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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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Belief selection in point-based planning algorithms for POMDPs
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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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study
Published 2020“…The termevolutionary algorithmis used to refer to any probabilistic algorithmwhose design is inspired by evolutionary mechanisms found in biological species. Most widely known algorithms of this category are genetic algorithms (GA). …”
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…In this paper, a multiswarm-intelligence-based algorithm (MSIA) is developed to cope with bound constrained functions. …”
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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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Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise
Published 2005“…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…The solution obtained shows that the proposed scheduling algorithm meets the communication system's requirements while conserving power and energy resources.…”
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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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Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems
Published 2022“…The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.…”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…An intrusion detection system (IDS) is the most promising solution for preventing malicious intrusions and tracing suspicious network behavioral patterns. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. …”
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From Collatz Conjecture to chaos and hash function
Published 2023“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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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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