Based on design, concrete can be classified into plain cement concrete (PCC), Steel reinforced concrete (RCC), fibre-reinforced concrete (FRC) and pre-stressed concrete. In Plain Cement Concrete, no steel reinforcement is provided.选择语言:从 到 ...
Optimal reinforcement scheme of anchor cables can be determined based on slope stress and displacement fields. By comparing the factor of safety and stress field before and after slope reinforcement, it is found that better reinforcement results can be achieved if strong reinforcement is applied upon...
Validate the implementation by making it run on harder and harder envs (you can compare results against the RL zoo). You usually need to run hyperparameter optimization for that step. You need to be particularly careful on the shape of the different objects you are manipulating (a broadcast ...
can be used to clearly compare the orientation degree of the polymer chains of both hydrogels during stretching, but the uniformity of the orientation structure at the submicron scale is unknown. The orientation uniformity can be visually compared through the SEM images of TDN hydrogel (Fig.3b) ...
32. The models in the model space can be categorized into four families: ABSOLUTE model (ABS), RELATIVE models (REL), ASYMMETRIC models (ASYM), and RELATIVE-ASYMMETRIC models (RELASYM). The ABS model is the baseline model. Other models were built up based on the ABS model and assumed ...
Animals rely on learned associations to make decisions. Associations can be based on relationships between object features (e.g., the three leaflets of poison ivy leaves) and outcomes (e.g., rash). More often, outcomes are linked to multidimensional states (e.g., poison ivy is green in su...
Operating such a hybrid bike-sharing system, i.e., with both bikes and ebikes, in a competitive multi-platform market, can be challenging due to the complex and unpredictable interplay among heterogeneous market participants, which becomes more pronounced with the ebike varying battery, and ...
By utilizing ANNs such as pointer networks [8], researchers were able to generalize multi-objective deep reinforcement learning algorithms so that they can be trained on a small-scale TSP (like a TSP with just 40 cities), but can find optimal solutions for large scale TSPs (with even more...
The SAC is a reinforcement learning algorithm based on the actor–critic structure. The actor is the policy function to generate actions that the agent uses to interact with the environment, represented by 𝜋𝜙(𝑎𝑡|𝑠𝑡)πϕ(at|st). The policy update equation can be obtained by...
Based on this model-free learning approach, integrated optimization results can be obtained in shorter times, and the better one in limited learning episodes is provided in Figure 3. The integrated optimization result consists of a job sequence {Job 10, Job 2, Job 1, Job 7, Job 9}Job 10...