Search Results - (( parallel optimization path algorithm ) OR ( _ utilisation data algorithm ))
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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Minimizing machining airtime motion with an ant colony algorithm
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors
Published 2008“…Different adder architectures are investigated for suitability on synthesis implementation of large data bus size adder for efficient usage within the ALU. An adder algorithm using repetitive constructs in a parallel algorithm that allows for efficient and optimal synthesis for large data bus size is proposed as a suitable implementation for the adder within the ALU. …”
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Heuristic task scheduling algorithms for optimal resource utilisation in grid computing
Published 2020“…The results of the two experimental scenarios showed that suf rage algorithm produced the best resource utilisation among the three investigated heuristic scheduling algorithms.…”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
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Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques
Published 2017“…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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Smart grid: Bio-inspired algorithms energy distributions for data centers
Published 2025“…These algorithms aim to reduce power consumption, improve resource utilisation, and enhance overall data centre efficiency. …”
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Financial time series predicting using machine learning algorithms
Published 2013“…Subsequently, Dynamic Time Warping (DTW) algorithm is utilised through brute force to predict the trend movement. …”
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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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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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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…Then, the outcomes demonstrated that the best classifier for categorizing our data with 0.96% accuracy is the Decision Tree machine learning algorithm. …”
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Student Project -
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Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing
Published 2025“…The algorithm explicitly considers SLA compliance, energy efficiency, resource utilisation, and migration overhead. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Besides, some real data sets were examined to validate the proposed algorithm. …”
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Hybrid Spatial-Artificial Intelligence Approach for Renewable Energy Sources Sites Identification and Integration in Sarawak State
Published 2022“…From this, the spatial criteria scheme data is produced. The MCDM-AHP algorithm is applied to the criteria scheme data to identify the number of RES sites. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm
Published 2025“…In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023“…This algorithm can also be used for task scheduling. The proposed algorithm efficiently maps and achieves the objective function for server consolidation, optimising energy consumption, VM migrations, and server utilisation. …”
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