Search Results - (( evolution classification technique algorithm ) OR ( data optimisation system algorithm ))
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Article -
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…These fine-tuning techniques continue to be the object of ongoing research. …”
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm
Published 2025“…Overall, the proposed approach shows promise in enhancing the efficiency and responsiveness of real-world waste collection systems. Future work may focus on integrating real-time data, adjusting algorithm parameters and hybridizing ABC algorithm with other metaheuristics to further improve performance.…”
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Student Project -
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Smart grid: Bio-inspired algorithms energy distributions for data centers
Published 2025“…This project proposes and evaluates three bio-inspired and evolutionary algorithms for VM allocation and migration: Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), and a Modified Genetic Algorithm (MGA). …”
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Final Year Project / Dissertation / Thesis -
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing
Published 2018“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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Email spam classification based on deep learning methods: A review
Published 2025“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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Analysis on target detection and classification in LTE based passive forward scattering radar
Published 2016“…By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. …”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation
Published 2011“…Unlike a conventional PSOIACO algorithm, this hybrid algorithm shows improvement of the classification accuracy in its generated rough reducts to solve NP-Hard problem. …”
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Conference or Workshop Item -
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Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation
Published 2017“…This work simulates traffic system and develop an optimising algorithm to instruct the traffic signal timing plan. …”
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Proceedings -
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
Published 2023“…A slanted GFPS with orientation angle of 30° and all edges clamped was developed and fabricated to represent the actual dynamics of the system. Then, data acquisition and instrumentation system were integrated to the rig to collect the input-output vibration data. …”
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Thesis -
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Book Section -
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