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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Thesis -
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…Since the direct application of the firefly algorithm cannot generate connected topologies, outputs from the firefly algorithm were used as an initial input material distribution for the OC method. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Thesis -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Lastly, in order to externally judge the validity of these types of clustering algorithms, there is a need for a method to correctly and efficiently evaluate their variant multiclass clustering results. …”
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Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim
Published 2025“…In this study, the result of the shooting method combined with various root-finding algorithms such as the Bisection method, Secant method, Newton's method, Ridder's method, Halley’s method, Brent’s method, Modified Newton method and Improved Ostrowski’s method to solve BVPs is evaluated. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences
Published 2021“…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin
Published 2021“…Newton's Method also called the Newton-Raphson method is a recursive algorithm for approximating the root of a differentiable function. …”
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Thesis -
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Published 2023“…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.
Published 2009“…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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