Search Results - (( network selection (search OR research) algorithm ) OR ( based optimisation system algorithm ))*
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…For this purpose, this study used the intensification and diversification properties of the recently proposed moth-flame optimisation (MFO) algorithm and utilised the algorithm in the proposed feature selection scheme. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Several algorithms, methods and spreadsheets are being proposed by various researchers in this field to improve materials selection. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…The ANNs that were used in this project were Multilayer Perceptron (MLP), Learning Vector Quantization (LVQ) and Adaptive Network Based Fuzzy Inference System (ANFIS). The types of VOCs used for the classification were Acetone, Benzene, Chloroform, Ethanol and Methanol. …”
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Research Reports -
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2006“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). …”
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Usage count of hydrogen-based hybrid energy storage systems: An analytical review, challenges and future research potentials
Published 2024“…An extensive comparative study between �usage count� and �citation analysis� among the selected top 100 articles is provided. Moreover, a detailed keyword co-occurrence network (KCN) analysis along with comprehensive reviews concerning HESS modelling, optimization objectives, algorithms, system constraints, and research gaps are presented. …”
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Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing
Published 2018“…The prevention model uses principal component analysis and linear discriminant analysis with a hybrid, nature-inspired metaheuristic algorithm called Ant Lion optimisation for feature selection and artificial neural networks to classify and configure the cloud server. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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Static and self-scalable filter range selection algorithms for peer-to-peer networks
Published 2011“…For peer-to-peer networks, Loo (2005) selection algorithm has been selected as the benchmark as it is an established algorithm that claimed to be the best proposed for this network. …”
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Hybridflood algorithms minimizing redundant messages and maximizing efficiency of search in unstructured P2P networks
Published 2012“…We proposed two novel search algorithms named QuickFlood and HybridFlood. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…Three plant system were used in this study. First system is based on the ball and hoop system and second system is based on the DC servo motor. …”
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An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…In this study, the most significant features for enhancing the IDS efficiency and creating a smaller dataset in order to reduce the execution time for detecting attacks are selected from the sizeable network dataset. 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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The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.]
Published 2012“…Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. …”
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Book Section -
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…In comparison with V-Detectors, cuckoo search, differential evolution, support vector machine, artificial neural network, na¨ıve bayes, and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms other algorithms with an average detection rate of 95:30% on all the datasets. …”
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