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Learning continuous functions using decision tree learning algorithms
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New enumeration algorithm for regular boolean functions
Published 2018“…This algorithm exploits the equivalence between regular Boolean functions and positive threshold functions that can be used to represent instances of the knapsack problem. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…The algorithm is tested using 200 randomly generated 2-variable 4-valued functions. …”
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A New Penalty Function Algorithm For Convex Quadratic Programming
Published 2020“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems
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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Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm
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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Computational evluation of protein energy functions
Published 2014“…However, the energy functions proposed so far by biophysicists and biochemists are still in the exploration phase and their usefulness has been demonstrated only individually. …”
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Evolution Of Activation Functions for Neural Architecture Search
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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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control
Published 2022“…The proposed algorithm (Ls-AOA) was tested against unimodal and multimodal benchmark functions and demonstrated better capability comparatively using other efficient metaheuristic algorithms reported in the literature. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
Published 2023“…<p dir="ltr">The problem of formation tracking control for a group of quadcopters with nonlinear dynamics using Barrier Lyapunov Functions (BLFs) is studied in this paper where the quadcopters are following a desired predefined trajectory in a predefined formation shape. …”
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Cross entropy error function in neural networks
Published 2002“…The ANN is implemented using the cross entropy error function in the training stage. …”
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Radial basis function networks for contingency analysis of bulkpower systems
Published 1999“…Radial basis function networks (RBFNs) are used for contingency evaluation of bulk power system. …”
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