The flowchart of Algorithm 2. حسب Jing Xu (15337)

"…For the former, it is further divided into two sub-problems according to the stochastic nature of passenger no-show behavior, which is optimized iteratively. Finally, the effectiveness of the proposed model and algorithm is evaluated through numerical studies. …"

Algorithms runtime comparison. حسب Meilin Zhu (688698)

"…Secondly, based on the idea of pre-optimization and dynamic adjustment, a two-stage dynamic optimization model of agricultural products joint distribution network under vehicles and customers sharing is established. …"

Solution results of different algorithms. حسب Meilin Zhu (688698)

"…Secondly, based on the idea of pre-optimization and dynamic adjustment, a two-stage dynamic optimization model of agricultural products joint distribution network under vehicles and customers sharing is established. …"

Parameters of joint significance test. حسب Yixuan Lu (9987980)

Train stopping plan. حسب Jing Xu (15337)

"…For the former, it is further divided into two sub-problems according to the stochastic nature of passenger no-show behavior, which is optimized iteratively. Finally, the effectiveness of the proposed model and algorithm is evaluated through numerical studies. …"

Major notations. حسب Jing Xu (15337)

"…For the former, it is further divided into two sub-problems according to the stochastic nature of passenger no-show behavior, which is optimized iteratively. Finally, the effectiveness of the proposed model and algorithm is evaluated through numerical studies. …"

S1 File - حسب Jing Xu (15337)

"…For the former, it is further divided into two sub-problems according to the stochastic nature of passenger no-show behavior, which is optimized iteratively. Finally, the effectiveness of the proposed model and algorithm is evaluated through numerical studies. …"

Pre-optimization iteration process. حسب Meilin Zhu (688698)

"…Secondly, based on the idea of pre-optimization and dynamic adjustment, a two-stage dynamic optimization model of agricultural products joint distribution network under vehicles and customers sharing is established. …"

The convergence behavior of our proposed algorithm for randomly synthesized kinematic data. حسب Mahdi Khoramshahi (14271668)

Parameters of each algorithm. حسب Nanqi Li (11640083)

Feature quantity and number. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Diagnostic accuracy of different models. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Average accuracy of different feature quantities. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Scatter diagram of different principal elements. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Key parameters of LightGBM. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Multi-model fault diagnosis results. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Compares the optimization results. حسب Nanqi Li (11640083)

Before and after optimization design variables. حسب Nanqi Li (11640083)

Table_1_Probabilistic Optimal Power Flow Calculation Method Based on Adaptive Diffusion Kernel Density Estimation.docx حسب Guoqing Li (23674)

"…<p>To accurately evaluate the influence of the uncertainty and correlation of photovoltaic (PV) output and load on the running state of power system, a probabilistic optimal power flow (POPF) calculation method based on adaptive diffusion kernel density estimation is proposed in this paper. …"

Rank-Based Greedy Model Averaging for High-Dimensional Survival Data حسب Baihua He (12885034)

"…We further adopt the greedy algorithm for high dimensions. Theoretically, we derive an asymptotic error bound for the optimal weights under some mild conditions. …"