Search Results - (( sequence optimization based algorithm ) OR ( using vectorization machine algorithm ))
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Thesis -
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Monograph -
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. …”
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Ensemble learning using multi-objective optimisation for arabic handwritten words
Published 2021“…The features were tested with Support Vector Machine (SVM) and Extreme Learning Machine (ELM). …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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Proceeding Paper -
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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Landslide risk zoning using support vector machine algorithm
Published 2024“…The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…This paper presents an intelligent system to reduce Non Technical Loss (NTL) using hybrid Support Vector Machine (SVM) and Genetic Algorithm (GA). …”
Conference Paper -
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Face recognition using eigenfaces and smooth support vector machine
Published 2011“…Face is one of the unique features of human body which has complicated characteristic.Facial features (eyes, nose, and mouth) can be used for face recognition. Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Undergraduates Project Papers -
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Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies
Published 2009“…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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Product assembly sequence optimization based on genetic algorithm
Published 2010“…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model
Published 2019“…The required memory of this algorithm is also time independent. In addition, the optimal state sequence obtained by the EVRA algorithm is the same as that obtained by the classical Viterbi algorithm for HHMM.…”
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Ultra-short-term PV power forecasting based on a support vector machine with improved dragonfly algorithm
Published 2021“…The proposed model of support vector machine (SVM) with improved dragonfly algorithm(IDA) is used to forecast the PV power. …”
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