Rustproof 发表于 2025-3-30 10:59:02
Route Scheduling System for Multiple Self-driving Cars Using K-means and Bio-inspired AlgorithmsS against GA, ACS and Particle Swarm Optimization (PSO) initialized with random population. The results showed that, as the number of cars and target locations increase, the hybrid approaches outperform GA, ACS and PSO without any pre-processing.防水 发表于 2025-3-30 12:40:08
Novel Decision Forest Building Techniques by Utilising Correlation Coefficient Methodsl results indicate that the proposed methods have the best average ensemble accuracy rank of 1.3 (for MICF) and 3.0 (for PCCF), compared to their closest competitor, Random Forest (RF), which has an average rank of 4.3. Additionally, the results from Friedman and Bonferroni-Dunn tests indicate statistically significant improvement.躲债 发表于 2025-3-30 19:52:26
http://reply.papertrans.cn/32/3108/310706/310706_53.png反省 发表于 2025-3-30 23:21:51
http://reply.papertrans.cn/32/3108/310706/310706_54.png阻碍 发表于 2025-3-31 02:53:57
http://reply.papertrans.cn/32/3108/310706/310706_55.pngcacophony 发表于 2025-3-31 05:30:17
http://reply.papertrans.cn/32/3108/310706/310706_56.pngWater-Brash 发表于 2025-3-31 12:41:53
Evaluating Acceleration Techniques for Genetic Neural Architecture Searchensive neural architecture search approach, and aims to pave the way for speeding up such algorithms by assessing the effect of acceleration methods on the overall performance of the neural architecture search procedure as well as on the produced architectures.食草 发表于 2025-3-31 15:42:51
Generation of Orthogonality for Feature Spaces in the Bio-inspired Neural Networksrthogonality basis functions create better tracking results. Thus, asymmetric structure of the network and its nonlinear characteristics are shown to be effective factors for generating orthogonality.labyrinth 发表于 2025-3-31 18:09:49
http://reply.papertrans.cn/32/3108/310706/310706_59.png偏离 发表于 2025-3-31 22:26:45
The Effectiveness of Synchronous Data-parallel Differentiable Architecture Searchinal results due to the pruning before extracting the final network. As a result, we achieve a speedup of 1.82 for two GPU workers and a 3.18 speedup for four GPU workers while retaining the same qualitative results as serially executing DARTS.