Search Results - (( basic optimization method algorithm ) OR ( data selection method algorithm ))
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1
An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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2
Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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3
Improving neural networks training using experiment design approach
Published 2005“…One more data (m+ 1) is entered to train the NN again. This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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4
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
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5
Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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6
A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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7
A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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Fuzzy C means imputation of missing values with ant colony optimization
Published 2020“…This error should be handled correctly before data is processed into processing model. This paper proposes a improved method of imputation by employing a new version of Fuzzy c Means (FCM) which hybridized with Evolutionary Algorithm to handle missing values problem. …”
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9
An enhance embedding method using edge and textures detection for image steganography
Published 2024“…This method seeks to ensure secure and effective data concealment by identifying and utilizing noisy zones in images, making it more difficult for steganalysis tools to detect the embedded information. …”
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10
Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph
Published 2016“…Then, utilization of cost-effective optimization algorithm for optimal sizing of the energy resources and other system components with accurate mathematical models for energy management of the entire hybrid system. …”
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11
Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…These methods are M1 and M2, and they basically differ in the type of input-output data used to train the artificial neural network. …”
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12
Particle swarm optimization (PSO) for CNC route problem
Published 2002“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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Undergraduates Project Papers -
13
Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…The application of orthogonal decomposition method using Householder transformation (refer to section 3.3) is used to solve the least-squares problem in power system state estimation. …”
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14
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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15
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
Published 2023“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”
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18
Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction
Published 2021“…Second, three multi-verse optimizer algorithm (MVOs), namely, basic MVO, modified MVO, hybrid MVO is proposed to solve the TDC problem; these algorithms are incremental improvements of the preceding versions. …”
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19
Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…After discussing about the introduction (the basic of CMOS transistor ), we will discuss how to create the Optimal layout of CMOS Functional Array with the minimum separation based on euler path method. …”
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20
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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