Search Results - (( data optimization method algorithm ) OR ( parameter implementation clustering algorithm ))
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Thesis -
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Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…Clustering is a famous method for creating data transmission more efcient. …”
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Article -
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Hybrid clustering-GWO-NARX neural network technique in predicting stock price
Published 2017“…Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. …”
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Conference or Workshop Item -
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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Thesis -
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Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…As these clustering algorithms require the number of clusters as input parameter of the algorithms, the study of number of clusters for the clustering is served as focus in this paper. …”
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Proceedings -
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…However, different clustering algorithms have different parameters that need to be specified. …”
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Book Chapter -
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”
Article -
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]
Published 2023“…In this study, the method used is K-Means to perform clustering based on area grouping. The implementation of the K-Means Clustering algorithm for detecting the level of spread of COVID-19 data in Indonesia by using the parameter k=3 is quite good with areas in Indonesia that have a high the spread of COVID-19 and the results of the cluster validity test get silhouette values on O = (Total Case, Total Death) and P = (Total Case, Total Death, Total Recovered) have the same cluster value, which is 0.93 which means the cluster quality is very good.…”
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Book Section -
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Cauchy density-based algorithm for VANETs clustering in 3D road environments
Published 2022“…Clustering algorithms for VANETs operate in a decentralized mode, which requires incorporating additional stages before deciding the clustering decisions and might create sub-optimality due to the local nature of the decentralized approach. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For floor localisation, the strategy is based on developing the algorithm to determine the floor by utilising fingerprint clustering technique. …”
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Thesis -
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
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Monograph -
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali
Published 2017“…Implementation wise, the algorithm is also parallelizable to a large extent thus allowing it to scale up/down vertically and horizontally and its adaptable to the high-performance computing environment. …”
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Thesis -
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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Thesis -
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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A coverage path planning approach for autonomous radiation mapping with a mobile robot
Published 2023Article
