neuro-fuzzy classification model
A novel optimal medium resolution remote sensing image classification using Neuro fuzzy approach
... and fuzzy systems are adaptive in the estimation of the input–output function without any precise mathematical ...while fuzzy systems can handle symbolic and qualitative ...a fuzzy classifier ...
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A Modified Neuro-Fuzzy System Using Metaheuristic Approaches for Data Classification
... Generally, literature emphasis on three main problems regarding ANFIS to solve computa - tional complexity: reducing rule-base, developing efficient training methods and member - ship functions selection. A significant ...
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Neuro fuzzy classification and detection technique for bioinformatics problems
... of classification or clustering of bioinformatics ...new classification technique in Adaptive Neuro Fuzzy Inference System (ANFIS) ...various classification techniques, conventional or ...
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Comparative Analysis Of Neuro-Fuzzy Model For Human Resources
... Neuro Fuzzy designs focus on specific observations and enhance the effectiveness rating of decision ...Moreover, Neuro Fuzzy design doesn't call for a priori knowledge of weights for inputs ...
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A Neuro-fuzzy approach for user behaviour classification and prediction
... the model by achieving encouraging ...a model consisting of Deep Belief Networks and Stacked Denoising auto-Encoders and showed that the extraction of features from high-dimensional data achieves a sub- ...
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Fuzzy Neuro Model for Intelligent Credit Risk Management
... HFNN model developed in this ...The classification accuracies of Training (TR), Evaluation (EV), and Testing (TE) samples were already dropping after the 25th ...input fuzzy set is activated all ...
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A Neuro-Fuzzy Based System for the Classification of Cells as Cancerous or Non-Cancerous
... Ansari and coworkers developed a system for predicting pancreatic ductal adenocarcinoma (PDAC) survival using artificial neural network (ANN) model [26]. A feed-forward ANN was used to construct the survival ...
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Fixed Neuro Fuzzy Classification Technique For Intrusion Detection Systems
... high ranks were considered for the parameter selection. The system used 31 features of the available 41 features of the NSL-KDD Cup 99 data set. The experiments were done on MATLAB R2012A with libSVM package, as it ...
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Comparison of Neuro fuzzy Models for Classification Fingerprint Images
... and fuzzy logic are two totally inspired concepts of human ...mathematical model defined as the resolution is based on the numerical values of inputs and outputs for neural networks and logic of the system ...
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Moving object detection and classification using neuro-fuzzy approach
... Moving object detection techniques usually manipulate the colour intensity [3] [4] [5], motion [6] [7] [8], and shape [2] [9] of an object as the feature vector. Mixture of Gaussians (MoG), histogram of oriented gradient ...
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Classification of MRI Brain Images Using Neuro Fuzzy Model
... the classification of MRI human brain ...the classification is done by a hybrid Neuro- fuzzy classifier ...the neuro classifier and the fuzzy classifier and overcomes the ...
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Effect of fuzzy partitioning in Crohn's disease classification: a neuro-fuzzy-based approach
... the neuro-fuzzy based classification was ...on fuzzy partitioning was ...of fuzzy partition to determine the optimal accuracy ...of classification, instead of feeding the entire ...
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Gender Clustering and Classification Algorithms in Speech Processing: A Comprehensive Performance Analysis
... mathematical model. Artificial neural networks (ANN), fuzzy logic, genetic programming and support vector machine (SVM) are the Computational Intelligence techniques which were productively used to solve ...
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Article Description
... image classification are being computationally heavy and also do not guarantee high ...hand fuzzy logic technique is more accurate but it fully depends on expert knowledge, which may not always ...
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Developing a Neuro Fuzzy Model for Weather Prediction
... pure fuzzy logic based forecasting. In this study, a Neuro-fuzzy approach will be proposed to predict weather in Sadat region, western desert, ...proposed model uses a ...
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Portfolio Investment Model Using Neuro Fuzzy System
... control model that includes ecological and economic uncertainty for managing both types of natural ...programming model to determine capital allocations to international markets and the selection of assets ...
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LOAD FREQUENCY CONTROL OF HYBRID POWER SYSTEM USING INTELLIGENT CONTROLLERS
... the model of hybrid power system is ...called Fuzzy PI and Neuro- Fuzzy approach. The advantage of Neuro-fuzzy approach is that it can deal with non-linearities in the meantime ...
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DYNAMIC SENSOR RELOCATION TECHNIQUE BASED LIGHT WEIGHT INTEGRATED PROTOCOL FOR WSN
... The Fuzzy membership functions are trained with the Neural Network nodes to have the control technique inherited into the ANFIS ...the fuzzy rules in its model. The learned ANFIS system is a ...
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DEVELOPMENT AND APPLICATION OF A STAGE GATE PROCESS TO REDUCE THE UNERLYING RISKS OF IT SERVICE PROJECTS
... predictive model to diagnosis and associated with the accuracy results with SVM, an NN, a rough set (Rosetta), and logistic ...set model is accurate than the ...predictive model is used to determine ...
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Speed Control and Protection of Three Phase BLDC Motor with Hall Effect Sensor Using Neuro Fuzzy Logic Controller
... , Hao Chen, Song Sun, Dionysios C. Aliprantis, and Joseph Zambreno [14] presented the FPGA implementation of an induction machine dynamic simulation, using numerical integration algorithm. In 1999, Z. M. Zhao, S. Meng ...
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