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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization algorithm. …”
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Simulated Annealing and Genetic Algorithms for Optimal Regression Testing
Published 1999“…We present two natural optimization algorithms, namely, a simulated annealing and a genetic algorithm, for solving this problem. …”
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Indoor Localization Based on Floor Plans and Power Maps
Published 2015“…An indoor localization algorithm that is based on fingerprinting and trilateration is developed. …”
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46
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A genetic algorithm for corrective retesting. (c1995)
Published 1995Get full text
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masterThesis -
48
Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests
Published 2023“…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …”
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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
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Multiclass feature selection with metaheuristic optimization algorithms: a review
Published 2022“…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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Parallel physical optimization algorithms for allocating data to multicomputer nodes
Published 1994“…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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A Survey of cuckoo search algorithm: optimizer and new applications
Published 2024“…Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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masterThesis -
54
Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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55
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Optimal selection of the forgetting matrix into an iterative learning control algorithm
Published 2005“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm
Published 2005“…A new Strength Pareto Evolutionary Algorithm based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. …”
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MSLP: mRNA subcellular localization predictor based on machine learning techniques
Published 2023“…We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.…”
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