Showing 1 - 20 results of 31 for search '(((( movement data algorithm ) OR ( waste processing algorithm ))) OR ( neural coding algorithm ))', query time: 0.14s Refine Results
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    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. It is based on studies into the movement of bird flocks. …”
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    Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

    Published 2020
    “…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO<sub>3</sub> on the performance of anaerobic digestion (AD) process. …”
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    RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems. by Sebastian Kruse (18595195)

    Published 2020
    “…Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. …”
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    Towards Scalable Process Mining Pipelines by Mohamed, Belal

    Published 2023
    “…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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    Investigation of Forming a Framework to shortlist contractors in the tendering phase by DABASH, MOHANNAD SALAH

    Published 2022
    “…The model to shortlist contractors in the tendering phase was created using machine learning to enable more contractors to submit for a project without having to waste time and money on the tendering process; if they are compatible with the project, then they have a high chance of getting it by being short-listed for the project, which they can then submit their tender package for; this will also ensure that the best company gets the job for the client which will act as a great step towards improving the tendering in construction projects. …”
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