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Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
TLDR
The results show that QEA performs well, even with a small population, without premature convergence as compared to the conventional genetic algorithm, and a Q-gate is introduced as a variation operator to drive the individuals toward better solutions.
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Genetic quantum algorithm and its application to combinatorial optimization problem
TLDR
The results show that GQA is superior to other genetic algorithms using penalty functions, repair methods and decoders and can represent a linear superposition of solutions due to its probabilistic representation.
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Quantum-Inspired Evolutionary Algorithms With a New Termination Criterion , H Gate , and Two-Phase Scheme
TLDR
The results show that the updated QEA makes QEA more powerful than the previous QEA in terms of convergence speed, fitness, and robustness.
Quantum-inspired evolutionary algorithms with a new termination criterion, Hepsilon gate, and two-phase scheme
TLDR
The results show that the updated QEA makes QEA more powerful than the previous QEA in terms of convergence speed, fitness, and robustness.
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Evolutionary programming techniques for constrained optimization problems
TLDR
Simulations indicate that the TPEP achieves an exact global solution without gradient information, with less computation time than the other optimization methods studied here, for general constrained optimization problems.
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Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots
TLDR
A novel sliding mode control law is proposed for asymptotically stabilizing the mobile robot to a desired trajectory and it is shown that the proposed scheme is robust to bounded external disturbances.
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Effective Background Model-Based RGB-D Dense Visual Odometry in a Dynamic Environment
TLDR
Experimental results demonstrate that the ego-motion is robustly obtained by BaMVO in a dynamic environment.
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A real-time limit-cycle navigation method for fast mobile robots and its application to robot soccer
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Parallel quantum-inspired genetic algorithm for combinatorial optimization problem
TLDR
Results show that PQGA is superior to QGA as well as other conventional genetic algorithms, and is able to possess the two characteristics of exploration and exploitation simultaneously.
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Online recurrent extreme learning machine and its application to time-series prediction
TLDR
A modified version of OS-ELM is proposed, called online recurrent extreme learning machine (OR- ELM), which is able to adjust input weights and can be applied to learn RNN, by applying ELM-auto-encoder and a normalization method called layer normalization (LN).
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