3.2.3. Comparison with other machine learning methods Seven machine learning models, which are multi-layer perception (MLP), support vector regressor (SVR), random forest, Decision tree, LightGBM, XGBoost, and
For a more profound compre- hension of systems, mathematical models are frequently employed in conjunction with experiments. Explaining pol- lutant removal in MAR involves understanding the intricate relationships among influential soil and water characteris- tics. Due to its intricacy, conventional ...
Long-range character is addressed computationally in periodic boundary conditions for simulation with the Ewald summation approach [16]. In its conventional form, this approach is efficient and scales well with the number of charges carried. Electrostatic solvers such as particle-particle and particle-...
First efforts have been taken, to identify relevant chemical features from such representations, which also points to one major challenge of these algorithms, which is their "black box" character. It is very difficult to extract from deep neural networks, why certain compounds are predicted to be...
Lifespan estimation during the designing stage supports reliability, which states the character of a population of elements. The RUL does not forecast the lifespan of a collection of parts; rather, it forecasts the remaining lifespan of a specific element in facility-oriented condition checking ...
These interactions may be further enhanced by the inclusion of specific functionalities or moieties on the backbone. The addition of bioactive factors to conducting polymers allows fabricating hybrid materials with improved conductive properties in terms of cell-to-cell and cell-to-materials interactions....
2015, 16, 27677–27706 transition of the thermo-responsive macromolecule and occurs at a characteris critical solution temperature. Polymers that exhibit a phase separation on heat 2.1. Macromers with Dual (Physical and cCrhiteimcaiclaslo)lGuetiloatniotnemPrpoeprearttuierse (LCST) while gelation ...