Search Results - (( wave optimization method algorithm ) OR ( data classification modified algorithm ))
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1
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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2
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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Thesis -
3
Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation
Published 2011“…Therefore the use of genetic algorithm (GA) optimization technique which is one of nonlinear optimization methods is an appropriate choice to solve surface wave inversion problem having high nonlinearity and multimodality. …”
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4
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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5
Optimizing the efficiency of Oscillating Water Column (OWC) wave energy converter using genetic algorithm
Published 2015“…This paper, describes a method to maximize the pneumatic system efficiency using optimization technique based on Genetic algorithm. …”
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6
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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7
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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8
The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…Thus, this study aims to adopt and modify the BFOA into Instance Selection (IS) classifier by manipulating its global search capability and high convergence rate for data classification problem. …”
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9
Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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10
Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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11
Mutable composite firefly algorithm for gene selection in microarray based cancer classification
Published 2022“…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
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12
Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…This paper presents an optimized wave kernel signature (OWKS) using a modified particle swarm optimization (MPSO) algorithm. …”
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13
Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…This paper presents an optimized wave kernel signature (OWKS) using a modified particle swarm optimization (MPSO) algorithm. …”
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14
Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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15
Automated classification of blasts in acute leukemia blood samples using HMLP network
Published 2011“…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
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16
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Data pre-processing on the data set may improve the classification results. …”
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Final Year Project / Dissertation / Thesis -
17
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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18
Logistic regression methods for classification of imbalanced data sets
Published 2012“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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19
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…Rough sets theory represents a mathematical approach to vagueness and uncertainty. Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. …”
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20
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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Thesis