to optimally design reinforced concrete short columns by using the adaptive neuro-fuzzy inference system. Using a genetic algorithm, This thesis first works on the optimal design of reinforced concrete short columns. Given conditions are the factored axial load, neutral axis depth, compressive strength of concrete and yield strength of steel, length of the column and the size of the size of steel bars. The constraints are built based on the domestic reinforced concrete engineering design code, by considering the strength requirements of combin

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MIAO, HE-CIAN, and 繆和謙. "Short Term Wind Power and Solar Power Forecasting Using Adaptive Neuro-Fuzzy Inference System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/98429976626273220177.

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碩士<br>聖約翰科技大學<br>電機工程系碩士班<br>103<br>This thesis proposes an adaptive network-based fuzzy inference system (ANFIS) based forecasting method for short-term wind power and solar power forecasting. An accurate forecasting method for power generation of the wind energy conversion system (WECS) and the photovoltaic (PV) system is urgent needed under the relevant issues associated with the high penetration of wind and solar power in the electricity system. To demonstrate the effectiveness of the proposed forecasting method， the method is tested on the practical information of wind power generation of

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Ting, Ming-Jen, and 丁明仁. "Using Adaptive Neuro-Fuzzy Inference System to Predict Strength for Different Orientation Laminated Composites." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/57349166894106078345.

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碩士<br>建國科技大學<br>服務與科技管理研究所<br>103<br>Laminated composites are cured panels formed by stacking several prepreg plies. Because fibers are directional, the laminates exhibit different strengths depending on the fiber direction. Designers arrange fibers by parallel to the force axes according to structural requirements. Fiber with directionality renders composites with substantial design diversity and flexibility. This study attempts to establish the relationship between material experimental data and strength prediction by using fuzzy theory. With output-input mapping of an adaptive neuro-fuzzy i

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Fikri, Aulia Rahman Mufti, and 方耀利. "Negotiation-Based Capacity Planning with a Learning Mechanism Using Adaptive Neuro-Fuzzy Inference System." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/r237wt.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>104<br>In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performances. This study focuses on the development of an integrated framework to allocate limited budget in a multiple-factory environment. We develop a negotiation framework with learning mechanism to allocate autonomously finite budget provided by a headquarter and to facilitate the use of limited manufactur

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Chung, I.-Hua, and 鍾易樺. "Application of Adaptive Neuro-Fuzzy Inference System to the Defect Recognition of Gas Insulated Switchgear." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/07908330046576727262.

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博士<br>國立臺灣科技大學<br>電機工程系<br>101<br>Partial discharge (PD) is the main cause of degradation of the insulation in gas-insulated switchgear (GIS). PD phenomena include: surface discharge, cavity discharge, corona discharge, and treeing channel discharge. Previous research has shown that different types of defects in GIS generate different symptoms of PD, which are associated with various degrees of damage to the GIS. Hence, PD detection is essential to the reliable evaluation of insulation systems and the identification of defects in GIS. In this research, the experimental objects were GIS defect

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Chan, Yung-Yao, and 詹詠堯. "Application of Adaptive Neuro-Fuzzy Inference System to Construct and Analyze Defroster Model for Refrigerator." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/13110113408815106334.

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碩士<br>國立高雄第一科技大學<br>系統資訊與控制研究所<br>98<br>We all know the refrigerator which is very extensive application in commercially. At after starting all refrigerator run in twenty four hours. Refrigerator need much cost and energy during running, which the heater of defroster used energy too very large. Therefore, it is worth exploring the issue how to reasonably reduce defroster time to save-energy and completely defrost. In the thesis, we adopt the experimental way to investigate of the defroster model for refrigerator. In this experiment, we use the defroster frequency, the operating temperature an

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Wang, Cheng-Hang, and 王正航. "Association Forecasting of Asthma Susceptibility Genes in Taiwanese Population using Adaptive Neuro-Fuzzy Inference System." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/93099200583966189434.

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博士<br>元智大學<br>資訊工程學系<br>98<br>Asthma is one of the most common chronic diseases in children. It is caused by complicated coactions including various genetic factors and environmental allergens. The polymorphisms of β2-adrenergic receptor (ADRβ2), MS4A2 genes, tumor necrosis factor (TNF) gene cluster, cytokine gene cluster (IL4, IL4Ra, IL13) and cluster of differentiation 14 (CD14) are recognized as signigicant risk factors for asthma. In the literature, past research showes that both the serum levels of total IgE and eosinophil play important roles in the pathogenesis of asthma. The CD14 and M

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Tang-YiWang and 王瑭毅. "Establishing a Clinical Prediction Model of Sleep Apnea Syndrome by Adaptive Neuro-Fuzzy Inference System." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/evnmr4.

