Search Results - (( simulation classification clustering algorithm ) OR ( using function based 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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2
Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay
Published 2024“…RFE was applied to the craniodental measurements of Rattus rattus (R.rattus) data to select the best feature subset for both male and female rats. A comparative study based on machine learning algorithms was also conducted by using all features and the RFE-selected features to classify the R. rattus sample based on the age groups. …”
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4
An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka
Published 2024“…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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6
Computational analysis of biological data: Where are we?
Published 2024“…The current book chapter discusses the advantages of computational modeling in studying biomedical research. Using computational modeling, classification algorithms can be applied to microarray and RNA sequencing data (such as hierarchical clustering - HCL, t-SNE and principal component analysis - PCA), and high-resolution images can be generated based on the analyzed data and patient samples. …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. The optimal number of cluster for FCM is obtained through cluster validity analysis. …”
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8
Feature extraction and classification :a case study of classifying a simulated digital mammogram images using self-organizing maps (som)
Published 2007“…The accuracy of classification performance was acquired. A case study of breast cancer has been demonstrated in this study by using a simulated digital mammogram images. …”
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Data redundancy reduction scheme for data aggregation in wireless sensor network
Published 2020“…This research proposes Data Redundancy Reduction Scheme (DRRS) which includes three algorithms namely, Metadata Classification (MC), Selection Active Nodes (SAN) and Anomaly Detection (AD) algorithms that works before data aggregation, when multiple composite events simultaneously occur in the different locations within the cluster. …”
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Neuro fuzzy classification and detection technique for bioinformatics problems
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Case study : an effect of noise in character recognition system using neural network
Published 2003“…These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean
Published 2007“…This paper presents the need for such a prediction and optimization engine that discusses the approach for history-based prediction and optimization. Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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A coverage path planning approach for autonomous radiation mapping with a mobile robot
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A Naïve-Bayes classifier for damage detection in engineering materials
Published 2007“…The method is based on mean and maximum values of the amplitudes of waves after dividing them into folds then grouping them by a clustering algorithm (e.g. k-means algorithm). The Naïve-Bayes classifier and the feature sub-set selection method were analyzed and tested on two sets of data. …”
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Isolated digit speech recognition in Malay language using Neuro-Fuzzy approach
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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A block cipher based on genetic algorithm
Published 2016“…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources
Published 2026“…To initialise function placement, Fitness-Based Swap (FBSW) algorithm is proposed which places functions based on pre-defined information such as function size, function maximum execution time, and storage cost. …”
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Computation of cryptosystem based on Lucas functions using addition chain
Published 2010“…Cryptosystem based on Lucas Functions is known as LUC Cryptosystem. …”
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