Search Results - (( using function methods 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 fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. …”
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Monograph -
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Enhancement load balancing in failover web server by using HTTP-response status techniques with pfsense opensource / Muhammad Hafiz Ramli
Published 2020“…Then, this paper will propose the architecture design and techniques will use during the implementation stage. Moreover, there will be a simulation with the research parameter. …”
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Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…In addition, an objective function is designed to accomplish Quality of Service (QoS) in WSN using three input parameters, namely energy, distance, and delay. …”
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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. …”
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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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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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Hybrid clustering-GWO-NARX neural network technique in predicting stock price
Published 2017“…It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. …”
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Conference or Workshop Item -
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A coverage path planning approach for autonomous radiation mapping with a mobile robot
Published 2023Article -
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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FSM-Gear weight-based energy-efficient protocol for illegal logging monitoring using firefly synchronization
Published 2022“…The effort of low-power algorithm was conducted in several stages, such as (1) randomly distributed localization technique; (2) randomly applied clustering and cluster head selection; (3) the use of Time Division Multiple Access (TDMA) synchronization; and (4) how to formulate the distance factor to the power emitted by sensor nodes not based on the real environment. …”
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Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control
Published 2014“…Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control.In engineering applications, two attractive tools have emerged recently.These two attractive tools are: the artificial neural networks and the fuzzy logic system. …”
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Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar
Published 2019“…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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