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Routing performance enhancement in hierarchical torus network by link-selection algorithm
Published 2005“…In this paper, we propose a link-selection algorithm for efficient use of physical links of the HTN, while keeping the link-selection algorithm as simple as the dimension-order routing algorithm. …”
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Dynamic communication performance enhancement in hierarchical torus network by selection algorithm
Published 2012“…This paper addresses three adaptive routing algorithms -- link-selection, channel-selection, and a combination of link-selection and channel-selection -- for the efficient use of physical links and virtual channels of an HTN to enhance dynamic communication performance. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…The basic concept of the GA is the natural selection and survival of the fittest, which is identical to the human genetic. …”
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IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…Selected basic behaviour-based algorithms such as wallfollower, obstacle avoidance, escape route and target detection are to be combined and its efficiency is measured. …”
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Final Year Project -
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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A detector generating algorithm for intrusion detection inspired by artificial immune system
Published 2015“…Artificial immune system (AIS) allows us to inspire several ideas for the design of computer intrusion detection.The standard of negative selection algorithm (NSA), offered by Stephanie Forrest in 1994, is one of the most common mechanisms in AIS that applied in anomaly detection for the similarity of its basic idea. …”
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The development of semantic meta-database: an ontology based semantic integration of biological databases
Published 2007“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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Monograph -
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Feature extraction and selection reduces the number of features. In this research, the shape and size feature were extracted using aspect ratio of selected morphological features. …”
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Hybridflood algorithms minimizing redundant messages and maximizing efficiency of search in unstructured P2P networks
Published 2012“…However, in a typical client-server network, as a client joins the network it only shares its demands, not its resources. Thus as more clients join the client-server network fewer resources are available to serve each client. …”
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Improving neural networks training using experiment design approach
Published 2005“…Randomly select the m data set for conventional training algorithm. …”
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A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana
Published 2018“…In recent times, speech technology and its related applications are becoming a popular topic among researchers. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad
Published 2016“…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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Power line faults classification by neural network train by Ant Colony Optimization
Published 2017“…The execution of this Ant Colony Optimization (ACO) usage was contrasted and that nonpartisan system and discovered it is more compelling than neural system. Metaheuristic algorithms are algorithms which, in order to escape from local optima, drive some basic heuristic: either a constructive heuristic starting from a null solution and adding elements to build a good complete one, or a local search heuristic starting from a complete solution and iteratively modifying some of its elements in order to achieve a better one. …”
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Student Project