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complex function » complex functions (Expand Search)
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complex function » complex functions (Expand Search)
algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
both function » cost function (Expand Search)
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Application of Red Deer Algorithm in Optimizing Complex functions
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
Published 2024“…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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New enumeration algorithm for regular boolean functions
Published 2018“…After proving this equivalence, this paper introduces a novel data structure that may, with further tweaking, enable faster enumeration algorithms for both regular Boolean functions and all-capacities knapsack problem instances.…”
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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”
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A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks
Published 2012“…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …”
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A non-convex economic load dispatch problem using chameleon swarm algorithm with roulette wheel and Levy flight methods
Published 2023“…In this paper, several enhancements were made to this algorithm. First, it’s position updating process was slightly tweaked and took advantage of the chameleons’ randomization as well as adopting several time-varying functions. …”
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
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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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
Published 2013Get full text
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On the parameterized parallel complexity and the vertex cover problem
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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Iterative Methods for the Solution of a Steady State Biofilter Model
Published 2017Get full text
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Computational evluation of protein energy functions
Published 2014“…Proteins are organic compounds made up of chains of amino acids that fold into complex 3-dimensional structures based on their chemical and physical properties. …”
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From Collatz Conjecture to chaos and hash function
Published 2023“…<p>The non-linear property of Chaos is a promising approach to information security, and many accomplishments have been made by combining Chaos with several sub-security domains, including chaos-based stream ciphers, block ciphers, image encryption, and hash functions. Most Chaos-based hash functions are insecure or inefficient due to their dependence on complex, attacked multi-dimensional maps or uncertain, weak one-dimensional maps like logistic and tent. …”
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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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Cross entropy error function in neural networks
Published 2002“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995)
Published 1995Get full text
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