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Titlebook: Bio-inspired Computing: Theories and Applications; 12th International C Cheng He,Hongwei Mo,Yuxin Zhao Conference proceedings 2017 Springer

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Multi-objective Optimization for Ladle Tracking of Aluminium Tapping Based on NSGA-II, uses exchange mutation (EM) operator. Finally, the practical production data of the aluminium factory is used to verify the validity and practicability of the method, and the results show that this method can obtain a feasible solution for the user to choose suitable solutions, and avoid the defect
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https://doi.org/10.1007/978-981-15-1408-1mber Complementer based on two-domain DNA strand displacement is proposed in this paper. It implements the function of converting binary code into complement code. Simulation experiment based on Visual DSD software is carried out. The simulation results show the correctness and feasibility of the lo
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https://doi.org/10.1007/978-981-15-1408-1es the robots a high level of adaptability and robustness. Given an initial configuration and a goal configuration of the robot, the problem of self-regulation consists on finding a sequence of module moves that will reconfigure the robot from the initial configuration to the goal configuration. In
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https://doi.org/10.1007/978-981-15-1408-1 exhaustive search is computationally expensive when searching for thresholds. In order to solve such challenging problems, the fitness function is designed by the maximum entropy method, the optimal threshold of segmentation is found by using the parallel optimization mechanism of Flower Pollinatio
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https://doi.org/10.1007/978-981-15-1408-1ormous potential to assist designers in enhancing the range of alternative arrangements and in expediting the design process. This paper presents a hybrid evolutionary algorithm to handle the multi-objective constrained arrangements optimization problem based on elitist non-dominated sorting strateg
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https://doi.org/10.1007/978-981-15-1408-1ent system is proposed. Three Filter methods’ results are aggregated to provide the stability information, and feature selection stability and classification accuracy are adopted as two optimization objectives. Weighted sum, weighted product and biobjective optimization methods together are applied
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