Showing 1 - 20 results of 166 for search '(( algorithm which function ) OR ( algorithm loss function ))', query time: 0.09s Refine Results
  1. 1

    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

    Published 2022
    “…A precise prediction of blueberry harvest losses is necessary to mitigate such losses. The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”
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    Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

    Published 2023
    “…In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
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  5. 5

    Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach by Nargess Sadeghzadeh-Nokhodberiz (16904952)

    Published 2023
    “…The method is firstly developed in a centralized scheme and then extended to a distributed framework using appropriate asymptotically convergent consensus algorithms. Therefore, the asymptotic convergence of the designed distributed algorithm to the centralized one is guaranteed. …”
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    Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

    Published 2017
    “…In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”
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    Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

    Published 2024
    “…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”
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    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    Published 2023
    “…The proposed model determines a training dataset by covering all the aspects of cost function calculation. This training dataset helps to train the model, which allows for efficient decision-making in optimum energy usage. …”
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    Computational evluation of protein energy functions by Mansour, Nashat

    Published 2014
    “…A protein is characterized by its 3D structure, which defines its biological function. Proteins fold into 3D structures in a way that leads to low-energy state. …”
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    conferenceObject
  12. 12

    Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

    Published 2020
    “…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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    masterThesis
  13. 13

    Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

    Published 1998
    “…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …”
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    article
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    Evolutionary algorithm for protein structure prediction by Mansour, Nashat

    Published 2010
    “…A protein is characterized by its 3D structure, which defines its biological function. The protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. …”
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    conferenceObject
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    Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

    Published 2006
    “…Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. …”
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    article
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    A new reactive power optimization algorithm by Mantawy, A.H.

    Published 2003
    “…A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active power loss. …”
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    article
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    Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

    Published 2018
    “…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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    article
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    Belief selection in point-based planning algorithms for POMDPs by Azar, Danielle

    Published 2017
    “…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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    conferenceObject
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    Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

    Published 2022
    “…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …”
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    Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

    Published 1999
    “…The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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    article