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碩士<br>國立成功大學<br>工程科學系<br>106<br>In recent years, getting a good sleep becomes one of the important issues and there are more researches to study sleep disorders. Obstructive sleep apnea (OSA) is one of the sleep disorders that has attracted much attention. However, the diagnosis of OSA is still limited in the daily clinical practice. Although we can obtain more accurate diagnosis through the examination in the hospital’s sleep lab, it is very time-consuming and expensive to undertake one. Besides, developing an accurate prediction model for OSA is still a difficult task in clinical trial. The

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Sung, Jheng-Hua, and 宋政樺. "Applying Adaptive Neuro-Fuzzy Inference System to estimate typhoon intensity forecast in the Northwest Pacific." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/wnw2kw.

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碩士<br>中原大學<br>土木工程研究所<br>107<br>This study employs machine learning to estimate typhoon intensity prediction. The prediction model for typhoon intensity is based on the adaptive neuro-fuzzy inference systems (ANFIS). The ANFIS typhoon intensity prediction model is built every 12 hours for the next five days; the improvement of typhoon intensity forecasts is compared to a baseline model with multiple linear regression (MLR). This study uses the Northwest Pacific basin as a case area and collects 2000~2012 typhoon non-landing data in SHIPS Developmental Data. The stepwise regression procedure (S

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Hsu, Chuang-Chin, and 許創欽. "Development of a gear fault diagnosis system using discrete wavelet transform and adaptive neuro-fuzzy inference." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/34874599466309652161.

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碩士<br>國立彰化師範大學<br>車輛科技研究所<br>96<br>In this thesis, an intelligent diagnosis for fault gear identification using discrete wavelet transform (DWT) and adaptive neuro-fuzzy inference (ANFI) system is presented. Generally, the abnormal transient signals can be shown different decomposition levels and used to recognize the various faults by the DWT amplitude figure. However, many fault conditions are hard to inspect accurately by the naked eye. In the present study, the feature extraction method based on DWT with energy spectrum is proposed. Furthermore, the ANFI system is proposed to identify

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Lai, Horng-Cherng, and 賴鴻成. "Adaptive Neuro-Fuzzy Inference System for Predicting Shoreline Changes –A case study in Yilan of Taiwan." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/rugc66.

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博士<br>國立臺灣大學<br>農藝學研究所<br>102<br>Shoreline erosion is a worldwide problem that causes a major concern to the socio-economic developments in coastal cities for many countries. The increasingly intensive human activities along coasts enlarge coastal erosion areas and aggravate erosion processes, and thus cause land losses; moreover the global climate change in the past decades results in rising sea levels. Taiwan is frequently attacked by typhoons and shoreline erosion is a major concern to local residents. Shoreline change prediction has gained considerable attention; nevertheless, little cons

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HSIEH, CHENG-EN, and 謝承恩. "Applying Adaptive Neuro-Fuzzy Inference System to Energy Saving Analysis for Active Magnetic Bearing Compressor Chiller." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/v57afn.

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碩士<br>國立臺北科技大學<br>能源與冷凍空調工程系<br>107<br>The research investigated the energy saving efficiency after replacement of Active Magnetic Bearing Compressor (AMBC) Chiller. It collected the actual data from the central monitoring system established by the air-conditioning manufacturer. It used adopted regression analysis to eliminate and filter unreasonable data. Using linear regression, backpropagation network (BPN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) to establish the power consumption model of the chiller, and find the most accurate modeling method. Using the modeling method to compar

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Chan, Yea-Kuang, and 詹益光. "Applying Adaptive Neuro-Fuzzy Inference System to Estimate the Turbine-Generator Output Power for Nuclear Power Plants." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/dmsdhd.

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博士<br>國立臺灣科技大學<br>電機工程系<br>100<br>Due to facing the limited power resources and the difficulty to develop new electricity utilities, to maintain the power plant optimal thermal efficiency for improving plant operation performance is the goal for advanced countries under the trend of electricity utility deregulation in recent years. In this research, an adaptive neuro-fuzzy inference system (ANFIS) was adopted to develop the turbine cycle model to predict the turbine-generator output. Operating data above the 95% load level from the plant's past three fuel cycles were collected and validated to

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Guruprasad, K. R. "Model Reference Learning Control Using ANFIS." Thesis, 1996. https://etd.iisc.ac.in/handle/2005/1714.

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Guruprasad, K. R. "Model Reference Learning Control Using ANFIS." Thesis, 1996. http://etd.iisc.ernet.in/handle/2005/1714.

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