Search Results - (( parameter adoption using algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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3
Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model
Published 2018“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. …”
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A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem
Published 2020“…As such, the adoption of parameter free meta-heuristic algorithms is often straightforward. …”
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5
Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model
Published 2018“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. …”
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Evaluation of outlier filtering algorithms for accurate measurement of travel time reliability incorporating lane-splitting situations / Obada M. A. Asqool
Published 2022“…Thus, the Jang algorithm and TransGuide algorithm could be used after calibrating their parameters for each day. …”
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7
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…Although useful, all aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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8
Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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10
An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite
Published 2018“…Although useful, most of the aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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Adopting Jaya Algorithm for Team Formation Problem
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Automatic control of flotation process using computer vision
Published 2015“…The performance of improved marker based watershed algorithm was validated by using several industrial and laboratory froth images. …”
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13
Modified Parameters of Harmony Search Algorithm for Better Searching
Published 2017“…The contributions to this research are the HMCR parameter using step function while the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter. …”
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14
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing
Published 2022“…The purpose of this review is to revisit and carry out up-to-date review on these distinguished algorithms with their respective current state of use. …”
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Weighting method for modal parameter based damage detection algorithms
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…However, different clustering algorithms have different parameters that need to be specified. …”
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Book Chapter -
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On determination of input parameters of the mass transfer process by fuzzy approach.
Published 2005“…The algorithm is also capable of determining the optimal values of the input parameters. …”
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Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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