Search Results - (( using function _ algorithm ) OR ( based classification modified algorithm ))
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1
An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…The modified WNN was then applied in the areas of classification and function approximation.…”
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2
A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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3
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…A modified fitness function in Wrapper GA was introduced by adding a function to maintain the balanced of the selected features. …”
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4
Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network
Published 2011“…Second, the proposed enhanced fuzzy c-means clustering algorithm—specifically, the modified point symmetry-based fuzzy c-means (MSFCM) algorithm—was employed in selecting the locations of the translation vectors of the WNN. …”
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5
Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…Firstly, a non-linear time-varying modified Sigmoid transfer function is used as the binarization method. Second, a hybrid Logistic-Tent chaotic map is employed to substitute the pseudorandom numbers of the probability operator in standard WOA. …”
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6
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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7
Application Of Neural Network In Malaria Parasites Classification
Published 2006“…Hybrid Multilayer Perceptron (HMLP) network with modified recursive prediction error algorithm will be developed using Borland C++ Builder. …”
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8
Logistic regression methods for classification of imbalanced data sets
Published 2012“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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9
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The third phase studied the reaction of the Radial Base Function-based SVM classifier to Modified Sun-Canopy-Sensor Correction (SCS+C) as a Topographic Correction (TC) technique for Landsat 8 data. …”
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10
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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11
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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12
An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving
Published 2014“…This paper modifies the Adaptive Contrast Enhancement Algorithm with Details Preserving (ACEDP) technique by integrating a fuzzy element in the image type selection. …”
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13
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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14
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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15
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…This paper introduced a new class of efficient second order conjugate gradient (CG) for training BP called Rivaie, Mustafa, Ismail and Leong (RMIL)/AG. The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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16
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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17
Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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18
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. These findings indicated that open source Arduino board is capable of running real time pattern, non-pattern recognition based control methods by producing classification accuracy up to 99.48% even though it is known as just a microcontroller that has limitation to run complex classifiers. …”
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19
Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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20
A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification
Published 2010“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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