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1
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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2
An Effective Fast Searching Algorithm for Internet Crawling Usage
Published 2016“…The search algorithm is a crucial part in any internet applications. …”
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3
Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…A lot of efforts have been made to investigate methodologies to form optimal efficiency in determining typical load profiles (TLPs), derived from various clustering and classification techniques. …”
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4
An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa
Published 2018“…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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5
Intuitive content management system via manipulation and duplication with if-else rules classification
Published 2018“…As a result, ICMS can transform dynamic websites into static websites with faster load speed using manipulation method mixed with data mining classification prediction and Boyer-Moore Horspool algorithm which can be classified, edited, adjustable and searched more precisely. …”
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Direct approach for mining association rules from structured XML data
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7
Songs Search Using Human Humming Voice
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria
Published 2010“…This paper presented an application of Artificial Neural Network (ANN) in steady state stability classifications. A multi layer feed forward ANN with Back Propagation Network algorithm is proposed in determining the steady state stability classifications. …”
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9
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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10
An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus
Published 2018“…Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
Published 2022“…The result represents a significant step in the development of a nondestructive and in-situ detection system which validated by both chemometric and machine learning (ML) classification techniques…”
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Message based random variable length key encryption algorithm.
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Initially, this tool adopts only Crow Search, Jaya, and Sine Cosine algorithms. But more metaheuristics will be included in future research. …”
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Evolutionary Music; Composing Beats and Chords Progression
Published 2020“…Evoluthm utilizes Harmony Search Algorithm and JFUGUE techniques in compliances with artificial intelligence (AI). …”
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15
Decision tree-based approach for online management of PEM fuel cells for residential application
Published 2004“…The main idea is to employ a classification technique, trained on a sufficient subset of data, to produce an estimate of the optimal setting without repeating the optimization process. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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18
Development of vehicle detection and counting system for traffic analysis using computer vision
Published 2024“…Lastly another deep sort algorithm is utilized to keep track of the detected vehicles and count them accordingly. …”
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19
Hybrid genetic algorithm for improving fault localization
Published 2018“…Therefore, there is a need for a technique which able to localize a fault effectively with less number of mutants generated. Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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Decision tree-based approach for online management of pem fuel cells for residential application
Published 2004“…The main idea was to employ a classification technique, trained on a sufficient subset of data, to produce an estimate of the optimal setting without repeating the optimization process. …”
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