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intelligent optimisation techniques: genetic algorithms, tabu search, simulated annealing and neural networks  (Verlag GmbH)

 
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    Verlag GmbH intelligent optimisation techniques: genetic algorithms, tabu search, simulated annealing and neural networks
    Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing And Neural Networks, supplied by Verlag GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/neural+network+algorithm/intelligent+optimisation+techniques++genetic+algorithms++tabu+search++simulated+annealing+and+neural+networks/us09710299-194-31-46
    Average 90 stars, based on 1 article reviews
    intelligent optimisation techniques: genetic algorithms, tabu search, simulated annealing and neural networks - by Bioz Stars, 2026-10
    90/100 stars

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    other:

    Article Title: A Finite-Differences Derivative-Descent Approach for Estimating Form Error in Precision-Manufactured Parts
    Article Snippet: Background: Form-error measurement is mandatory for the quality assurance of manufactured parts and plays a critical role in precision engineering.. There is now a significant literature on analytical methods of form-error measurement, which either use mathematical properties of the relevant objective function or develop a surrogate for the objective function that is more suitable in optimization.. On the other hand, computational or numerical methods, which only require the numeric values of the objective function, are less studied in the literature on form-error metrology.

    Article Title: Method and a computer program product for controlling the execution of at least one application on or for a mobile electronic device, and a computer
    Article Snippet: Self-learning algorithms that can be used in such classifier generation can be found e.g. in B. Kröse, P. Smagt, An introduction to Neural Networks, University of Amsterdam, November 1996; D. Karaboga, D. Pham, Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks, Springer Verlag, 2000; F. Divina, E. Marchiori, Handling Continuous Attributes in an Evolutionary Inductive Learner, published in IEEE Transactions on Evolutionary Computation, vol.



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    The optimal results of included studies by the algorithm.

    Journal: Nursing & Health Sciences

    Article Title: A Systematic Review of the Accuracy of Machine Learning Models for Diagnosing Pulmonary Tuberculosis: Implications for Nursing Practice and Implementation

    doi: 10.1111/nhs.70077

    Figure Lengend Snippet: The optimal results of included studies by the algorithm.

    Article Snippet: The Gaussian‐fuzzy‐neural network (GFNN) algorithm, used in one study ( n = 1 study, 8.3%) (Mithra and Sam Emmanuel ), was effective for analyzing sputum smear microscopic images.

    Techniques: Plasmid Preparation