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algorithm step » algorithm its (Expand Search), algorithm sma (Expand Search), algorithm survey (Expand Search)
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1
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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2
Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems
Published 2023“…Recently, optimization problems have been revised in many domains, and they need powerful search methods to address them. In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
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3
A Comparative Study of Elgamal Based Cryptographic Algorithms
Published 2004“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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4
Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
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5
A comparative study of ElGamal based digital signature algorithms
Published 2006“…We implement the classical and modified ElGamal digital signature scheme to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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6
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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An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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8
Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
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9
Stochastic evolution algorithm for technology mapping
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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10
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. A protein is characterized by its 3D structure, which defines its biological function. …”
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11
Metaheuristic Algorithm for State-Based Software Testing
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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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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13
Application of Red Deer Algorithm in Optimizing Complex functions
Published 2021“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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14
Tracking analysis of normalized adaptive algorithms
Published 2003“…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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15
Evolutionary algorithm for protein structure prediction
Published 2010“…A protein is characterized by its 3D structure, which defines its biological function. …”
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16
Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
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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17
New enumeration algorithm for regular boolean functions
Published 2018“…This paper introduces a new algorithm for enumerating regular Boolean functions. …”
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18
Random vector functional link network: Recent developments, applications, and future directions
Published 2023“…Finally, we present potential future research directions/opportunities that can inspire the researchers to improve the RVFL’s architecture and learning algorithm further. </p> <h2>Other Information</h2> <p>Published in: Applied Soft Computing<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/ </a> <br> See article on publisher's website: <a href="http://dx.doi.org/10.1016/j.asoc.2023.110377" target="_blank">http://dx.doi.org/10.1016/j.asoc.2023.110377</a> </p>…”
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study
Published 2020“…The benchmark problem used is the floorplanning of very large scale integrated (VLSI) circuits. This is a hard multi-criteria optimization problem. Fuzzy logic is used to combine all objective criteria into a single fuzzy evaluation (cost) function, which is then used to rate competing solutions. # 2001 Elsevier Science Ltd. …”
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20
Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
Published 2000“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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