Search Results - candidate ((((electron algorithm) OR (evolutionary algorithm))) OR (detection algorithm))
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An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…This research designed an anomaly-based detection, by adopting the modified Cuckoo Search Algorithm (CSA), called Mutation Cuckoo Fuzzy (MCF) for feature selection and Evolutionary Neural Network (ENN) for classification. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…This is considered a multi-objective problem because the problem involves optimizing more than one problem simultaneously subject to constraint(s). Evolutionary multi-objective algorithms are considered as good candidate for solving multi-objective optimization problems and have been applied to variety of problems in different areas. …”
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3
Normative Fish Swarm Algorithm For Global Optimization With Applications
Published 2019“…The results obtained from both applications have proved that the proposed NFSA is more effective in multi-objective optimization and MPPT approaches in comparison to few compared evolutionary algorithms.…”
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4
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. Using a number of candidate detectors, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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Proceeding Paper -
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Improvement real-time detection of moving vehicle in a dynamic scene using shadow removal method / Khairul Azman Ahmad, Mohd Halim Mohd Noor,Mohamad Adha Mohamad Idin
Published 2011“…Real-time processing is still feasible as these sophisticated algorithms are applied only a small number of candidates foreground pixels. …”
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Research Reports -
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Therefore, we propose a prominent approach that integrates each of the NN, a meta-heuristic based on an evolutionary genetic algorithm (GA), and a core online-offline clustering (Core). …”
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Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
Published 2015“…In this study, the performances of four different peak models of time domain approach which are Dumpala's, Acir's, Liu's, and Dingle's peak models are evaluated for electroencephalogram (EEG) signal peak detection algorithm. The algorithm is developed into three stages: peak candidate detection, feature extraction, and classification. …”
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Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi
Published 2014“…This proposed technique will be compared with Evolutionary Programming (EP) algorithm, that usually designed to maximize or minimize the objective function, which is a measure of the quality of each candidate solution. …”
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Adaptive DNA computing algorithm by using PCR and restriction enzyme
Published 2004“…By doing this, the molecules which serve as a solution candidate can he narrowcd down and the optimal solution can be detected easily. …”
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Book Section -
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Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network
Published 2016“…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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Fast shot boundary detection based on separable moments and support vector machine
Published 2021“…Moreover, for the proposed SBD algorithm, a comparative study is performed with state-of-the-art algorithms. …”
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Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network
Published 2016“…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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Classification of Short Possessive Clitic Pronoun Nya in Malay Text to Support Anaphor Candidate Determination
Published 2020“…In this paper, the automatic semantic tag was used to determine the type of nya, which at the same time could determine nya as an anaphor candidate. The new algorithms and MalayAR architecture were proposed. …”
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Efficient distance computation algorithm between nearly intersect objects using dynamic pivot point in virtual environment application
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Classification of short possessive clitic pronoun Nya in Malay text to support anaphor candidate determination
Published 2020“…In this paper, the automatic semantic tag was used to determine the type of nya, which at the same time could determine nya as an anaphor candidate. The new algorithms and MalayAR architecture were proposed. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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Breast Cancer Prediction Model Using Machine Learning
Published 2021“…Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. …”
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Improved fault location on distribution network based on multiple measurements of voltage sags pattern
Published 2012“…A new ranking approach is proposed to overcome multiple faulted section candidates. A large scale 11 kV network which comprises of 43 nodes and 5 branches are used to evaluate the proposed algorithm. …”
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