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1
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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2
Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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3
Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…Spearman Correlation was used to checked multi-collinearity effect on debris flow conditioning factors; evaluations factors of Information Value (IV), Crammer V were assessed.Wrapper feature subset selection technique was used, different metaheuristic search algorithms (e.g. …”
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4
Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
Published 2022“…Stakeholders can use the identified effective factors to improve education outcomes.…”
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5
How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
Published 2021“…Most of the weed images were captured using red, green, and blue (RGB) camera, i.e., 48.28% and main classification algorithm was machine learning techniques, i.e., 47.90%. …”
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6
How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields?
Published 2024Article -
7
Developing an ensembled machine learning model for predicting water quality index in Johor River Basin
Published 2025“…Then, in terms of WQI calculation, feature importance method is used to identify the most important parameters that can be used to predict the WQI. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao
Published 2024“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. …”
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9
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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10
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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11
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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12
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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13
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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14
Design of intelligent control system and its application on fabricated conveyor belt grain dryer
Published 2011“…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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15
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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16
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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17
Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm
Published 2020“…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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18
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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19
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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20
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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