Search Results - (( java implication based algorithm ) OR ( knowledge information swarm algorithm ))
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Optimizing the Management of Knowledge Assets using Swarm Intelligence
Published 2018“…This study presents the employment of swarm intelligence algorithm, i.e Firefly Algorithm, to automatically cluster text document without the use of k value. …”
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Document clustering for knowledge discovery using nature-inspired algorithm
Published 2014“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
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Nature inspired data mining algorithm for document clustering in information retrieval
Published 2014“…Document clustering is an important technique that has been widely employed in Information Retrieval (IR). Various clustering techniques have been reported, but the effectiveness of most techniques relies on the initial value of k clusters.Such an approach may not be suitable as we may not have prior knowledge on the collection of documents.To date, there are various swarm based clustering techniques proposed to address such problem, including this paper that explores the adaptation of Firefly Algorithm (FA) in document clustering. …”
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A novel approach to data mining using simplified swarm optimization
Published 2011“…This deficiency has prompted the need for a new intelligent data mining technique based on stochastic population-based optimization that could discover useful information from data. In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
Published 2017“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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Application of the Whale Optimization Algorithm (WOA) in Reservoir Optimization Operation Under Investigation of Climate Change Impact: A Case Study at Klang Gate Dam, Malaysia
Published 2024“…The effectiveness of analyzing large amounts of data that comes with engaging climate change scenarios, for planning advanced reservoir management can be achieved through the use of optimization algorithms. The Whale Optimization Algorithm (WOA) is a swarm intelligence algorithm derived following animal-behaviour-based concepts. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
Published 2024“…This study proposed a motion planning and control strategy for an autonomous vehicle collision avoidance system based on the potential field (PF) approach with a combination of the parameter scheduling technique. A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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Book Chapter -
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Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
Published 2024“…This study proposed a motion planning and control strategy for an autonomous vehicle collision avoidance system based on the potential field (PF) approach with a combination of the parameter scheduling technique. A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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