Search Results - (( evolution optimization approach algorithm ) OR ( bayesian classification using algorithm ))
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A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification
Published 2006“…ECT measured the different capacitance value of fluid and produced the data for the classification problem. Multilayed Perceptron (MLP), a type of artificial neural network (ANN) which is widely used in a classification problem is developed using MATLAB 7®. …”
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Monograph -
2
Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…In this system a Bayesian algorithm was used in order to implement the system. …”
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Thesis -
3
An experimental study of classification algorithms for crime prediction.
Published 2013“…This paper compares the two different classification algorithms namely, Naïve Bayesian and Decision Tree for predicting ‘Crime Category’ for different states in USA. …”
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Article -
4
Feature extraction using active appearance model algorithm with Bayesian classification approach
Published 2013“…This study enhances invariant recognition of human faces and analysis to improve face verification and identification performance using Active Appearance Model (AAM) for feature extraction with Bayesian classification approach. …”
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Conference or Workshop Item -
5
Detection of acute leukaemia cells using variety of features and neural networks
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Working Paper -
6
An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka
Published 2024“…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
Article -
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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8
Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Article -
9
Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…A useful property of the statistical classifier like Bayesian is that, it is optimal in the sense that it minimizes the expected mis classification rate. …”
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Thesis -
10
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Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi
Published 2019“…Genetic Algorithm(GA) is used to optimize the order of sequence of the input sample and the parameters of the Bayesian ARTMAP (BAM). …”
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Thesis -
12
Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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Article -
13
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Keyword: Random Forest, Bayesian Inference, Classification, Regression, Missing Data.…”
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Thesis -
14
A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem
Published 2020“…The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. …”
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Article -
15
Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
Published 2014“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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Book -
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A study on classification learning algorithms to predict crime status.
Published 2013“…In this paper, we conducted an experiment to obtain better supervised classification learning algorithms to predict crime status by using two different feature selection methods tested on real dataset. …”
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Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). …”
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Thesis -
19
Differential evolution for neural networks learning enhancement
Published 2008“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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Thesis -
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