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Optimization Methods for Customized Bus Routes in Random Environments
Published 2025-01-01Get full text
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Spatiotemporal heterogeneity of the ecological civilization in the Yangtze River economic belt
Published 2025-08-01Get full text
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning
Published 2025-07-01“…In these diversified test scenarios, the improved TD3 algorithm exhibits remarkable adaptability and stability. …”
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Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network
Published 2020-03-01Get full text
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COMPARATIVE ANALYSIS OF COLORING ALGORITHMS FOR ORDINARY WEIGHTED GRAPH
Published 2014-06-01Get full text
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Illustration Design Model with Clustering Optimization Genetic Algorithm
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection
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Applying Genetic Algorithm for test pattern generation process optimization
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Numerical Simulation of Diversion Tunnel Excavation Using GPU-Accelerated Anisotropic Random Fields
Published 2023-01-01Get full text
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Path Planning Algorithm for Manipulators in Complex Scenes Based on Improved RRT*
Published 2025-01-01“…Aiming at the problems of a six-degree-of-freedom robotic arm in a three-dimensional multi-obstacle space, such as low sampling efficiency and path search failure, an improved fast extended random tree (RRT*) algorithm for robotic arm path planning method (abbreviated as HP-APF-RRT*) is proposed. …”
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In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study
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Universal Simulation Model of Battery Degradation with Optimization of Parameters by Genetic Algorithm
Published 2022-12-01Get full text
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Precise wind allocation scheme decision based on attraction-repulsion algorithm
Published 2025-04-01Get full text
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Routing algorithm for heterogeneous computing force requests based on computing first network
Published 2025-02-01“…An optimized genetic algorithm to address this issue was proposed. This algorithm was designed from both local and global perspectives: to ensure fast convergence to the target solution locally, a single parameter satisfying the randomness strategy was used to initialize the population, making it widely dispersed in the solution space; adopting a multi-parameter solution (or path) balanced selection strategy for selection operations, making the selected population rich and diverse; adopting a two-layer crossover strategy for crossover operations, with the aim of expanding the breadth of global search; adopting a multi parameter random single point mutation strategy for mutation operations, with the aim of deepening local search capabilities. …”
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