Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 27 for “"Adaptive neuro-fuzzy inference system"”.
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Adaptive neuro-fuzzy inference system based neural network and parameter constraints
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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A Novel Combined Investment Recommender System Using Adaptive Neuro-Fuzzy Inference System
Investment recommendation systems (IRSs) are critical tools used by potential investors to make informed decisions about investment options. However, existing systems have limitations in terms of accuracy and efficiency, leading to a need for more effective and efficient recommendation systems. …
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Fuzzy inference systems for iris biometrics to reduce search time in large databases
… a method that can reduce the search time of a system trying to match a user's iris image against those in a very large database. One method to reduce search time is to predict an individual's ethnicity and then only search iris templates belonging to that particular ethnicity in the database. …
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A neural fuzzy approach to modeling the thermal behavior of power transformers
… 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 …
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Detecting and Modelling Stress Levels in E-Learning Environment Users
A modern Intelligent Tutoring System (ITS) should be sentient of a learner's cognitive and affective states, as a learner’s performance could be affected by motivational and emotional factors. It is important to design a method that supports low-cost, task-independent and unobtrusive sensing of a …
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Development and Design of Self-Sensing SMAs using Thermoelectric Effect
… SMA. This work then models this behavior using Adaptive Neuro Fuzzy Inference System (ANFIS) and compares it to experimental results. The nonlinear learning and adaptation of ANFIS architecture makes it suitable to model the temperature path hysteresis of SMAs.
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Fuzzy Neural Networks (FNNs) with the integration of fuzzy logic, neural networks and optimization techniques have not only solved the issue of “black box” in Artificial Neural Networks (ANNs) but also have been effective in a wide variety of real-world applications. Despite of attracting …
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Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier
… and iCS were then employed on proposed novel Fuzzy-Meta Classifier (FMC) which offered highly reduced model complexity and high accuracy as compared to Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed three-layer FMC produced efficient rules that generated nearly 100% accuracies on …
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Modified anfis architecture with less computational complexities for classification problems
Adaptive Neuro Fuzzy Inference System (ANFIS) is one of those soft computing techniques that have solved the problems effectively in a wide variety of real-world applications. Even though it has been widely used, ANFIS architecture still has a drawback of computational complexities. The number of …
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Prediction of Enrollment using Computational Intelligence
… include an artificial neural network (ANN), a neurofuzzy inference system (ANFIS) and an aggregated fuzzy time series model. A novel form of ANN, namely, single multiplicative neuron (SMN), as an alternative to traditional multi-layer perceptron (MLP), has been used for time series prediction. …
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Data redundancy reduction using sensitivity analysis method for machine-learning-based battery management system
… (ML) techniques in the battery management system (BMS). The novel approach analyzes the sensitivity of lithium-ion battery model parameters towards their discharge performances. The sensitivity analysis is based on the sum-of-difference method to identify redundant model parameters that …
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Performance of maximum power point tracking by using conventional and soft computing techniques during partial shading conditions
… and modeling the maximum power point tracking system. Maximum power extraction from PV system can be achieved by using maximum power point tracking (MPPT) techniques that are classified into conventional and soft computing. This work demonstrates the performance of three types of MPPT …
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Epileptic Seizure Detection And Prediction From Electroencephalogram Using Neuro-Fuzzy Algorithms
… presents innovative approaches based on fuzzy logic in epileptic seizure detection and prediction from Electroencephalogram (EEG). The fuzzy rule-based algorithms were developed with the aim to improve quality of life of epilepsy patients by utilizing intelligent methods. An adaptive …
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Control of nonlinear systems using Sugeno fuzzy approximators
… deals with the issue of controlling nonlinear systems by integrating available classical as well as modern tools such as fuzzy logic and neural networks. The proposed approaches throughout this thesis are based on the well known first-order Sugeno fuzzy system. To achieve a better understanding …
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Development and analysis of hybrid adaptive neuro-fuzzy inference systems for the recognition of weak signals preceding earthquakes
… The work described in this thesis incorporates neuro-fuzzy technology for the reliable recognition of EEP signals within the electric field. Neuro-fuzzy networks are neural networks with intrinsic fuzzy logic abilities, i.e. the weights of the neurons in the network define the premise and …
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Adaptive Hierarchical Control in V2G Integrated Micro-grids
An adaptive hierarchical control system for utilizing electric vehicle (EV) batteries to provide energy storage service in a Vehicle-to-Grid (V2G) integrated micro-grid is presented in this thesis. The control system consists of an on-line self-tuning (ST) adaptive inverter controller at the …
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Modeling of Bioenergy Production
… capable of representing the pyrolysis reaction system. We propose a new kinetic reaction model, which would account for significant uncertainty. Specifically we have employed fuzzy modeling using the adaptive neuro-fuzzy inference system (ANFIS) in order to describe the pyrolysis of biomass. The …
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Hydrochemical Assessment and Modelling of Groundwater Quality of an Urban Aquifer Near A Sanitary Landfill
… learning methods (Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System). A total of twenty models are constructed and evaluated. Results show that Total Dissolved Solids is statistically related to parameters such as Ca, Mg, HCO3, SO4, Cl, EC, and pH. Multiple evaluation metrics …
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Analytical study of computer vision-based pavement crack quantification using machine learning techniques
… cracks, using an automated computer vision-based system to provide a better understanding of the pavement deterioration process. To achieve this objective, an automated crack-recognition software was developed, employing a series of image processing algorithms of crack extraction, crack grouping, …
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A Comprehensive Study of Buoyant Rosette Jets Using Laboratory Experiments, CFD, and Machine Learning
… field predictions in wastewater discharge systems. Experiments were conducted using LIF techniques to obtain high-resolution scalar concentration fields, and visual jet trajectory data under different operating conditions were obtained. These experimental results can be used as a benchmark …
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